The status page's walkthrough (M6.6b)

A new package, nisse-ui: a read-only page for studying how the agents
work. For each work item it shows the steps (what people and the
orchestrator said, and each run), each run's turns, and each turn's
request read against the log it was made from:
- each message beside the events it came from, tagged unchanged,
  labelled, narrated, shortened (by how much) or a compaction, with what
  fitting dropped;
- what is new since the turn before, and where the request first
  differs (where prompt reuse had to stop), next to the server's count;
- the reply with its reasoning, and the raw JSON.

Runs going in circles are flagged by nisse_core.loop.circles (repeated
near-identical replies, one correction given again and again, repeated
apologies), a pure function M7.8 can reuse in Driver.run.

In nisse-core:
- render.py: message_indexes(), from the same code render() uses, so
  the page's matching can't drift from what was sent.
- calls.py: the record notes when recording began; the reader gains
  calls_for(item) and call(id).
- state/readonly.py: opens an agent's SQLite file without creating its
  -wal/-shm files (mode=ro alone does, once the writer has closed).

The page reads only through read-only connections, escapes everything,
and sends a Content Security Policy that allows no script. It listens on
127.0.0.1; until M6.6d puts it behind Authelia, reach it over an SSH
tunnel. Jinja2 is its one new dependency, for autoescaping.

Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01J5Utyfzw7gF7UhjRDEtjTk

Dockerfile

@@ -30,6 +30,7 @@ COPY nisse-core nisse-core
 COPY nisse-dev nisse-dev
 COPY nisse-ops nisse-ops
 COPY nisse-review nisse-review
+COPY nisse-ui nisse-ui
 
 # nisse-dev and what it needs, installed (not editable): the source tree
 # isn't part of the image.

bench/results/2026-10-23-qwen3.8-27b.jsonl

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+{"backing": "openai/qwen3.8-27b", "check_output": ".......                                                                  [100%]\n7 passed in 0.23s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 58265, "tokens_out": 3548, "trimmed_requests": 0, "ts": "2026-10-23T23:32:24+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 82.7}
+{"backing": "openai/qwen3.8-27b", "check_output": ".......                                                                  [100%]\n7 passed in 0.26s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 51177, "tokens_out": 3971, "trimmed_requests": 0, "ts": "2026-10-23T23:33:57+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 92.2}
+{"backing": "openai/qwen3.8-27b", "check_output": "%]\n=================================== FAILURES ===================================\n_________________ test_the_plan_asked_for_tests_and_they_pass __________________\n\n    def test_the_plan_asked_for_tests_and_they_pass() -> None:\n        # At least one valid and one invalid input for each of the eight rules.\n        import subprocess\n        import sys\n    \n        run = subprocess.run(\n            [sys.executable, \"-m\", \"pytest\", \"-q\", \"test_durations.py\"],\n            capture_output=True,\n            text=True,\n            check=False,\n        )\n>       assert run.returncode == 0, run.stdout[-1500:]\nE       AssertionError: ..F...............                                                       [100%]\nE         =================================== FAILURES ===================================\nE         _______________________________ test_rule2_valid _______________________________\nE         \nE             def test_rule2_valid():\nE                 assert parse_duration(\"1H30M\") == 5400\nE         >       assert parse_duration(\"2D1h\") == 172800\nE         E       AssertionError: assert 176400 == 172800\nE         E        +  where 176400 = parse_duration('2D1h')\nE         \nE         test_durations.py:34: AssertionError\nE         =========================== short test summary info ============================\nE         FAILED test_durations.py::test_rule2_valid - AssertionError: assert 176400 ==...\nE         1 failed, 17 passed in 0.03s\nE         \nE       assert 1 == 0\nE        +  where 1 = CompletedProcess(args=['/usr/bin/python', '-m', 'pytest', '-q', 'test_durations.py'], returncode=1, stdout='..F.......... test_durations.py::test_rule2_valid - AssertionError: assert 176400 ==...\\n1 failed, 17 passed in 0.03s\\n', stderr='').returncode\n\n.bench_check/test_hidden.py:87: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n1 failed, 48 passed in 0.30s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `python -m pytest -q test_durations.py`: alueError'>\n\ntest_durations.py:10: Failed\n=========================== short test summary info ============================\nFAILED test_durations.py::test_rule2_valid - KeyError: 'H'\nFAILED test_durations.py::test_rule6_invalid - Failed: DID NOT RAISE <class '...\n2 failed, 16 passed in 0.06s\n\nstderr:; `python -m pytest -q test_durations.py`: 00 == 172800\nE        +  where 176400 = parse_duration('2D1h')\n\ntest_durations.py:34: As", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 67972, "tokens_out": 26798, "trimmed_requests": 0, "ts": "2026-10-23T23:44:01+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 603.8}
+{"backing": "openai/qwen3.8-27b", "check_output": "................................................F                        [100%]\n=================================== FAILURES ===================================\n_________________ test_the_plan_asked_for_tests_and_they_pass __________________\n\n    def test_the_plan_asked_for_tests_and_they_pass() -> None:\n        # At least one valid and one invalid input for each of the eight rules.\n        import subprocess\n        import sys\n    \n        run = subprocess.run(\n            [sys.executable, \"-m\", \"pytest\", \"-q\", \"test_durations.py\"],\n            capture_output=True,\n            text=True,\n            check=False,\n        )\n        assert run.returncode == 0, run.stdout[-1500:]\n        summary = run.stdout.strip().splitlines()[-1]\n>       assert int(summary.split()[0]) >= 16, summary\nE       AssertionError: 10 passed in 0.02s\nE       assert 10 >= 16\nE        +  where 10 = int('10')\n\n.bench_check/test_hidden.py:89: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n1 failed, 48 passed in 0.30s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 45446, "tokens_out": 24240, "trimmed_requests": 0, "ts": "2026-10-23T23:53:06+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 543.7}
+{"backing": "openai/qwen3.8-27b", "check_output": ".................................................                        [100%]\n49 passed in 0.32s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 42076, "tokens_out": 21588, "trimmed_requests": 0, "ts": "2026-10-24T00:01:12+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 485.9}
+{"backing": "openai/qwen3.8-27b", "check_output": "t_durations.py::test_unit_form_valid[45s-45] - ValueError: invalid ...\nE         FAILED test_durations.py::test_case_valid - ValueError: invalid duration: '1d...\nE         FAILED test_durations.py::test_decimals_valid[1.5h-5400] - ValueError: invali...\nE         FAILED test_durations.py::test_decimals_valid[1.5m-90] - ValueError: invalid ...\nE         FAILED test_durations.py::test_decimals_valid[0.5m-30] - ValueError: invalid ...\nE         FAILED test_durations.py::test_zero_valid - ValueError: invalid duration: '0s'\nE         8 failed, 48 passed in 0.10s\nE         \nE       assert 1 == 0\nE        +  where 1 = CompletedProcess(args=['/usr/bin/python', '-m', 'pytest', '-q', 'test_durations.py'], returncode=1, stdout='F.FF....F.... test_durations.py::test_zero_valid - ValueError: invalid duration: \\'0s\\'\\n8 failed, 48 passed in 0.10s\\n', stderr='').returncode\n\n.bench_check/test_hidden.py:87: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_valid[2h-7200] - ValueError: invalid...\nFAILED .bench_check/test_hidden.py::test_valid[1d2h3m4s-93784] - ValueError: ...\nFAILED .bench_check/test_hidden.py::test_valid[45s-45] - ValueError: invalid ...\nFAILED .bench_check/test_hidden.py::test_valid[1d-86400] - ValueError: invali...\nFAILED .bench_check/test_hidden.py::test_valid[2D-172800] - ValueError: inval...\nFAILED .bench_check/test_hidden.py::test_valid[1d 2h 3m 4s-93784] - ValueErro...\nFAILED .bench_check/test_hidden.py::test_valid[1.5h-5400] - ValueError: inval...\nFAILED .bench_check/test_hidden.py::test_valid[1.5m-90] - ValueError: invalid...\nFAILED .bench_check/test_hidden.py::test_valid[0.25h-900] - ValueError: inval...\nFAILED .bench_check/test_hidden.py::test_valid[0s-0] - ValueError: invalid du...\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - ValueError: i...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n12 failed, 37 passed in 0.37s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `python -m pytest -q test_durations.py`: .py:100: ValueError\n=========================== short test summary info ============================\nFAILED test_durations.py::test_order_valid - ValueError: invalid duration: '2...\nFAILED test_durations.py::test_spaces_valid - ValueError: invalid duration: '...\n2 failed, 54 passed in 0.08s\n\nstderr:; `python -m pytest -q test_durations.py`: ValueError: invali...\nFAILED test_durations.py::test_decimals_valid[1.5m-90] - ValueErro", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 46209, "tokens_out": 17440, "trimmed_requests": 0, "ts": "2026-10-24T00:07:44+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 391.1}
+{"backing": "openai/qwen3.8-27b", "check_output": "%]\n=================================== FAILURES ===================================\n_________________ test_the_plan_asked_for_tests_and_they_pass __________________\n\n    def test_the_plan_asked_for_tests_and_they_pass() -> None:\n        # At least one valid and one invalid input for each of the eight rules.\n        import subprocess\n        import sys\n    \n        run = subprocess.run(\n            [sys.executable, \"-m\", \"pytest\", \"-q\", \"test_durations.py\"],\n            capture_output=True,\n            text=True,\n            check=False,\n        )\n>       assert run.returncode == 0, run.stdout[-1500:]\nE       AssertionError: ....F............                                                        [100%]\nE         =================================== FAILURES ===================================\nE         ____________________________ test_rule3_order_valid ____________________________\nE         \nE             def test_rule3_order_valid():\nE                 assert parse_duration(\"1d\") == 86400\nE         >       assert parse_duration(\"1d2h\") == 90000\nE         E       AssertionError: assert 93600 == 90000\nE         E        +  where 93600 = parse_duration('1d2h')\nE         \nE         test_durations.py:43: AssertionError\nE         =========================== short test summary info ============================\nE         FAILED test_durations.py::test_rule3_order_valid - AssertionError: assert 936...\nE         1 failed, 16 passed in 0.03s\nE         \nE       assert 1 == 0\nE        +  where 1 = CompletedProcess(args=['/usr/bin/python', '-m', 'pytest', '-q', 'test_durations.py'], returncode=1, stdout='....F........ test_durations.py::test_rule3_order_valid - AssertionError: assert 936...\\n1 failed, 16 passed in 0.03s\\n', stderr='').returncode\n\n.bench_check/test_hidden.py:87: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n1 failed, 48 passed in 0.27s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `python -m pytest -q test_durations.py`: IndexError: no such group\nFAILED test_durations.py::test_rule6_decimals_invalid - IndexError: no such g...\nFAILED test_durations.py::test_rule8_zero_valid - IndexError: no such group\nFAILED test_durations.py::test_rule8_errors_invalid - AssertionError: Regex p...\n9 failed, 8 passed in 0.08s\n\nstderr:; `cd /tmp/nisse-bench/30f587e1da734aa8bc880bc887d1fdf9 && python - <<'EOF'\nimport re\np = 'durations.py'\ns = open(p).read()`: 3600 ", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 31297, "tokens_out": 18856, "trimmed_requests": 0, "ts": "2026-10-24T00:14:50+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 425.1}
+{"backing": "openai/qwen3.8-27b", "check_output": "..........                                                               [100%]\n10 passed in 0.03s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 24569, "tokens_out": 5681, "trimmed_requests": 0, "ts": "2026-10-24T00:16:58+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 128.0}
+{"backing": "openai/qwen3.8-27b", "check_output": "..........                                                               [100%]\n10 passed in 0.03s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `git status --short && git diff`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `pwd && ls -la && git -C /tmp/nisse-bench/28292b6addd54c719fd768b670f42ea1 rev-parse --show-toplevel 2>&1`:  root 4096 Oct 24 00:17 .\ndrwxr-xr-x 3 root root 4096 Oct 24 00:16 ..\ndrwxr-xr-x 3 root root 4096 Oct 24 00:17 .pytest_cache\ndrwxr-xr-x 3 root root 4096 Oct 24 00:17 invoicing\ndrwxr-xr-x 3 root root 4096 Oct 24 00:17 tests\nfatal", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 97180, "tokens_out": 10964, "trimmed_requests": 0, "ts": "2026-10-24T00:21:09+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 15, "wall_s": 250.5}
+{"backing": "openai/qwen3.8-27b", "check_output": "..........                                                               [100%]\n10 passed in 0.03s\n", "commit": "3caf4aa", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-27b", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "qwen3.8-27b thinking, llama.cpp b11783 Q4_K_XL", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 55827, "tokens_out": 4580, "trimmed_requests": 0, "ts": "2026-10-24T00:22:54+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 105.2}
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bench/results/2026-10-24-qwen3.8-flash-next-lowthink.jsonl

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+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 34000, "tokens_out": 3132, "trimmed_requests": 0, "ts": "2026-10-24T02:26:17+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 77.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 30938, "tokens_out": 1734, "trimmed_requests": 0, "ts": "2026-10-24T02:27:03+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 45.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/7af3cccffe124de58a5cf2a7cebdc66b/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/7af3cccffe124de58a5cf2a7cebdc66b/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 38560, "tokens_out": 2455, "trimmed_requests": 0, "ts": "2026-10-24T02:28:01+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 57.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.60s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 112397, "tokens_out": 7477, "trimmed_requests": 0, "ts": "2026-10-24T02:30:31+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 19, "wall_s": 149.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.61s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 5, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/b73f9bf948a642c1accf7d73ac0e6bd8 && rm -f /tmp/tracker-check.json && TRACKER_FILE=/tmp/tracker-check`: exit code: 2\nstdout:\nadded 1\n[!] 1 Pay rent (due 2026-10-01)\nexit=2\nls: cannot access '/tmp/tracker-check.json': No such file or directory\n\nstderr:\nusage: tracker [-h] [--file FILE] {add,list,done} ...\ntracker: error: invalid --due date: nope; `cd /tmp/nisse-bench/b73f9bf948a642c1accf7d73ac0e6bd8 && git status --short && git branch -a && git log ", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 85188, "tokens_out": 5374, "trimmed_requests": 0, "ts": "2026-10-24T02:32:22+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 109.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "])\nE                 assert capsys.readouterr().out == \"[!] 1 Pay rent (due 2026-10-01)\\n\"\nE                 main([\"--file\", path, \"done\", \"1\"])\nE                 capsys.readouterr()\nE                 main([\"--file\", path, \"list\", \"--overdue\"])\nE                 assert capsys.readouterr().out == \"\"\nE                 main([\"--file\", path, \"list\"])\nE         >       assert capsys.readouterr().out.splitlines() == [\nE                     \"[ ] 3 No date\",\nE                     \"[ ] 2 Call Bob (due 2026-10-09)\",\nE                     \"[x] 1 Pay rent (due 2026-10-01)\",\nE                 ]\nE         E       AssertionError: assert ['[ ] 2 Call ... 2026-10-01)'] == ['[ ] 3 No da... 2026-10-01)']\nE         E         At index 0 diff: '[ ] 2 Call Bob (due 2026-10-09)' != '[ ] 3 No date'\nE         E         Full diff:\nE         E           [\nE         E         +  '[ ] 2 Call Bob (due 2026-10-09)',\nE         E            '[ ] 3 No date',\nE         E         -  '[ ] 2 Call Bob (due 2026-10-09)',\nE         E            '[x] 1 Pay rent (due 2026-10-01)',...\nE         E         \nE         E         ...Full output truncated (2 lines hidden), use '-vv' to show\nE         \nE         tests/test_due_dates.py:157: AssertionError\nE         =========================== short test summary info ============================\nE         FAILED tests/test_due_dates.py::test_cli_list_overdue_only - AssertionError: ...\nE         1 failed, 22 passed in 0.08s\nE         \nE       assert 1 == 0\nE        +  where 1 = CompletedProcess(args=['/usr/bin/python', '-m', 'pytest', '-q', 'tests'], returncode=1, stdout='................F........ tests/test_due_dates.py::test_cli_list_overdue_only - AssertionError: ...\\n1 failed, 22 passed in 0.08s\\n', stderr='').returncode\n\n.bench_check/test_hidden.py:183: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_projects_own_tests_pass_and_cover_due_dates\n1 failed, 19 passed in 0.63s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/49f7075f9a2c44c1aeb777c73694939d && grep -rn \"python\" --include=\"*\" -l . | head; ls -a; which python`: exit code: 128\nstdout:\n./tracker/cli.py\n./tracker/__pycache__/cli.cpython-310.pyc\n.\n..\n.pytest_cache\ntests\ntracker\n\nstderr:; `cd /tmp/nisse-bench/49f7075f9a2c44c1aeb777c73694939d && python -m pytest -q`: ll output truncated (2 lines hidden), use '-vv' to show\n\ntests/test_due_dates.py:157: AssertionError\n=========================== short test summ", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 93671, "tokens_out": 9019, "trimmed_requests": 0, "ts": "2026-10-24T02:35:19+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 17, "wall_s": 176.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/9fd039c1d5d043638cfd10d69f67c245/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/9fd039c1d5d043638cfd10d69f67c245/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 4, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/9fd039c1d5d043638cfd10d69f67c245 && ls -a .git/HEAD && python -m pytest -q 2>&1 | tail -1 && git sta`: exit code: 2\nstdout:\n\nstderr:\nls: cannot access '.git/HEAD': No such file or directory; `cd /tmp/nisse-bench/9fd039c1d5d043638cfd10d69f67c245 && ls -a; echo \"---\"; git rev-parse --git-dir; echo \"---\"; git bran`: exit code: 128\nstdout:\n.\n..\n.pytest_cache\ntests\ntracker\n---\n---\n\nstderr:\nfatal: not a git repository (or any of the parent directories):", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 22695, "tokens_out": 1854, "trimmed_requests": 0, "ts": "2026-10-24T02:36:03+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 43.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 45033, "tokens_out": 1735, "trimmed_requests": 0, "ts": "2026-10-24T02:36:51+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 47.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `git status --short && git diff --stat`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `ls -a /tmp/nisse-bench/fb8e6f0ca53e43fa89bb0f433a8731d5 && git -C /tmp/nisse-bench/fb8e6f0ca53e43fa89bb0f433a8731d5 stat`: exit code: 128\nstdout:\n.\n..\n.pytest_cache\n__pycache__\nrates.py\ntest_rates.py\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 15029, "tokens_out": 492, "trimmed_requests": 0, "ts": "2026-10-24T02:37:07+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 5, "wall_s": 15.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `git status --short && git diff`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `pwd && ls -a && git rev-parse --show-toplevel 2>&1`: exit code: 128\nstdout:\n/tmp/nisse-bench/9db9bb5565b44153abe3730427595d64\n.\n..\n.pytest_cache\n__pycache__\nrates.py\ntest_rates.py\nfatal: not a git repository (or any of the parent directories): .git\n\nstderr:", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 12589, "tokens_out": 450, "trimmed_requests": 0, "ts": "2026-10-24T02:37:22+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 5, "wall_s": 14.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 18380, "tokens_out": 1124, "trimmed_requests": 0, "ts": "2026-10-24T02:37:51+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 28.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 165881, "tokens_out": 7206, "trimmed_requests": 0, "ts": "2026-10-24T02:40:47+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 33, "wall_s": 175.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 89210, "tokens_out": 3484, "trimmed_requests": 0, "ts": "2026-10-24T02:42:17+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 23, "wall_s": 89.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 33160, "tokens_out": 1758, "trimmed_requests": 0, "ts": "2026-10-24T02:43:03+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 45.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 108756, "tokens_out": 4908, "trimmed_requests": 0, "ts": "2026-10-24T02:45:07+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 27, "wall_s": 123.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 42691, "tokens_out": 2236, "trimmed_requests": 0, "ts": "2026-10-24T02:46:05+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 57.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 123603, "tokens_out": 4709, "trimmed_requests": 0, "ts": "2026-10-24T02:48:06+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 28, "wall_s": 120.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 84443, "tokens_out": 3178, "trimmed_requests": 0, "ts": "2026-10-24T02:49:26+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 17, "wall_s": 79.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 121790, "tokens_out": 4551, "trimmed_requests": 0, "ts": "2026-10-24T02:51:15+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 21, "wall_s": 108.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 50512, "tokens_out": 2022, "trimmed_requests": 0, "ts": "2026-10-24T02:52:09+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 53.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 75529, "tokens_out": 3110, "trimmed_requests": 0, "ts": "2026-10-24T02:53:33+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 16, "wall_s": 83.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "heck/test_hidden.py:32: ImportError\n________ test_the_new_name_appears_in_every_file_that_used_the_old_one _________\n\n    def test_the_new_name_appears_in_every_file_that_used_the_old_one() -> None:\n        for name in [\n            \"catalog\",\n            \"pricing\",\n            \"inventory\",\n            \"notifications\",\n            \"orders\",\n            \"reports\",\n            \"storage\",\n            \"cli\",\n        ]:\n            source = (ROOT / \"shopkeeper\" / f\"{name}.py\").read_text()\n>           assert \"read_settings\" in source, f\"shopkeeper/{name}.py\"\nE           AssertionError: shopkeeper/catalog.py\nE           assert 'read_settings' in '\"\"\"The product catalogue: SKU, name and unit price, from a CSV file.\"\"\"\\n\\nimport csv\\nfrom dataclasses import datacl...Product(row[\"sku\"], row[\"name\"], float(row[\"unit_price\"]))\\n            for row in csv.DictReader(handle)\\n        }\\n'\n\n.bench_check/test_hidden.py:63: AssertionError\n_________________________ test_behaviour_is_unchanged __________________________\n\ntmp_path = PosixPath('/tmp/pytest-of-root/pytest-158/test_behaviour_is_unchanged0')\nmonkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x7f1fa00ef280>\n\n    def test_behaviour_is_unchanged(\n        tmp_path: Path, monkeypatch: pytest.MonkeyPatch\n    ) -> None:\n>       from shopkeeper.config import read_settings, reload_config\nE       ImportError: cannot import name 'read_settings' from 'shopkeeper.config' (/tmp/nisse-bench/22119fdf2a7a49bcb617d87b1fd96a42/shopkeeper/config.py)\n\n.bench_check/test_hidden.py:70: ImportError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_old_name_is_gone_everywhere - As...\nFAILED .bench_check/test_hidden.py::test_the_new_name_is_exported - ImportErr...\nFAILED .bench_check/test_hidden.py::test_the_new_name_appears_in_every_file_that_used_the_old_one\nFAILED .bench_check/test_hidden.py::test_behaviour_is_unchanged - ImportError...\n4 failed, 3 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/22119fdf2a7a49bcb617d87b1fd96a42 && git status --short && git log --oneline -3 && ls docs 2>/dev/nul`: exit code: 2\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/22119fdf2a7a49bcb617d87b1fd96a42 && ls -a && git rev-parse --show-toplevel`: exit code: 128\nstdout:\n.\n..\nREADME.md\nshopkeeper\ntests\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 13417, "tokens_out": 833, "trimmed_requests": 0, "ts": "2026-10-24T02:53:55+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 4, "wall_s": 21.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.28s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 55035, "tokens_out": 25069, "trimmed_requests": 0, "ts": "2026-10-24T03:01:43+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 467.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 56267, "tokens_out": 18472, "trimmed_requests": 0, "ts": "2026-10-24T03:07:35+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 13, "wall_s": 350.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.23s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 57281, "tokens_out": 13531, "trimmed_requests": 0, "ts": "2026-10-24T03:12:03+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 267.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 543577, "tokens_out": 44970, "trimmed_requests": 0, "ts": "2026-10-24T03:26:45+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 881.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.23s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 69826, "tokens_out": 18630, "trimmed_requests": 0, "ts": "2026-10-24T03:32:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 13, "wall_s": 366.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 334798, "tokens_out": 13181, "trimmed_requests": 0, "ts": "2026-10-24T03:38:10+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 316.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 406830, "tokens_out": 42956, "trimmed_requests": 0, "ts": "2026-10-24T03:53:04+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 893.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/d0e7e52ef3d04cfa88dba30d78f557ee && grep -rn \"normalise_rate\\|RATE_PLACES\\|apply_rate\\|to_cents\" --i`: n rate.quantize(RATE_PLACES, rounding=ROUND_HALF_UP)\n./invoicing/money.py:26:def apply_rate(amount: Decimal, rate: Decimal) -> Decimal:\n./invoicing/money.py:28:    return to_cents(amount * normalise_rate(rate))\n=== git ===\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/d0e7e52ef3d04cfa88dba30d7", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 22969, "tokens_out": 3203, "trimmed_requests": 0, "ts": "2026-10-24T03:54:13+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 68.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 62046, "tokens_out": 7992, "trimmed_requests": 0, "ts": "2026-10-24T03:56:57+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 13, "wall_s": 163.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 153408, "tokens_out": 14685, "trimmed_requests": 0, "ts": "2026-10-24T04:02:09+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 23, "wall_s": 312.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 17690, "tokens_out": 944, "trimmed_requests": 0, "ts": "2026-10-24T04:02:36+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 26.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 29949, "tokens_out": 1355, "trimmed_requests": 0, "ts": "2026-10-24T04:03:14+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 37.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 15353, "tokens_out": 1012, "trimmed_requests": 0, "ts": "2026-10-24T04:03:41+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 26.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 53334, "tokens_out": 4332, "trimmed_requests": 0, "ts": "2026-10-24T04:05:17+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 16, "wall_s": 96.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 29023, "tokens_out": 1887, "trimmed_requests": 0, "ts": "2026-10-24T04:06:06+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 48.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "c647046f0fb3e306", "tokens_in": 18346, "tokens_out": 868, "trimmed_requests": 0, "ts": "2026-10-24T06:50:20+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 25.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "c647046f0fb3e306", "tokens_in": 20745, "tokens_out": 1178, "trimmed_requests": 0, "ts": "2026-10-24T06:50:50+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 30.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "c647046f0fb3e306", "tokens_in": 10574, "tokens_out": 507, "trimmed_requests": 0, "ts": "2026-10-24T06:51:06+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 4, "wall_s": 15.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "c647046f0fb3e306", "tokens_in": 20728, "tokens_out": 1149, "trimmed_requests": 0, "ts": "2026-10-24T06:51:35+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 29.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "c647046f0fb3e306", "tokens_in": 10583, "tokens_out": 564, "trimmed_requests": 0, "ts": "2026-10-24T06:51:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 4, "wall_s": 17.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.61s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "6441a4a5e212d384", "tokens_in": 164399, "tokens_out": 11847, "trimmed_requests": 0, "ts": "2026-10-24T06:55:57+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 24, "wall_s": 243.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "...................F                                                     [100%]\n=================================== FAILURES ===================================\n_____________ test_the_projects_own_tests_pass_and_cover_due_dates _____________\n\n    def test_the_projects_own_tests_pass_and_cover_due_dates() -> None:\n        result = subprocess.run(\n            [sys.executable, \"-m\", \"pytest\", \"-q\", \"tests\"],\n            capture_output=True,\n            text=True,\n            check=False,\n            cwd=Path.cwd(),\n        )\n        assert result.returncode == 0, result.stdout[-1500:]\n        written = \"\\n\".join(p.read_text() for p in Path(\"tests\").glob(\"test_*.py\"))\n        for name in (\"due\", \"overdue\", \"version\"):\n>           assert name in written, f\"no test mentions {name!r}\"\nE           AssertionError: no test mentions 'version'\nE           assert 'version' in 'from datetime import date\\n\\nfrom tracker.core import add_task, complete, overdue, sort_tasks\\nfrom tracker.models im..., 1]\\n\\n\\ndef test_completing_an_unknown_task() -> None:\\n    with pytest.raises(KeyError):\\n        complete([], 7)\\n'\n\n.bench_check/test_hidden.py:186: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_projects_own_tests_pass_and_cover_due_dates\n1 failed, 19 passed in 0.58s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "6441a4a5e212d384", "tokens_in": 270056, "tokens_out": 45972, "trimmed_requests": 0, "ts": "2026-10-24T07:10:38+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 879.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.62s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "6441a4a5e212d384", "tokens_in": 162620, "tokens_out": 9667, "trimmed_requests": 0, "ts": "2026-10-24T07:14:05+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 22, "wall_s": 206.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.59s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "6441a4a5e212d384", "tokens_in": 198689, "tokens_out": 13747, "trimmed_requests": 0, "ts": "2026-10-24T07:18:54+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 33, "wall_s": 288.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.58s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "6441a4a5e212d384", "tokens_in": 53806, "tokens_out": 5176, "trimmed_requests": 0, "ts": "2026-10-24T07:20:40+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 104.7}
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+{"backing": "openai/qwen3.8-flash-next", "check_output": "heck/test_hidden.py:32: ImportError\n________ test_the_new_name_appears_in_every_file_that_used_the_old_one _________\n\n    def test_the_new_name_appears_in_every_file_that_used_the_old_one() -> None:\n        for name in [\n            \"catalog\",\n            \"pricing\",\n            \"inventory\",\n            \"notifications\",\n            \"orders\",\n            \"reports\",\n            \"storage\",\n            \"cli\",\n        ]:\n            source = (ROOT / \"shopkeeper\" / f\"{name}.py\").read_text()\n>           assert \"read_settings\" in source, f\"shopkeeper/{name}.py\"\nE           AssertionError: shopkeeper/catalog.py\nE           assert 'read_settings' in '\"\"\"The product catalogue: SKU, name and unit price, from a CSV file.\"\"\"\\n\\nimport csv\\nfrom dataclasses import datacl...Product(row[\"sku\"], row[\"name\"], float(row[\"unit_price\"]))\\n            for row in csv.DictReader(handle)\\n        }\\n'\n\n.bench_check/test_hidden.py:63: AssertionError\n_________________________ test_behaviour_is_unchanged __________________________\n\ntmp_path = PosixPath('/tmp/pytest-of-root/pytest-325/test_behaviour_is_unchanged0')\nmonkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x7fdfd978b250>\n\n    def test_behaviour_is_unchanged(\n        tmp_path: Path, monkeypatch: pytest.MonkeyPatch\n    ) -> None:\n>       from shopkeeper.config import read_settings, reload_config\nE       ImportError: cannot import name 'read_settings' from 'shopkeeper.config' (/tmp/nisse-bench/fea88401f21744469f143da113e4d7de/shopkeeper/config.py)\n\n.bench_check/test_hidden.py:70: ImportError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_old_name_is_gone_everywhere - As...\nFAILED .bench_check/test_hidden.py::test_the_new_name_is_exported - ImportErr...\nFAILED .bench_check/test_hidden.py::test_the_new_name_appears_in_every_file_that_used_the_old_one\nFAILED .bench_check/test_hidden.py::test_behaviour_is_unchanged - ImportError...\n4 failed, 3 passed in 0.26s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "refactor-rename", "task_hash": "0e3ae69d6d1a1f83", "tokens_in": 304537, "tokens_out": 6879, "trimmed_requests": 0, "ts": "2026-10-24T07:38:24+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 170.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "................................................F                        [100%]\n=================================== FAILURES ===================================\n_________________ test_the_plan_asked_for_tests_and_they_pass __________________\n\n    def test_the_plan_asked_for_tests_and_they_pass() -> None:\n        # At least one valid and one invalid input for each of the eight rules.\n        import subprocess\n        import sys\n    \n        run = subprocess.run(\n            [sys.executable, \"-m\", \"pytest\", \"-q\", \"test_durations.py\"],\n            capture_output=True,\n            text=True,\n            check=False,\n        )\n        assert run.returncode == 0, run.stdout[-1500:]\n        summary = run.stdout.strip().splitlines()[-1]\n>       assert int(summary.split()[0]) >= 16, summary\nE       AssertionError: 10 passed in 0.01s\nE       assert 10 >= 16\nE        +  where 10 = int('10')\n\n.bench_check/test_hidden.py:89: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n1 failed, 48 passed in 0.22s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 153003, "tokens_out": 35213, "trimmed_requests": 0, "ts": "2026-10-24T07:49:17+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 22, "wall_s": 653.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 7263, "tokens_out": 162, "trimmed_requests": 0, "ts": "2026-10-24T07:49:25+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 3, "wall_s": 7.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.29s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 89921, "tokens_out": 19947, "trimmed_requests": 0, "ts": "2026-10-24T07:55:39+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 15, "wall_s": 373.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.28s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `python -m pytest -q 2>&1 | tail -5; cat .gitignore 2>/dev/null`: exit code: 1\nstdout:\n\nno tests ran in 0.00s\n\nstderr:; `python -m pytest -q -W ignore 2>&1 | tail -5; ls .github 2>/dev/null`: exit code: 2\nstdout:\n\nno tests ran in 0.00s\n\nstderr:", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 14794, "tokens_out": 13563, "trimmed_requests": 0, "ts": "2026-10-24T07:59:47+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 5, "wall_s": 247.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.28s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 29169, "tokens_out": 22916, "trimmed_requests": 0, "ts": "2026-10-24T08:06:49+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 421.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 349083, "tokens_out": 17968, "trimmed_requests": 0, "ts": "2026-10-24T08:13:27+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 397.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 65153, "tokens_out": 10044, "trimmed_requests": 0, "ts": "2026-10-24T08:16:57+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 13, "wall_s": 209.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 130585, "tokens_out": 11457, "trimmed_requests": 0, "ts": "2026-10-24T08:20:56+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 21, "wall_s": 239.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 365485, "tokens_out": 25984, "trimmed_requests": 0, "ts": "2026-10-24T08:30:10+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 553.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 247445, "tokens_out": 16980, "trimmed_requests": 0, "ts": "2026-10-24T08:36:07+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 32, "wall_s": 356.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 31160, "tokens_out": 1623, "trimmed_requests": 0, "ts": "2026-10-24T08:36:50+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 42.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 14267, "tokens_out": 755, "trimmed_requests": 0, "ts": "2026-10-24T08:37:12+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 21.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 21617, "tokens_out": 1278, "trimmed_requests": 0, "ts": "2026-10-24T08:37:46+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 33.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 24614, "tokens_out": 1408, "trimmed_requests": 0, "ts": "2026-10-24T08:38:22+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 36.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/1a6de7d768d24f4eb66de94853d47581/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "7a57cef+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-lowthink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next lowthink, git ws", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 14404, "tokens_out": 639, "trimmed_requests": 0, "ts": "2026-10-24T08:38:41+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 18.2}

bench/results/2026-10-24-qwen3.8-flash-next-nothink.jsonl

@@ -0,0 +1,40 @@
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7fd358eeeef0>(37.5)\nE        +    where <function approx at 0x7fd358eeeef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7fd358eeeef0>(0.0)\nE        +    where <function approx at 0x7fd358eeeef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 24529, "tokens_out": 688, "trimmed_requests": 0, "ts": "2026-10-24T04:06:50+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 19.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 42270, "tokens_out": 1058, "trimmed_requests": 0, "ts": "2026-10-24T04:07:18+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 27.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7f278f16aef0>(37.5)\nE        +    where <function approx at 0x7f278f16aef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7f278f16aef0>(0.0)\nE        +    where <function approx at 0x7f278f16aef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/3db6f755ae70433fb4a75c70f8677928 && sed -n '1,60p' ARCHITECTURE.md docs/plans/* 2>/dev/null; ls docs`: exit code: 2\nstdout:\n\nstderr:; `cd /tmp/nisse-bench/3db6f755ae70433fb4a75c70f8677928 && git log --oneline -5 && git status --short`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 10241, "tokens_out": 305, "trimmed_requests": 0, "ts": "2026-10-24T04:07:28+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 4, "wall_s": 9.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 39623, "tokens_out": 929, "trimmed_requests": 0, "ts": "2026-10-24T04:07:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 24.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7f8e0030eef0>(37.5)\nE        +    where <function approx at 0x7f8e0030eef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7f8e0030eef0>(0.0)\nE        +    where <function approx at 0x7f8e0030eef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/4ed61c563a044016963ccf02c8916024 && git status --short && git log --oneline -n 3 && git branch --sho`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/4ed61c563a044016963ccf02c8916024 && ls -a . && git init 2>&1 | tail -2 && git add inventory.py test_`: ease tell me who you are.\n\nRun\n\n  git config --global user.email \"you@example.com\"\n  git config --global user.name \"Your N", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 10258, "tokens_out": 334, "trimmed_requests": 0, "ts": "2026-10-24T04:08:02+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 4, "wall_s": 9.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/1a05099dd8c14a71a577ce16b90fa7d1/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/1a05099dd8c14a71a577ce16b90fa7d1/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/1a05099dd8c14a71a577ce16b90fa7d1 && printf 'from datetime import date\\nfrom tracker.models import Ta`: exit code: 1\nstdout:\n\nstderr:\nTraceback (most recent call last):\n  File \"/tmp/chk.py\", line 2, in <module>\n    from tracker.models import Task\nModuleNotFoundError: No module named 'tracker'; `cd /tmp/nisse-bench/1a05099dd8c14a71a577ce16b90fa7d1 && python /tmp/chk.py`: exit code: 1\nstdout:\n\nstderr:\nTraceback (most recent call last):\n  File \"/tmp/c", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 66704, "tokens_out": 1154, "trimmed_requests": 0, "ts": "2026-10-24T04:08:30+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 27.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/1473514b219743528b84d11efde27d0c/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/1473514b219743528b84d11efde27d0c/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 315470, "tokens_out": 3494, "trimmed_requests": 0, "ts": "2026-10-24T04:09:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 82.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/15567af48e0749bd980cfc0590f7945c/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/15567af48e0749bd980cfc0590f7945c/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 51676, "tokens_out": 872, "trimmed_requests": 0, "ts": "2026-10-24T04:10:16+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 23.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/70b88661b9fd4fb89e0a1f2edd0fdc04/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/70b88661b9fd4fb89e0a1f2edd0fdc04/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 175680, "tokens_out": 2357, "trimmed_requests": 0, "ts": "2026-10-24T04:11:07+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 31, "wall_s": 51.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/2a6003da7d3741a19ddcb8ce76cec03c/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/2a6003da7d3741a19ddcb8ce76cec03c/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 45594, "tokens_out": 821, "trimmed_requests": 0, "ts": "2026-10-24T04:11:30+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 22.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 22218, "tokens_out": 605, "trimmed_requests": 0, "ts": "2026-10-24T04:11:49+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 18.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 31063, "tokens_out": 797, "trimmed_requests": 0, "ts": "2026-10-24T04:12:11+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 21.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/ba2c7e65ae464e4b91d54b4cdd0630cd && git diff --stat && git diff`: cified path\n    --find-object <object-id>\n                          look for differences that change the number of occurrences of the specified object\n    --diff-filter [(A|C|D|M|R|T|U|X|B)...[*]]\n                          select files by diff type\n    --output <file>       Output to a specific file; `cd /tmp/nisse-bench/ba2c7e65ae464e4b91d54b4cdd0630cd && git status --porcelain && ", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 15115, "tokens_out": 379, "trimmed_requests": 0, "ts": "2026-10-24T04:12:24+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 5, "wall_s": 12.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.28s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 18339, "tokens_out": 629, "trimmed_requests": 0, "ts": "2026-10-24T04:12:42+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 17.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 24454, "tokens_out": 642, "trimmed_requests": 0, "ts": "2026-10-24T04:13:01+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 18.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `grep -rn \"shout\" . --include=*.py | head; git log --oneline -n 5; git status --short`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git\nfatal: not a git repository (or any of the parent directories): .git; `pwd; ls -a; echo ---; cd /tmp/nisse-bench/dc4654bf539240efbb98805550c4a972 && pwd && ls -a && git status --short`: exit code: 128\nstdout:\n/tmp/nisse-bench/dc4654bf539240efbb98805550c4a972\n.\n..\n.pytest_cache\ngreet", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 24391, "tokens_out": 423, "trimmed_requests": 0, "ts": "2026-10-24T04:13:16+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 14.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.14s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/699bdeeed097409e8306e78435300731 && ls -R . | head -50 && cat ARCHITECTURE.md 2>/dev/null; git statu`: exit code: 128\nstdout:\n.:\ngreeter\ntests\n\n./greeter:\n__init__.py\n__main__.py\ncli.py\ncore.py\n\n./tests:\ntest_greeter.py\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/699bdeeed097409e8306e78435300731 && head -5 greeter/core.py greeter/cli.py greeter/__main__.py tests`: core import greet\n\n\n\n==> gre", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 4429, "tokens_out": 172, "trimmed_requests": 0, "ts": "2026-10-24T04:13:21+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 2, "wall_s": 5.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 15994, "tokens_out": 511, "trimmed_requests": 0, "ts": "2026-10-24T04:13:35+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 6, "wall_s": 13.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 4, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 219923, "tokens_out": 3084, "trimmed_requests": 0, "ts": "2026-10-24T04:14:41+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 65.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/8b9ad9449cf14a8ba1851341e116e30f && git log --oneline 2>&1 | head -3; echo \"---\"; git rev-parse HEAD`: exit code: 128\nstdout:\nfatal: your current branch 'master' does not have any commits yet\n---\nfatal: ambiguous argument 'HEAD': unknown revision or path not in the working tree.\nUse '--' to separate paths from revisions, like this:\n'git <command> [<revision>...] -- [<file>...]'\nHEAD\n\nstderr:; `cd /tmp/nisse-bench/8b9ad9449cf14a8ba1851341e116e30f &", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 12724, "tokens_out": 434, "trimmed_requests": 0, "ts": "2026-10-24T04:14:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 5, "wall_s": 11.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 206511, "tokens_out": 2722, "trimmed_requests": 0, "ts": "2026-10-24T04:15:58+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 26, "wall_s": 65.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 55372, "tokens_out": 1259, "trimmed_requests": 0, "ts": "2026-10-24T04:16:32+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 33.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "heck/test_hidden.py:32: ImportError\n________ test_the_new_name_appears_in_every_file_that_used_the_old_one _________\n\n    def test_the_new_name_appears_in_every_file_that_used_the_old_one() -> None:\n        for name in [\n            \"catalog\",\n            \"pricing\",\n            \"inventory\",\n            \"notifications\",\n            \"orders\",\n            \"reports\",\n            \"storage\",\n            \"cli\",\n        ]:\n            source = (ROOT / \"shopkeeper\" / f\"{name}.py\").read_text()\n>           assert \"read_settings\" in source, f\"shopkeeper/{name}.py\"\nE           AssertionError: shopkeeper/catalog.py\nE           assert 'read_settings' in '\"\"\"The product catalogue: SKU, name and unit price, from a CSV file.\"\"\"\\n\\nimport csv\\nfrom dataclasses import datacl...Product(row[\"sku\"], row[\"name\"], float(row[\"unit_price\"]))\\n            for row in csv.DictReader(handle)\\n        }\\n'\n\n.bench_check/test_hidden.py:63: AssertionError\n_________________________ test_behaviour_is_unchanged __________________________\n\ntmp_path = PosixPath('/tmp/pytest-of-root/pytest-196/test_behaviour_is_unchanged0')\nmonkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x7f09cba5f280>\n\n    def test_behaviour_is_unchanged(\n        tmp_path: Path, monkeypatch: pytest.MonkeyPatch\n    ) -> None:\n>       from shopkeeper.config import read_settings, reload_config\nE       ImportError: cannot import name 'read_settings' from 'shopkeeper.config' (/tmp/nisse-bench/416a8af09e4645e5ad7bf58d9b64d25b/shopkeeper/config.py)\n\n.bench_check/test_hidden.py:70: ImportError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_old_name_is_gone_everywhere - As...\nFAILED .bench_check/test_hidden.py::test_the_new_name_is_exported - ImportErr...\nFAILED .bench_check/test_hidden.py::test_the_new_name_appears_in_every_file_that_used_the_old_one\nFAILED .bench_check/test_hidden.py::test_behaviour_is_unchanged - ImportError...\n4 failed, 3 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/416a8af09e4645e5ad7bf58d9b64d25b && ls -la docs 2>/dev/null; ls shopkeeper tests; cat README.md; cat`:  uses `SHOPKEEPER_CONFIG`, or the built-in\ndefaults from `load_config_defaults()` when that is unset. After editing the\nfile, `reload_config(settings)` reads it again.\n\n## Command line\n\n    python -m shopkeeper --config shop.ini price SKU-1 3\n    python -m shopkeeper --config shop.ini stock\n\nstderr:; `cd /tmp/nisse-bench/416a8af09e4645e5ad7bf58d9", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 8765, "tokens_out": 255, "trimmed_requests": 0, "ts": "2026-10-24T04:16:41+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 3, "wall_s": 8.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.23s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/fa9c6d68d1094f268db86e3cacb90e5b && git status --short && git diff --stat`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/fa9c6d68d1094f268db86e3cacb90e5b && git status --short`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 37212, "tokens_out": 717, "trimmed_requests": 0, "ts": "2026-10-24T04:16:59+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 18.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 32447, "tokens_out": 643, "trimmed_requests": 0, "ts": "2026-10-24T04:17:19+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 19.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 219174, "tokens_out": 3853, "trimmed_requests": 0, "ts": "2026-10-24T04:18:37+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 77.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 272990, "tokens_out": 3094, "trimmed_requests": 0, "ts": "2026-10-24T04:19:54+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 76.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 322430, "tokens_out": 3421, "trimmed_requests": 0, "ts": "2026-10-24T04:21:14+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 80.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 221015, "tokens_out": 3100, "trimmed_requests": 0, "ts": "2026-10-24T04:22:28+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 73.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.28s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 210938, "tokens_out": 2687, "trimmed_requests": 0, "ts": "2026-10-24T04:23:29+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 60.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 399001, "tokens_out": 6794, "trimmed_requests": 0, "ts": "2026-10-24T04:25:34+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 125.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/2e305ba0540042759a3a2ab807dff94c && python -m pytest -q 2>&1 | tail -5 && git status --short`: st_invoice.py:33: AssertionError\n=========================== short test summary info ============================\nFAILED tests/test_invoice.py::test_multi_currency_total - AssertionError: ass...\n1 failed, 3 passed in 0.02s\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/2e305ba0540042759a3a2ab807dff94c ", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 44075, "tokens_out": 921, "trimmed_requests": 0, "ts": "2026-10-24T04:25:59+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 24.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 4, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 324880, "tokens_out": 5127, "trimmed_requests": 0, "ts": "2026-10-24T04:27:42+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 102.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 73408, "tokens_out": 1832, "trimmed_requests": 0, "ts": "2026-10-24T04:28:27+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 45.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 466326, "tokens_out": 9794, "trimmed_requests": 0, "ts": "2026-10-24T04:33:12+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 284.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/ad15e7dba504451186f51ab0705633f9/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cat README.md && git status --short --branch`: exit code: 128\nstdout:\nA small utilities project.\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `ls -a; echo \"---\"; ls -a ..; echo \"---\"; git rev-parse --show-toplevel 2>&1`: exit code: 128\nstdout:\n.\n..\nREADME.md\n---\n.\n..\nad15e7dba504451186f51ab0705633f9\nbackup\nfix_rates.patch\n---\nfatal: not a git repository (or any of the parent directories): .git\n\nstderr:", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 6658, "tokens_out": 113, "trimmed_requests": 0, "ts": "2026-10-24T04:33:20+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 3, "wall_s": 7.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/fcd64bf8fb4340019e645922fd69476c/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 4, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 60782, "tokens_out": 866, "trimmed_requests": 0, "ts": "2026-10-24T04:33:49+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 28.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/179076dc718b43239298fc2aa827c8c9/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 6666, "tokens_out": 148, "trimmed_requests": 0, "ts": "2026-10-24T04:33:55+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 3, "wall_s": 5.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/f052989ea901437da39741a01ac29ef2/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 156892, "tokens_out": 1853, "trimmed_requests": 0, "ts": "2026-10-24T04:34:45+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 49.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/d9b1a9ac592047969fd209e70cf8ac9a/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next-nothink", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next nothink, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cat README.md && git log --oneline -n 5 && git branch -a`: exit code: 128\nstdout:\nA small utilities project.\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `ls -a && cat .git/config 2>/dev/null; echo \"---\"; env | grep -i git`: exit code: 1\nstdout:\n.\n..\nREADME.md\n---\n\nstderr:", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 6670, "tokens_out": 120, "trimmed_requests": 0, "ts": "2026-10-24T04:34:51+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 3, "wall_s": 6.1}

bench/results/2026-10-24-qwen3.8-flash-next.jsonl

@@ -0,0 +1,80 @@
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7ff058a5aef0>(37.5)\nE        +    where <function approx at 0x7ff058a5aef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7ff058a5aef0>(0.0)\nE        +    where <function approx at 0x7ff058a5aef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 38535, "tokens_out": 1702, "trimmed_requests": 0, "ts": "2026-10-24T00:32:01+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 45.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "......                                                                   [100%]\n6 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 28254, "tokens_out": 1634, "trimmed_requests": 0, "ts": "2026-10-24T00:32:42+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 41.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7f90c04a2ef0>(37.5)\nE        +    where <function approx at 0x7f90c04a2ef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7f90c04a2ef0>(0.0)\nE        +    where <function approx at 0x7f90c04a2ef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/674b6571b9ea411db7340cf98b9ae088 && ls -la && git log --oneline -5`: : 128\nstdout:\ntotal 16\ndrwxr-xr-x 2 root root 4096 Oct 24 00:32 .\ndrwxr-xr-x 3 root root 4096 Oct 24 00:32 ..\n-rw-r--r-- 1 root root  572 Sep 25 02:24 inventory.py\n-rw-r--r-- 1 root root  389 Sep 25 02:24 test_inventory.py\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cd /tmp/nisse-bench/674b6571b9ea411db7340cf98b9ae088 && cat inventory.py && ech", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 4321, "tokens_out": 200, "trimmed_requests": 0, "ts": "2026-10-24T00:32:49+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 2, "wall_s": 6.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7f3138bb2ef0>(37.5)\nE        +    where <function approx at 0x7f3138bb2ef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7f3138bb2ef0>(0.0)\nE        +    where <function approx at 0x7f3138bb2ef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/a2cb409693af49918a8bb363aa8bca02 && ls -la && python -m pytest -q`: , quantity=100), Item(name='nut', unit_price=0.1, quantity=40)])\n\ntest_inventory.py:6: AssertionError\n=========================== short test summary info ============================\nFAILED test_inventory.py::test_total_value_counts_every_unit - AssertionError...\n1 failed, 1 passed in 0.02s\n\nstderr:; `cd /tmp/nisse-bench/a2cb409693af49918a8bb363aa8bca02 && cat inventory.py && echo", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 4499, "tokens_out": 185, "trimmed_requests": 0, "ts": "2026-10-24T00:32:56+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 2, "wall_s": 6.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "cted = 37.5\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 12.5 == 37.5 \u00b1 3.7e-05\nE        +  where 12.5 = total_value([Item(name='gear', unit_price=12.5, quantity=3)])\nE        +  and   37.5 \u00b1 3.7e-05 = <function approx at 0x7f81d941aef0>(37.5)\nE        +    where <function approx at 0x7f81d941aef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n_________________________ test_total_value[items3-0.0] _________________________\n\nitems = [Item(name='empty', unit_price=9.99, quantity=0)], expected = 0.0\n\n    @pytest.mark.parametrize(\n        (\"items\", \"expected\"),\n        [\n            ([], 0.0),\n            ([Item(\"bolt\", 0.25, 100), Item(\"nut\", 0.10, 40)], 29.0),\n            ([Item(\"gear\", 12.5, 3)], 37.5),\n            ([Item(\"empty\", 9.99, 0)], 0.0),\n        ],\n    )\n    def test_total_value(items: list[Item], expected: float) -> None:\n>       assert total_value(items) == pytest.approx(expected)\nE       AssertionError: assert 9.99 == 0.0 \u00b1 1.0e-12\nE        +  where 9.99 = total_value([Item(name='empty', unit_price=9.99, quantity=0)])\nE        +  and   0.0 \u00b1 1.0e-12 = <function approx at 0x7f81d941aef0>(0.0)\nE        +    where <function approx at 0x7f81d941aef0> = pytest.approx\n\n.bench_check/test_hidden.py:22: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_total_value[items1-29.0] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items2-37.5] - Assertion...\nFAILED .bench_check/test_hidden.py::test_total_value[items3-0.0] - AssertionE...\n3 failed, 3 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "fix-bug", "task_hash": "9e9349d5ed6dae8d", "tokens_in": 20023, "tokens_out": 1419, "trimmed_requests": 0, "ts": "2026-10-24T00:33:31+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 34.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.66s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 297614, "tokens_out": 14462, "trimmed_requests": 0, "ts": "2026-10-24T00:38:43+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 34, "wall_s": 311.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/3b8af3bfb0454fee930ea90c52b01607/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/3b8af3bfb0454fee930ea90c52b01607/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.07s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `find . -path ./.git -prune -o -type f -print | head -50 && echo \"---\" && git log --oneline -5`: xit code: 128\nstdout:\n./tests/test_storage_and_cli.py\n./tests/test_core.py\n./tracker/cli.py\n./tracker/formatting.py\n./tracker/__init__.py\n./tracker/core.py\n./tracker/models.py\n./tracker/__main__.py\n./tracker/storage.py\n---\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git; `cat ARCHITECTURE.md 2>/dev/null; ls docs/plans 2>/dev/null`: exit code: ", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 2650, "tokens_out": 118, "trimmed_requests": 0, "ts": "2026-10-24T00:38:49+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 4.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.84s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 335447, "tokens_out": 29502, "trimmed_requests": 0, "ts": "2026-10-24T00:48:35+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 585.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "....................                                                     [100%]\n20 passed in 0.62s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 226775, "tokens_out": 17497, "trimmed_requests": 0, "ts": "2026-10-24T00:54:24+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 23, "wall_s": 348.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/d43c24d9027647b89ba74ebc218830f3/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:10: in <module>\n    from tracker.core import add_task, complete, overdue, sort_tasks\nE   ImportError: cannot import name 'overdue' from 'tracker.core' (/tmp/nisse-bench/d43c24d9027647b89ba74ebc218830f3/tracker/core.py)\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.06s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/d43c24d9027647b89ba74ebc218830f3 && ls -la && cat ARCHITECTURE.md 2>/dev/null; ls docs/plans 2>/dev/`: exit code: 2\nstdout:\ntotal 16\ndrwxr-xr-x 4 root root 4096 Oct 24 00:54 .\ndrwxr-xr-x 3 root root 4096 Oct 24 00:54 ..\ndrwxr-xr-x 2 root root 4096 Sep 29 14:17 tests\ndrwxr-xr-x 2 root root 4096 Sep 29 14:17 tracker\n\nstderr:; `cd /tmp/nisse-bench/d43c24d9027647b89ba74ebc218830f3 && git log --oneline -5 && git status --short`: exit code: 128\nstdout:\n", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-milestone", "task_hash": "106e68dd7bfe9dba", "tokens_in": 2652, "tokens_out": 194, "trimmed_requests": 0, "ts": "2026-10-24T00:54:30+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 5.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 69026, "tokens_out": 3589, "trimmed_requests": 0, "ts": "2026-10-24T00:55:59+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 88.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n......................F................................................. [ 95%]\n.............                                                            [100%]\n=================================== FAILURES ===================================\n________________________________ test_rate[237] ________________________________\n\nn = 237\n\n    @pytest.mark.parametrize(\"n\", range(300))\n    def test_rate(n: int) -> None:\n>       assert RATES[f\"R{n:03d}\"] == pytest.approx(n % 25 / 100)\nE       assert 0.21 == 0.12 \u00b1 1.2e-07\nE        +  where 0.12 \u00b1 1.2e-07 = <function approx at 0x7f77890baef0>(((237 % 25) / 100))\nE        +    where <function approx at 0x7f77890baef0> = pytest.approx\n\n.bench_check/test_hidden.py:11: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_rate[237] - assert 0.21 == 0.12 \u00b1 1....\n1 failed, 300 passed in 0.28s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `ls -la && cat ARCHITECTURE.md 2>/dev/null; ls docs/plans 2>/dev/null`: exit code: 2\nstdout:\ntotal 20\ndrwxr-xr-x 2 root root 4096 Oct 24 00:55 .\ndrwxr-xr-x 3 root root 4096 Oct 24 00:55 ..\n-rw-r--r-- 1 root root 5445 Sep 25 02:24 rates.py\n-rw-r--r-- 1 root root  208 Sep 25 02:24 test_rates.py\n\nstderr:; `git log --oneline -5 && git status --short`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 2064, "tokens_out": 142, "trimmed_requests": 0, "ts": "2026-10-24T00:56:04+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 4.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.27s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 38087, "tokens_out": 2309, "trimmed_requests": 0, "ts": "2026-10-24T00:57:03+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 58.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 79745, "tokens_out": 4267, "trimmed_requests": 0, "ts": "2026-10-24T00:58:47+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 19, "wall_s": 103.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "b90340b3dd8b39b4", "tokens_in": 274258, "tokens_out": 9448, "trimmed_requests": 0, "ts": "2026-10-24T01:02:37+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 36, "wall_s": 230.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `find . -type f -not -path \"./.git/*\" | head -50 && echo \"---\" && cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\n./greeter/cli.py\n./greeter/__init__.py\n./greeter/core.py\n./greeter/__main__.py\n./tests/test_greeter.py\n---\n\nstderr:; `git log --oneline -5 && git status`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 2158, "tokens_out": 108, "trimmed_requests": 0, "ts": "2026-10-24T01:02:42+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 4.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.03s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 3, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 62759, "tokens_out": 3656, "trimmed_requests": 0, "ts": "2026-10-24T01:04:12+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 16, "wall_s": 89.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `find . -not -path './.git/*' -not -name '.git' -type f | head -50 && echo '---' && cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\n./greeter/cli.py\n./greeter/__init__.py\n./greeter/core.py\n./greeter/__main__.py\n./tests/test_greeter.py\n---\n\nstderr:; `git log --oneline -5 && git status --short && git branch -a`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 2155, "tokens_out": 123, "trimmed_requests": 0, "ts": "2026-10-24T01:04:16+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 4.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 27973, "tokens_out": 1564, "trimmed_requests": 0, "ts": "2026-10-24T01:04:54+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 37.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `find . -type f -not -path './.git/*' | head -50 && echo '---' && cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\n./greeter/cli.py\n./greeter/__init__.py\n./greeter/core.py\n./greeter/__main__.py\n./tests/test_greeter.py\n---\n\nstderr:; `git log --oneline -5 && git status`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "870e2574d3aca955", "tokens_in": 2155, "tokens_out": 109, "trimmed_requests": 0, "ts": "2026-10-24T01:04:59+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 4.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 63624, "tokens_out": 3770, "trimmed_requests": 0, "ts": "2026-10-24T01:06:26+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 86.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 87204, "tokens_out": 3607, "trimmed_requests": 0, "ts": "2026-10-24T01:07:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 85.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "heck/test_hidden.py:32: ImportError\n________ test_the_new_name_appears_in_every_file_that_used_the_old_one _________\n\n    def test_the_new_name_appears_in_every_file_that_used_the_old_one() -> None:\n        for name in [\n            \"catalog\",\n            \"pricing\",\n            \"inventory\",\n            \"notifications\",\n            \"orders\",\n            \"reports\",\n            \"storage\",\n            \"cli\",\n        ]:\n            source = (ROOT / \"shopkeeper\" / f\"{name}.py\").read_text()\n>           assert \"read_settings\" in source, f\"shopkeeper/{name}.py\"\nE           AssertionError: shopkeeper/catalog.py\nE           assert 'read_settings' in '\"\"\"The product catalogue: SKU, name and unit price, from a CSV file.\"\"\"\\n\\nimport csv\\nfrom dataclasses import datacl...Product(row[\"sku\"], row[\"name\"], float(row[\"unit_price\"]))\\n            for row in csv.DictReader(handle)\\n        }\\n'\n\n.bench_check/test_hidden.py:63: AssertionError\n_________________________ test_behaviour_is_unchanged __________________________\n\ntmp_path = PosixPath('/tmp/pytest-of-root/pytest-103/test_behaviour_is_unchanged0')\nmonkeypatch = <_pytest.monkeypatch.MonkeyPatch object at 0x7f3ec63eb2b0>\n\n    def test_behaviour_is_unchanged(\n        tmp_path: Path, monkeypatch: pytest.MonkeyPatch\n    ) -> None:\n>       from shopkeeper.config import read_settings, reload_config\nE       ImportError: cannot import name 'read_settings' from 'shopkeeper.config' (/tmp/nisse-bench/dd46b8506f79458794053f14497a69af/shopkeeper/config.py)\n\n.bench_check/test_hidden.py:70: ImportError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_the_old_name_is_gone_everywhere - As...\nFAILED .bench_check/test_hidden.py::test_the_new_name_is_exported - ImportErr...\nFAILED .bench_check/test_hidden.py::test_the_new_name_appears_in_every_file_that_used_the_old_one\nFAILED .bench_check/test_hidden.py::test_behaviour_is_unchanged - ImportError...\n4 failed, 3 passed in 0.26s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `ls docs 2>/dev/null; ls *.cfg *.toml 2>/dev/null; cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\n\nstderr:; `cd /tmp/nisse-bench/dd46b8506f79458794053f14497a69af && git status --short && python -m pytest -q 2>&1 | tail -5`: exit code: 128\nstdout:\n\nstderr:\nfatal: not a git repository (or any of the parent directories): .git", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 25938, "tokens_out": 1145, "trimmed_requests": 0, "ts": "2026-10-24T01:08:25+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 32.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.23s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 38134, "tokens_out": 2129, "trimmed_requests": 0, "ts": "2026-10-24T01:09:16+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 50.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.25s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "aaa8fc0b5a74a012", "tokens_in": 100984, "tokens_out": 4189, "trimmed_requests": 0, "ts": "2026-10-24T01:10:58+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 101.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.32s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 65604, "tokens_out": 23945, "trimmed_requests": 0, "ts": "2026-10-24T01:18:26+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 447.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 26823, "tokens_out": 19981, "trimmed_requests": 0, "ts": "2026-10-24T01:24:45+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 378.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.28s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 365193, "tokens_out": 53607, "trimmed_requests": 0, "ts": "2026-10-24T01:41:30+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 33, "wall_s": 1003.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cat durations.py; ls docs/plans 2>/dev/null; cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\n\"\"\"Human-written durations. See SPEC.md.\"\"\"\n\n\ndef parse_duration(text: str) -> int:\n    \"\"\"A duration in whole seconds, as SPEC.md specifies.\"\"\"\n    raise NotImplementedError\n\nstderr:; `python -V && python -m pytest --version && git log --oneline -3 && git status --short`: exit code: 128\nstdout:\nPython 3.10.12\n\nstderr:\npytest 6.2.5\nfatal: not a git repository (or any o", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 5254, "tokens_out": 2102, "trimmed_requests": 0, "ts": "2026-10-24T01:42:14+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 2, "wall_s": 44.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.23s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "ab0053a41dbbcdf8", "tokens_in": 86956, "tokens_out": 20718, "trimmed_requests": 0, "ts": "2026-10-24T01:48:38+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 383.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 147005, "tokens_out": 20109, "trimmed_requests": 0, "ts": "2026-10-24T01:55:26+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 20, "wall_s": 407.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 89000, "tokens_out": 11377, "trimmed_requests": 0, "ts": "2026-10-24T01:59:22+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 235.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 186211, "tokens_out": 30867, "trimmed_requests": 0, "ts": "2026-10-24T02:10:18+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 24, "wall_s": 655.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "              LineItem(\"setup\", d(\"99.00\"), 1, \"GBP\"),\n            ],\n            discount=Discount(d(\"7.5\")),\n            tax_percent=d(\"17.5\"),\n        )\n        # 400 EUR = 344.31 GBP; subtotal 443.31; discount 33.25; tax 71.76.\n>       assert invoice.subtotal() == d(\"443.31\")\nE       AssertionError: assert Decimal('443.00') == Decimal('443.31')\nE        +  where Decimal('443.00') = <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))>()\nE        +    where <bound method Invoice.subtotal of Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40....ecimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5'))> = Invoice(currency='GBP', lines=[LineItem(description='seats', unit_price=Decimal('40.00'), quantity=10, currency='EUR')...Decimal('99.00'), quantity=1, currency='GBP')], discount=Discount(percent=Decimal('7.5')), tax_percent=Decimal('17.5')).subtotal\nE        +  and   Decimal('443.31') = d('443.31')\n\n.bench_check/test_hidden.py:73: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-USD-EUR-91.95] - A...\nFAILED .bench_check/test_hidden.py::test_conversion[100.00-EUR-USD-108.75] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[250.00-GBP-EUR-290.44] - ...\nFAILED .bench_check/test_hidden.py::test_conversion[10000-JPY-USD-67.12] - As...\nFAILED .bench_check/test_hidden.py::test_multi_currency_total - AssertionErro...\nFAILED .bench_check/test_hidden.py::test_fractional_discount - AssertionError...\nFAILED .bench_check/test_hidden.py::test_fractional_tax - AssertionError: ass...\nFAILED .bench_check/test_hidden.py::test_everything_together - AssertionError...\n8 failed, 2 passed in 0.05s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/487e585cd57c4d71bd5ea80c844a394a && ls -la && cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\ntotal 16\ndrwxr-xr-x 4 root root 4096 Oct 24 02:10 .\ndrwxr-xr-x 3 root root 4096 Oct 24 02:10 ..\ndrwxr-xr-x 2 root root 4096 Sep 29 14:17 invoicing\ndrwxr-xr-x 2 root root 4096 Sep 29 14:17 tests\n\nstderr:; `cd /tmp/nisse-bench/487e585cd57c4d71bd5ea80c844a394a && ls -la invoicing tests && git log --oneline -5`: 7 money.py\n-rw-r--r-- 1 root root  906 S", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 4675, "tokens_out": 183, "trimmed_requests": 0, "ts": "2026-10-24T02:10:25+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 2, "wall_s": 6.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "ae05a8edb160d159", "tokens_in": 70428, "tokens_out": 7438, "trimmed_requests": 0, "ts": "2026-10-24T02:13:13+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 167.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "\n==================================== ERRORS ====================================\n_________________ ERROR collecting .bench_check/test_hidden.py _________________\nImportError while importing test module '/tmp/nisse-bench/d0aa863794b5469b83da2cc6975d850f/.bench_check/test_hidden.py'.\nHint: make sure your test modules/packages have valid Python names.\nTraceback:\n/usr/lib/python3.10/importlib/__init__.py:126: in import_module\n    return _bootstrap._gcd_import(name[level:], package, level)\n.bench_check/test_hidden.py:2: in <module>\n    from slugify import slugify\nE   ModuleNotFoundError: No module named 'slugify'\n=========================== short test summary info ============================\nERROR .bench_check/test_hidden.py\n!!!!!!!!!!!!!!!!!!!! Interrupted: 1 error during collection !!!!!!!!!!!!!!!!!!!!\n1 error in 0.04s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 46772, "tokens_out": 2733, "trimmed_requests": 0, "ts": "2026-10-24T02:14:21+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 15, "wall_s": 68.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 45438, "tokens_out": 3259, "trimmed_requests": 0, "ts": "2026-10-24T02:15:42+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 80.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 27057, "tokens_out": 1430, "trimmed_requests": 0, "ts": "2026-10-24T02:16:22+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 40.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 191439, "tokens_out": 12403, "trimmed_requests": 0, "ts": "2026-10-24T02:21:03+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 37, "wall_s": 280.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "3caf4aa+dirty", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, 2026-10-23", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "c0e42f85934119cc", "tokens_in": 38908, "tokens_out": 2306, "trimmed_requests": 0, "ts": "2026-10-24T02:22:01+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 13, "wall_s": 57.9}
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+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.26s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "a7e928f67b93ac2a", "tokens_in": 27455, "tokens_out": 1444, "trimmed_requests": 0, "ts": "2026-10-24T05:20:52+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 37.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.27s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "a7e928f67b93ac2a", "tokens_in": 63663, "tokens_out": 2941, "trimmed_requests": 0, "ts": "2026-10-24T05:22:07+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 15, "wall_s": 74.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n........................................................................ [ 95%]\n.............                                                            [100%]\n301 passed in 0.25s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "long-output", "task_hash": "a7e928f67b93ac2a", "tokens_in": 58260, "tokens_out": 2451, "trimmed_requests": 0, "ts": "2026-10-24T05:23:09+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 60.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........................................................................ [ 23%]\n........................................................................ [ 47%]\n........................................................................ [ 71%]\n......................F................................................. [ 95%]\n.............                                                            [100%]\n=================================== FAILURES ===================================\n________________________________ test_rate[237] ________________________________\n\nn = 237\n\n    @pytest.mark.parametrize(\"n\", range(300))\n    def test_rate(n: int) -> None:\n>       assert RATES[f\"R{n:03d}\"] == pytest.approx(n % 25 / 100)\nE       assert 0.21 == 0.12 \u00b1 1.2e-07\nE        +  where 0.12 \u00b1 1.2e-07 = <function approx at 0x7f99acbc6ef0>(((237 % 25) / 100))\nE        +    where <function approx at 0x7f99acbc6ef0> = pytest.approx\n\n.bench_check/test_hidden.py:11: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_rate[237] - assert 0.21 == 0.12 \u00b1 1....\n1 failed, 300 passed in 0.29s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `ls -la && cat ARCHITECTURE.md 2>/dev/null`: exit code: 1\nstdout:\ntotal 24\ndrwxr-xr-x 3 root root 4096 Oct 24 05:23 .\ndrwxr-xr-x 4 root root 4096 Oct 24 05:23 ..\ndrwxr-xr-x 8 root root 4096 Oct 24 05:23 .git\n-rw-r--r-- 1 root root 5445 Oct 24 02:43 rates.py\n-rw-r--r-- 1 root root  208 Oct 24 02:43 test_rates.py\n\nstderr:; `git log --oneline -5 && ls docs/plans 2>/dev/null`: exit code: 2\nstdout:\n0e840b4 seed\n\nstderr:", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "long-output", "task_hash": "a7e928f67b93ac2a", "tokens_in": 2062, "tokens_out": 95, "trimmed_requests": 0, "ts": "2026-10-24T05:23:13+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 1, "wall_s": 4.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "65dc28a1ea223dca", "tokens_in": 161451, "tokens_out": 2897, "trimmed_requests": 0, "ts": "2026-10-24T05:24:45+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 91.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.04s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "65dc28a1ea223dca", "tokens_in": 43514, "tokens_out": 1813, "trimmed_requests": 0, "ts": "2026-10-24T05:25:32+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 46.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".....                                                                    [100%]\n5 passed in 0.04s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "multi-file", "task_hash": "65dc28a1ea223dca", "tokens_in": 70156, "tokens_out": 3041, "trimmed_requests": 0, "ts": "2026-10-24T05:26:55+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 21, "wall_s": 81.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "65dc28a1ea223dca", "tokens_in": 177491, "tokens_out": 3272, "trimmed_requests": 0, "ts": "2026-10-24T05:28:34+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 39, "wall_s": 99.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "d stderr arguments may not be used '\n                                 'with capture_output.')\n            kwargs['stdout'] = PIPE\n            kwargs['stderr'] = PIPE\n    \n        with Popen(*popenargs, **kwargs) as process:\n            try:\n                stdout, stderr = process.communicate(input, timeout=timeout)\n            except TimeoutExpired as exc:\n                process.kill()\n                if _mswindows:\n                    # Windows accumulates the output in a single blocking\n                    # read() call run on child threads, with the timeout\n                    # being done in a join() on those threads.  communicate()\n                    # _after_ kill() is required to collect that and add it\n                    # to the exception.\n                    exc.stdout, exc.stderr = process.communicate()\n                else:\n                    # POSIX _communicate already populated the output so\n                    # far into the TimeoutExpired exception.\n                    process.wait()\n                raise\n            except:  # Including KeyboardInterrupt, communicate handled that.\n                process.kill()\n                # We don't call process.wait() as .__exit__ does that for us.\n                raise\n            retcode = process.poll()\n            if check and retcode:\n>               raise CalledProcessError(retcode, process.args,\n                                         output=stdout, stderr=stderr)\nE               subprocess.CalledProcessError: Command '['/usr/bin/python', '-m', 'greeter', '--shout', 'Bob']' returned non-zero exit status 2.\n\n/usr/lib/python3.10/subprocess.py:526: CalledProcessError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_shout - TypeError: greet() got an un...\nFAILED .bench_check/test_hidden.py::test_cli_shout - SystemExit: 2\nFAILED .bench_check/test_hidden.py::test_module_entry_point - subprocess.Call...\n3 failed, 2 passed in 0.11s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "capped", "outcome_note": "hit the 40-turn cap", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "multi-file", "task_hash": "65dc28a1ea223dca", "tokens_in": 192763, "tokens_out": 4667, "trimmed_requests": 0, "ts": "2026-10-24T05:30:35+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 40, "wall_s": 120.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.25s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "0e3ae69d6d1a1f83", "tokens_in": 112064, "tokens_out": 3679, "trimmed_requests": 0, "ts": "2026-10-24T05:32:06+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 18, "wall_s": 90.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "0e3ae69d6d1a1f83", "tokens_in": 58522, "tokens_out": 2844, "trimmed_requests": 0, "ts": "2026-10-24T05:33:15+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 68.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "0e3ae69d6d1a1f83", "tokens_in": 43385, "tokens_out": 2258, "trimmed_requests": 0, "ts": "2026-10-24T05:34:09+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 53.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.24s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "0e3ae69d6d1a1f83", "tokens_in": 64481, "tokens_out": 2586, "trimmed_requests": 0, "ts": "2026-10-24T05:35:15+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 13, "wall_s": 65.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".......                                                                  [100%]\n7 passed in 0.23s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "refactor-rename", "task_hash": "0e3ae69d6d1a1f83", "tokens_in": 48476, "tokens_out": 2694, "trimmed_requests": 0, "ts": "2026-10-24T05:36:20+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 9, "wall_s": 64.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.28s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 11692, "tokens_out": 9942, "trimmed_requests": 0, "ts": "2026-10-24T05:39:22+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 4, "wall_s": 181.4}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "dden.py::test_invalid[h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[.5h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[+2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30m1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h2h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1s1m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1 h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[30 1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1h1.5m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.5s] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[0.01m] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1.5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:2] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:60] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1:02:03:04] - NotImplemented...\nFAILED .bench_check/test_hidden.py::test_invalid[1.5:30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[1: 30] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[   ] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-5] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_invalid[-1h] - NotImplementedError\nFAILED .bench_check/test_hidden.py::test_the_result_is_an_int - NotImplemente...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n49 failed in 0.29s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "escalated", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 65105, "tokens_out": 39162, "trimmed_requests": 0, "ts": "2026-10-24T05:51:23+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 16, "wall_s": 720.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.24s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 110249, "tokens_out": 39997, "trimmed_requests": 0, "ts": "2026-10-24T06:03:37+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 19, "wall_s": 733.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "rror: invalid ...\nE         FAILED test_durations.py::test_order_valid[1m30s-90] - ValueError: invalid du...\nE         FAILED test_durations.py::test_order_valid[2h45m-9900] - ValueError: invalid ...\nE         FAILED test_durations.py::test_spaces_valid[ 1h 30m -5400] - ValueError: inva...\nE         FAILED test_durations.py::test_spaces_valid[1h 30m-5400] - ValueError: invali...\nE         FAILED test_durations.py::test_spaces_valid[1d 2h 3m 4s-93784] - ValueError: ...\nE         FAILED test_durations.py::test_spaces_valid[1h  30m-5400] - ValueError: inval...\nE         FAILED test_durations.py::test_spaces_valid[2h 30m 15s-9015] - ValueError: in...\nE         FAILED test_durations.py::test_decimals_valid[1.5h30m-7200] - ValueError: inv...\nE         FAILED test_durations.py::test_decimals_valid[1.5h1m-5460] - ValueError: inva...\nE         FAILED test_durations.py::test_results_are_plain_ints - ValueError: invalid d...\nE         21 failed, 101 passed in 0.22s\nE         \nE       assert 1 == 0\nE        +  where 1 = CompletedProcess(args=['/usr/bin/python', '-m', 'pytest', '-q', 'test_durations.py'], returncode=1, stdout='....FFFF.....est_durations.py::test_results_are_plain_ints - ValueError: invalid d...\\n21 failed, 101 passed in 0.22s\\n', stderr='').returncode\n\n.bench_check/test_hidden.py:87: AssertionError\n=========================== short test summary info ============================\nFAILED .bench_check/test_hidden.py::test_valid[1h30m-5400] - ValueError: inva...\nFAILED .bench_check/test_hidden.py::test_valid[1d2h3m4s-93784] - ValueError: ...\nFAILED .bench_check/test_hidden.py::test_valid[1H30M-5400] - ValueError: inva...\nFAILED .bench_check/test_hidden.py::test_valid[2D-172800] - ValueError: inval...\nFAILED .bench_check/test_hidden.py::test_valid[ 1h 30m -5400] - ValueError: i...\nFAILED .bench_check/test_hidden.py::test_valid[1d 2h 3m 4s-93784] - ValueErro...\nFAILED .bench_check/test_hidden.py::test_the_plan_asked_for_tests_and_they_pass\n7 failed, 42 passed in 0.45s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "stuck", "outcome_note": "2 commands failed in a row: `cd /tmp/nisse-bench/df3e4e010d52475b9f9e778c3fae55de && sed -i 's/\"1h -30m\", \"0s 0s\"/\"1h -30m\", \"\\\\n\"/' test_durations.p`: alueError: inv...\nFAILED test_durations.py::test_decimals_valid[1.5h1m-5460] - ValueError: inva...\nFAILED test_durations.py::test_decimals_invalid[3.5m] - Failed: DID NOT RAISE...\nFAILED test_durations.py::test_results_are_plain_ints - ValueError: invalid d...\n17 failed, 105 passed in 0.23s\n\nstderr:; `cd /tmp/nisse-bench/df3e4e010d52475b9f9e778c3", "prose_turns": 1, "provider": "openai", "rate_limit_wait_s": 0.0, "success": false, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 80691, "tokens_out": 41924, "trimmed_requests": 0, "ts": "2026-10-24T06:16:12+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 754.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": ".................................................                        [100%]\n49 passed in 0.29s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "spec-parser", "task_hash": "da37be7fe1b360a6", "tokens_in": 211535, "tokens_out": 28749, "trimmed_requests": 0, "ts": "2026-10-24T06:25:29+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 24, "wall_s": 556.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 101324, "tokens_out": 12181, "trimmed_requests": 0, "ts": "2026-10-24T06:29:36+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 14, "wall_s": 246.6}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 84848, "tokens_out": 5649, "trimmed_requests": 0, "ts": "2026-10-24T06:31:41+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 12, "wall_s": 124.9}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 60619, "tokens_out": 9368, "trimmed_requests": 0, "ts": "2026-10-24T06:34:51+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 10, "wall_s": 189.8}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 2, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "failed", "outcome_note": "kept replying in prose", "prose_turns": 2, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 198038, "tokens_out": 20650, "trimmed_requests": 0, "ts": "2026-10-24T06:42:09+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 26, "wall_s": 437.2}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "..........                                                               [100%]\n10 passed in 0.02s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "trace-bug", "task_hash": "d5fc20a602374663", "tokens_in": 77502, "tokens_out": 6784, "trimmed_requests": 0, "ts": "2026-10-24T06:44:35+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 11, "wall_s": 146.0}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 20336, "tokens_out": 1119, "trimmed_requests": 0, "ts": "2026-10-24T06:45:04+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 8, "wall_s": 28.7}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 136343, "tokens_out": 5207, "trimmed_requests": 0, "ts": "2026-10-24T06:47:18+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 31, "wall_s": 134.1}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 48771, "tokens_out": 2452, "trimmed_requests": 0, "ts": "2026-10-24T06:48:20+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 16, "wall_s": 61.3}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 0, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 17838, "tokens_out": 982, "trimmed_requests": 0, "ts": "2026-10-24T06:48:47+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 26.5}
+{"backing": "openai/qwen3.8-flash-next", "check_output": "........                                                                 [100%]\n8 passed in 0.01s\n", "commit": "7a57cef", "cost": 0.0, "failed_commands": 1, "fallbacks": [], "invented_tools": 0, "model": "qwen3.8-flash-next", "model_info": {"max_input_tokens": 131072, "max_output_tokens": 32768, "supports_function_calling": true, "supports_tool_choice": true}, "note": "flash-next thinking, git ws", "outcome": "completed", "outcome_note": "", "prose_turns": 0, "provider": "openai", "rate_limit_wait_s": 0.0, "success": true, "task": "write-function", "task_hash": "9bb2ea20c66ef0c1", "tokens_in": 17749, "tokens_out": 1046, "trimmed_requests": 0, "ts": "2026-10-24T06:49:14+00:00", "tuning": {"build_vm": {"retry_s": 300.0, "settle_s": 180.0}, "context": {"compact_at": 0.6, "compact_keep_turns": 3, "compact_to": 0.25, "keep_recent_turns": 6, "safety_margin": 0.1}, "delegation": {"max_tokens": 200000, "max_turns": 30, "wall_clock_s": 900.0}, "driver": {"failure_limit": 2, "max_turns": 40}, "expert": {"consult_budget": 3}, "loop": {"bug_grace_s": 600.0, "general_idle_s": 86400.0}, "memory": {"max_turns": 10}, "preflight": {"command_timeout_s": 900, "max_turns": 20}, "tools": {"command_timeout_s": 120, "max_output_chars": 4000}}, "turns": 7, "wall_s": 27.0}

docs/Architecture.md

@@ -21,6 +21,7 @@ overnight and expects to be treated well in return.
 | Dev Agent | `nisse-dev` | Designs and builds software projects (Part D) |
 | Review Agent | `nisse-review` | Reviews pull requests (Part R) |
 | Sysadmin Agent | `nisse-ops` | Operates infrastructure (Part O) |
+| Status page | `nisse-ui` | Shows the operator what the agents are doing and how (X6); not an agent |
 
 More agents are planned (3D design work, video-file management), each another
 application over `nisse-core`. One string names all of an agent's artifacts
@@ -220,6 +221,10 @@ again after a restart), permissions (L3), and work in progress as intents (L8).
   next tool boundary, unmounts elevated credentials, and asks what next.
 - **`abandon` ends a work item** from any waiting point, closing its record and
   any open PRs with a note and aborting its unresolved intents.
+- **A run going in circles ends** rather than running to its turn cap: turns that
+  repeat near-identically, or one correction (such as "reply with a tool call")
+  given again and again, end it in code, escalated with what it was doing. A loop
+  the model can't leave is the harness's to fix, not the model's to push through.
 - **Every action passes through the three layers** (P4).
 
 ### L3. Authority: scope and approvals
@@ -278,7 +283,8 @@ executes nothing, so it runs on the agent host.
 
 **Matrix is the conversation channel:** a self-hosted homeserver, one identity and
 room per agent, behind a `Transport` interface so another chat system is one new
-class. Existing Matrix clients are the UI.
+class. Existing Matrix clients are the UI for conversation and commands; a
+read-only page shows each agent's work, and how it went, in detail (X6).
 
 **A thread per work item.** Each item's conversation is a Matrix thread, and the
 thread is how the agent knows which item a message is about.
@@ -332,7 +338,8 @@ logs the outage; interrupted outbound effects are covered by intents (L8).
 ### L6. Context and memory
 
 **1. The working context of one model call** is rendered from the log at call time
-for one role, fitted to that model's window, and never stored.
+for one role, fitted to that model's window, and never stored as state. A copy
+goes into the call record (L7) for the operator to study; nothing reads it back.
 - **A long run is compacted:** well before the window fills, the model's own
   notes replace the middle of its run in one step (a `compaction` event, L7),
   keeping word for word what started the work and its last few turns. Rare,
@@ -411,6 +418,30 @@ call time.
   delegation that produced it.
 - **The log is never edited;** corrections and compactions are new events.
 
+**The call record** is a second store beside the log, for study only: `nisse-core`
+writes it for every model call of every agent, into its own file on the agent's
+volume.
+- **What each call was:** the request exactly as sent (system prompt, tools,
+  messages, `tool_choice`, output limit; never headers, so no credential), the raw
+  response with its reasoning, the model asked and the one that answered, time,
+  tokens, the server's own count of prompt reuse, and what fitting cut. A failed
+  call is recorded with its error.
+- **Where it came from:** its work item, role and run (a driver run, a consult, a
+  compaction, a classification), and for each message, the log events it was
+  rendered from and what rendering did to them (unchanged, labelled, narrated,
+  compacted, shortened and by how much), with what was dropped. So a request reads
+  against the log it was made from (L6).
+- **Content is stored once,** by hash: a long, growing conversation costs about one
+  copy of itself.
+- **It is never load-bearing:** nothing in the agent reads it, a failed write is
+  logged and the call goes ahead, and it is deleted when the agent starts. Its
+  layout never migrates; it carries its version for the page (X6).
+- **Agents are told:** while it records, each system prompt says in one sentence
+  that the agent's calls are recorded for the operator's study.
+- **On by default, off per agent** in its configuration: an agent that handles
+  other people's lives (a household's presence, conversations, cameras) records
+  nothing unless they know.
+
 ### L8. Durability and recovery
 
 **The state store** (SQLite) holds each work item's position, permissions, pending
@@ -1078,8 +1109,9 @@ template with a trigger, rate limit and expiry, for a routine fix).
 
 **One agent host,** stable and long-lived. Each agent is a container on it with its
 own volume (state, transcripts), secrets (L12) and network; no agent can reach
-another's. Its MCP servers run beside it (X3). The vault lives here (L10). **It never
+another's, and only the status page reads their volumes, read-only (X6). Its MCP
-runs a command a model chose** (L13), which is what makes sharing it safe.
+servers run beside it (X3). The vault lives here (L10). **It never runs a command
+a model chose** (L13), which is what makes sharing it safe.
 
 **Tool VMs** are where model-chosen commands run, reached only over SSH from the
 agent host, each built from a template plus recorded installs and disposable:
@@ -1135,10 +1167,52 @@ Vaultwarden, Samba AD with Authelia, and SilverBullet for the operator's view of
 the vault. Each agent has its own account, token and room in each; nothing is
 shared between agents.
 
+### X6. The status page
+
+**`nisse-ui`** is the operator's view of the agents: what each is doing, and how it
+did it in full detail. It is for understanding the system (how context, compaction
+and memory work in practice), more than for daily use.
+- **What it shows:** per agent, the active item, what's queued, parked and blocked
+  and why, recent closed items, with links to issue, PR and thread; and per item, a
+  walkthrough: its steps (runs, and the orchestrator's facts and gates between
+  them), each run's turns, and each turn's request and response from the call
+  record (L7), readable: where each message came from and what was done to it,
+  what changed since the previous turn and where prompt reuse stopped, the
+  reasoning, and the raw JSON. Memory appears as the log records it: the index
+  when it was shown, each note read or written. Work from before the agent's last
+  start has its steps but no requests.
+- **Loops are flagged:** near-identical turns, repeated apologies, one correction
+  given again and again, so they're seen and fixed (L2).
+- **It reads, never writes:** each agent's state store and call record through a
+  read-only mount, opened read-only in short transactions, and the agent's memory
+  folder read-only, as SilverBullet does (L10). Each agent stays the only writer
+  of its state (L8), and agent code doesn't change for the page. It runs no
+  model, holds no credentials and reaches nothing but the mounts and Caddy.
+- **Versions:** it is released with the agents, from the same tag. It reads the
+  state store's schema versions it knows and says so for any other, rather than
+  guessing; it reads item data tolerantly (defaults for missing fields, raw names
+  for unknown states), for the gap while one container updates before another.
+  CI tests it against stores written by the agents' own code, so a change that
+  would break it fails in the same PR.
+- **Any recorded run opens,** not only a live agent's: bring-up, end-to-end and
+  benchmark runs leave the same two files.
+- **Everything it shows is untrusted text** (L11): it is escaped, and the page
+  allows no script it didn't ship.
+- **Access** is through Caddy behind Authelia, the operator's group only: it shows
+  everything the models saw, including what other people wrote (peers, issue
+  authors, whatever an agent handles). Nothing is exported from it.
+- **Commands come later** (Part Q), never by writing an agent's files: as another
+  `Transport` (L5), so a button sends what Matrix would, with the same rules and
+  record.
+
 ---
 
 ## Part Q — Open questions
 
+- **Commands from the status page** (X6): how they reach each agent and show who
+  sent them (a per-agent inbox only the page writes, or signed requests). The
+  first are `stop`, priority ("do #N next"), and a **hold**: a task, or a whole
+  agent, does nothing until released. A hold is a new command, in Matrix too.
 - **The classifier's model,** and how its verdicts are calibrated against overrides.
 - **Recognising questions:** an explicit marker or classification; a misread asks.
 - **How far the local driver goes,** measured on real work (P7).

docs/Development-Plan.md

@@ -40,7 +40,7 @@ Only `nisse-dev` has real code; `nisse-core` and `nisse-ops` are placeholders.
 | **D3–D4** Workspace, git | partial | Idempotent publishing; no fresh workspace (#62), `git add -A` (#80) |
 | **D5** Review | partial | PR conversation comments only (#69), watch stall (#70) |
 | **D7–D8** Deployment, projects | partial | Bring-up runs `nisse-dev`'s and `nisse-review`'s images under systemd on this box; project entries in config (M1.4); egress not enforced |
-| **O**, **X** | partial | `nisse-dev` has its image (M1.5), `nisse-review` its own (M7.6, acceptance after merge); nothing runs on the agent host |
+| **O**, **X** | partial | `nisse-dev` has its image (M1.5), `nisse-review` its own (M7.6, acceptance after merge); nothing runs on the agent host; the status page's walkthrough runs on this box (M6.6b) |
 | `specs/` | done for now | `loop.qnt` (the architecture, #91); `orchestrator.qnt` went with `control.py` (M2.8) |
 
 ---
@@ -578,6 +578,25 @@ Samba AD principal (L12).
 
 **M6.5 The browser tool.** *Pre-approved.* On the internal test network (D7).
 
+**M6.6 The status page.** *Pre-approved (design agreed 2026-10-24, #109).*
+`nisse-ui` (X6), for studying how the agents work: context, compaction, memory.
+Slices a–c are built on this box before the agent host is ready, against
+bring-up, end-to-end and benchmark runs; only d waits for M6.1.
+- **a. The call record** (L7) in `nisse-core`: written by the shared model client
+  and `Driver.run`, with each message's provenance from the per-role view and
+  fitting; wired in each agent's build; deleted at start. Each system prompt
+  says the calls are recorded, while they are. **Done** (#179).
+- **b. The walkthrough:** an item's steps, each run's turns, and each request read
+  against the log it was made from; runs going in circles flagged. **Done** (this
+  PR): the `nisse-ui` package, on 127.0.0.1 behind an SSH tunnel until d. The
+  loop rules are `nisse_core.loop.circles`, for M7.8 to reuse.
+- **c. The overview:** each agent's active, queued, parked and blocked items.
+- **d. Deployment:** its image, the read-only mounts and a Caddy route behind
+  Authelia (with #166).
+
+Commands wait (Part Q). The shared database #109 first proposed is dropped: each
+agent keeps its own store.
+
 ### Phase 7 — `nisse-core` and `nisse-review`
 
 `nisse-review` (Part R) comes before `nisse-ops`: it writes only comments, so it
@@ -780,6 +799,13 @@ publishes `gitea.dongar.net/dev/nisse-review` beside `nisse-dev`, and
 **M7.7 Deployment.** *Waits for the agent host (Phase 6).* Its container on the
 agent host, Gitea account and secrets (R5).
 
+**M7.8 Runs that go in circles end** (L2). *Pre-approved.* In `Driver.run`, for
+every agent. Seen 2026-10-24 on Flash-Next: invented tool names met with the
+prose reminder turn after turn, and a no-thinking run posting the same apology
+comment about 20 times until the turn cap. Repeated near-identical turns, or the
+same correction given too often, end the run as escalated, with what it was
+doing; the limits are tuning.
+
 ### Phase 8 — `nisse-ops`
 
 **M8.1 MCP servers** (#37). Settled so far: redaction scrubs each instance's own
@@ -796,6 +822,7 @@ the Terraform the operator is writing now. **M8.4 The ops tool VM and deployment
 From the architecture's open questions and older issues: filing issues from
 conversation; stacked PRs; releases; `nisse-ops` issuing credentials; a server
 database; recovering the agent host (an ops issue); more than one active work item;
+commands from the status page, with a hold on a task or agent (X6);
 vision; one local model for every agent; several forges (#26); a room per project
 (#28).
 
@@ -816,6 +843,7 @@ vision; one local model for every agent; several forges (#26); a room per projec
 | #69 inline review comments | M2.1 |
 | #70 watch stall | M2.1 |
 | #77 conversational agent | M2.3 (questions), M2.7 |
+| #109 a UI for every agent's status (no shared database) | M6.6 |
 | #137 block on an unreachable build VM | M4.4 |
 | #144 redact secrets an MCP server returns | After M8.1 |
 

nisse-core/src/nisse_core/loop/circles.py

@@ -0,0 +1,111 @@
+"""Runs going in circles (L2, X6): turns that repeat near-identically, one
+correction given again and again, or apologies over and over.
+
+A pure function over a run's turns, so the status page can flag a loop now
+and ``Driver.run`` can end one later (M7.8) from the same rules.
+"""
+
+import re
+from collections.abc import Sequence
+from dataclasses import dataclass
+from difflib import SequenceMatcher
+
+SIMILAR = 0.9  # how alike two replies are to count as the same
+REPEATS = 3  # how many times before it's a circle
+_COMPARED = 2000  # characters of each reply compared
+
+_APOLOGY = re.compile(
+    r"\b(sorry|apologi[sz]e|apologies|my mistake|my apologies|please disregard|"
+    r"disregard (this|that|the previous|my))\b",
+    re.IGNORECASE,
+)
+
+
+@dataclass(frozen=True)
+class Turn:
+    """What a circle is judged on: the model's reply (its text and tool
+    calls) and what the harness told it before this turn."""
+
+    text: str = ""
+    calls: tuple[tuple[str, str], ...] = ()  # (tool, arguments as sent)
+    told: tuple[str, ...] = ()  # corrections given since the turn before
+
+
+@dataclass(frozen=True)
+class Circle:
+    kind: str  # "repeated reply" | "repeated correction" | "repeated apology"
+    turns: tuple[int, ...]  # indexes into the turns given
+    detail: str
+
+
+def find_circles(
+    turns: Sequence[Turn], *, similar: float = SIMILAR, repeats: int = REPEATS
+) -> list[Circle]:
+    """Every circle in a run, in the order they started."""
+    found = _repeated_replies(turns, similar, repeats)
+    found += _repeated_corrections(turns, repeats)
+    apologies = tuple(i for i, t in enumerate(turns) if _APOLOGY.search(t.text))
+    if len(apologies) >= repeats:
+        found.append(
+            Circle(
+                "repeated apology",
+                apologies,
+                f"the model apologised in {len(apologies)} turns",
+            )
+        )
+    return sorted(found, key=lambda c: c.turns[0])
+
+
+def _signature(turn: Turn) -> str:
+    calls = "\n".join(f"{tool}({args})" for tool, args in turn.calls)
+    return f"{turn.text.strip()}\n{calls}"[:_COMPARED]
+
+
+def _alike(a: str, b: str, similar: float) -> bool:
+    if a == b:
+        return True
+    matcher = SequenceMatcher(None, a, b, autojunk=False)
+    return matcher.quick_ratio() >= similar and matcher.ratio() >= similar
+
+
+def _repeated_replies(
+    turns: Sequence[Turn], similar: float, repeats: int
+) -> list[Circle]:
+    """Stretches of consecutive turns each alike the one before."""
+    found: list[Circle] = []
+    signatures = [_signature(t) for t in turns]
+    start = 0
+    for i in range(1, len(turns) + 1):
+        if (
+            i < len(turns)
+            and signatures[i].strip()
+            and _alike(signatures[i - 1], signatures[i], similar)
+        ):
+            continue
+        if i - start >= repeats:
+            found.append(
+                Circle(
+                    "repeated reply",
+                    tuple(range(start, i)),
+                    f"{i - start} near-identical replies in a row",
+                )
+            )
+        start = i
+    return found
+
+
+def _repeated_corrections(turns: Sequence[Turn], repeats: int) -> list[Circle]:
+    """One correction given in ``repeats`` or more turns, in a row or not."""
+    given: dict[str, list[int]] = {}
+    for i, turn in enumerate(turns):
+        for text in dict.fromkeys(turn.told):
+            given.setdefault(text, []).append(i)
+    return [
+        Circle(
+            "repeated correction",
+            tuple(at),
+            f"told {len(at)} times: {text[:120]}",
+        )
+        for text, at in given.items()
+        if len(at) >= repeats
+    ]

nisse-core/src/nisse_core/loop/driver.py

@@ -15,6 +15,7 @@ from typing import Any, Literal, Protocol
 
 from nisse_core.log.canonical import AssistantText, Fact, ToolCall, ToolResult
 from nisse_core.loop.tools import names
+from nisse_core.models import calls
 from nisse_core.models.compact import Compactor
 from nisse_core.models.llm import LLMClient, LLMError
 from nisse_core.state.cancel import Cancel, skip_calls
@@ -93,7 +94,19 @@ class Driver:
         self._failure_limit = failure_limit
         self._cancel = cancel or Cancel()
 
-    def run(
+    def run(self, transcript: Transcript, **options: Any) -> RunOutcome:
+        """One run, recorded as one (L7): its calls are its turns. See
+        ``_run`` for the options."""
+        with calls.run(
+            calls.recorder_of(self._client),
+            work_item=transcript.work_item,
+            role=transcript.actor,
+        ) as recorded:
+            outcome = self._run(transcript, **options)
+            recorded.end(outcome.kind, outcome.note)
+            return outcome
+
+    def _run(
         self,
         transcript: Transcript,
         *,

nisse-core/src/nisse_core/loop/expert.py

@@ -32,6 +32,7 @@ from nisse_core.log.canonical import (
     StoredEvent,
     UserMessage,
 )
+from nisse_core.models import calls
 from nisse_core.models.llm import LLMClient, LLMError, ModelRefused, RoleMap
 from nisse_core.state.store import Transcript
 
@@ -156,6 +157,7 @@ class ExpertDesk:
                 # consult neither depends on nor leaks repo context. It cannot
                 # ride in the system prompt alone — the Messages API requires
                 # at least one non-system message.
+                with calls.purpose("consult", role="expert"):
                     produced = self._client.complete(
                         [
                             StoredEvent(

nisse-core/src/nisse_core/models/calls.py

@@ -0,0 +1,519 @@
+"""The call record (architecture L7, X6): every model call an agent makes,
+kept for the operator to study, never for the agent to read.
+
+Each call is recorded as it was sent and answered: the request body exactly
+(never its headers, so no credential), the raw response with its reasoning,
+the model asked and the one that answered, time, tokens and the server's own
+count of prompt reuse. Beside that, where the request came from: its work
+item, role and run, and for each event sent, its log id and its content as
+sent, with what compaction replaced, what fitting shortened or dropped. The
+status page reads a request against the state store it was made from.
+
+It is diagnostic only. Nothing in the agent reads it, a write that fails is
+logged once and recording stops while the call goes ahead, and the file is
+deleted when the agent starts, so its layout never migrates: it carries a
+version, and a reader that doesn't know it says so.
+
+Content is stored once by hash and compressed, so a conversation that grows
+by a turn a call costs about one copy of itself.
+
+Runs and purposes reach the recorder through a context variable: the driver
+opens a run around its turns (``run``), and a call made for something else
+(a compaction, a consult) says so (``purpose``).
+"""
+
+import contextlib
+import hashlib
+import json
+import sqlite3
+import threading
+import uuid
+import zlib
+from collections.abc import Iterable, Iterator, Mapping, Sequence
+from contextvars import ContextVar
+from dataclasses import dataclass, replace
+from datetime import UTC, datetime
+from pathlib import Path
+from typing import Any
+
+from nisse_core.log.canonical import StoredEvent, event_type, to_payload
+from nisse_core.oplog import OpLog
+from nisse_core.state import readonly
+
+LAYOUT_VERSION = 1
+
+# Said to the model, at the end of its system prompt, while its calls are
+# recorded (L7): it is the operator's record, and the agent should know.
+NOTICE = "Your model calls are recorded for the operator's study."
+
+_SCHEMA = (
+    "CREATE TABLE meta (key TEXT PRIMARY KEY, value TEXT NOT NULL)",
+    "CREATE TABLE blobs (hash TEXT PRIMARY KEY, data BLOB NOT NULL)",
+    """
+    CREATE TABLE runs (
+        id TEXT PRIMARY KEY,
+        parent TEXT,
+        work_item TEXT,
+        role TEXT NOT NULL,
+        kind TEXT NOT NULL,
+        started_at TEXT NOT NULL,
+        ended_at TEXT,
+        outcome TEXT,
+        note TEXT
+    )
+    """,
+    """
+    CREATE TABLE calls (
+        id INTEGER PRIMARY KEY AUTOINCREMENT,
+        at TEXT NOT NULL,
+        seconds REAL NOT NULL,
+        run TEXT,
+        work_item TEXT,
+        role TEXT,
+        purpose TEXT,
+        model TEXT NOT NULL,
+        answered_by TEXT,
+        outcome TEXT NOT NULL,
+        error TEXT,
+        tokens_in INTEGER,
+        tokens_out INTEGER,
+        tokens_cached INTEGER,
+        cache_n INTEGER,
+        prompt_n INTEGER,
+        estimate INTEGER,
+        factor REAL,
+        route TEXT,
+        status INTEGER,
+        request TEXT,
+        response TEXT,
+        sent TEXT NOT NULL,
+        compacted TEXT NOT NULL,
+        shortened TEXT NOT NULL,
+        dropped TEXT NOT NULL,
+        trim TEXT
+    )
+    """,
+    "CREATE INDEX calls_by_run ON calls (run, id)",
+    "CREATE INDEX calls_by_item ON calls (work_item, id)",
+)
+
+
+def utc_now() -> str:
+    return datetime.now(UTC).isoformat()
+
+
+def path_for(state_db: Path) -> Path:
+    """Where an agent's call record lives: beside its state store, named
+    after it, so two agents sharing a directory keep two records."""
+    return state_db.with_name(f"{state_db.stem}.calls.db")
+
+
+def recorder_for(
+    state_db: Path, enabled: bool, oplog: OpLog | None = None
+) -> "CallRecorder | None":
+    """An agent's recorder, as its configuration has it (L7): made, and so
+    the old record deleted, when the agent starts."""
+    return CallRecorder(path_for(state_db), oplog=oplog) if enabled else None
+
+
+def with_notice(system: str | None) -> str:
+    return f"{system}\n\n{NOTICE}" if system else NOTICE
+
+
+# Where a call is made from, for its record.
+
+
+@dataclass(frozen=True)
+class Scope:
+    run: str | None = None
+    parent: str | None = None
+    work_item: str | None = None
+    role: str | None = None
+    purpose: str | None = None
+
+
+_OUTSIDE = Scope()  # no run, no purpose: frozen, so safe to share
+_scope: ContextVar[Scope] = ContextVar("nisse_call_scope", default=_OUTSIDE)
+
+
+def current() -> Scope:
+    return _scope.get()
+
+
+class RunHandle:
+    """Says how a run ended, for its record."""
+
+    def __init__(self) -> None:
+        self.outcome = ""
+        self.note = ""
+
+    def end(self, outcome: str, note: str = "") -> None:
+        self.outcome, self.note = outcome, note
+
+
+def recorder_of(client: Any) -> "CallRecorder | None":
+    """The recorder a client records into, through any wrappers (they pass
+    attributes on); None if it records nothing."""
+    found = getattr(client, "call_recorder", None)
+    return found if isinstance(found, CallRecorder) else None
+
+
+@contextlib.contextmanager
+def run(
+    recorder: "CallRecorder | None",
+    *,
+    work_item: str | None,
+    role: str,
+    kind: str = "run",
+) -> Iterator[RunHandle]:
+    """A run: the calls made inside it are its turns. Nested in any run
+    already open (a delegation inside a driver run)."""
+    outer = _scope.get()
+    run_id = uuid.uuid4().hex[:16]
+    handle = RunHandle()
+    if recorder is not None:
+        recorder.run_started(run_id, outer.run, work_item, role, kind)
+    token = _scope.set(
+        Scope(run=run_id, parent=outer.run, work_item=work_item, role=role)
+    )
+    try:
+        yield handle
+    except BaseException as exc:
+        handle.end("error", f"{type(exc).__name__}: {exc}"[:500])
+        raise
+    finally:
+        _scope.reset(token)
+        if recorder is not None:
+            recorder.run_ended(run_id, handle.outcome, handle.note)
+
+
+@contextlib.contextmanager
+def purpose(name: str, *, role: str | None = None) -> Iterator[None]:
+    """Calls made inside are for ``name`` (a compaction, a consult), by
+    ``role`` when it isn't the run's."""
+    outer = _scope.get()
+    token = _scope.set(replace(outer, purpose=name, role=role or outer.role))
+    try:
+        yield
+    finally:
+        _scope.reset(token)
+
+
+# What a call did to the events it was given (L6), for its record.
+
+
+@dataclass(frozen=True)
+class Provenance:
+    sent: Sequence[StoredEvent]  # what went out, in order, as sent
+    compacted: Mapping[int, int | None]  # event id -> the compaction that replaced it
+    shortened: Mapping[int, int]  # event id -> characters fitting cut
+    dropped: Sequence[int]  # event ids fitting left out
+
+
+def _encode(value: Any) -> tuple[str, bytes]:
+    text = json.dumps(value, ensure_ascii=False, sort_keys=False)
+    digest = hashlib.sha256(text.encode()).hexdigest()[:32]
+    return digest, zlib.compress(text.encode(), 6)
+
+
+class CallRecorder:
+    """Writes the call record. Never raises into the call it records: the
+    first failure is logged and recording stops."""
+
+    def __init__(self, path: str | Path, *, oplog: OpLog | None = None) -> None:
+        self.path = Path(path)
+        self._oplog = oplog
+        self._lock = threading.Lock()
+        self._conn: sqlite3.Connection | None = None
+        self.active = False
+        try:
+            # Deleted at start (L7): records live as long as the process, so
+            # the layout never needs migrating.
+            for suffix in ("", "-wal", "-shm"):
+                Path(f"{self.path}{suffix}").unlink(missing_ok=True)
+            conn = sqlite3.connect(
+                self.path, isolation_level=None, check_same_thread=False
+            )
+            # WAL so the status page can read while the agent writes; no
+            # fsync per write, since a record lost in a power cut costs nothing.
+            conn.execute("PRAGMA journal_mode=WAL")
+            conn.execute("PRAGMA synchronous=NORMAL")
+            conn.execute("BEGIN")
+            for statement in _SCHEMA:
+                conn.execute(statement)
+            conn.execute(
+                "INSERT INTO meta (key, value) VALUES ('layout_version', ?), "
+                "('started_at', ?)",
+                (str(LAYOUT_VERSION), utc_now()),
+            )
+            conn.execute("COMMIT")
+            self._conn = conn
+            self.active = True
+        except (OSError, sqlite3.Error) as exc:
+            self._failed(exc)
+
+    def _failed(self, exc: BaseException) -> None:
+        self.active = False
+        if self._oplog is not None:
+            self._oplog.emit(
+                "calls.record_failed",
+                cause="recording stopped; the calls go on",
+                path=str(self.path),
+                error=f"{type(exc).__name__}: {exc}"[:300],
+            )
+
+    def _write(self, write: Any) -> None:
+        if not self.active or self._conn is None:
+            return
+        with self._lock:
+            try:
+                self._conn.execute("BEGIN")
+                write(self._conn)
+                self._conn.execute("COMMIT")
+            except Exception as exc:  # noqa: BLE001 -- never into the call
+                with contextlib.suppress(sqlite3.Error):
+                    self._conn.execute("ROLLBACK")
+                self._failed(exc)
+
+    def _blob(self, conn: sqlite3.Connection, value: Any) -> str:
+        digest, data = _encode(value)
+        conn.execute(
+            "INSERT OR IGNORE INTO blobs (hash, data) VALUES (?, ?)", (digest, data)
+        )
+        return digest
+
+    def run_started(
+        self,
+        run_id: str,
+        parent: str | None,
+        work_item: str | None,
+        role: str,
+        kind: str,
+    ) -> None:
+        self._write(
+            lambda conn: conn.execute(
+                "INSERT INTO runs (id, parent, work_item, role, kind, started_at) "
+                "VALUES (?, ?, ?, ?, ?, ?)",
+                (run_id, parent, work_item, role, kind, utc_now()),
+            )
+        )
+
+    def run_ended(self, run_id: str, outcome: str, note: str) -> None:
+        self._write(
+            lambda conn: conn.execute(
+                "UPDATE runs SET ended_at = ?, outcome = ?, note = ? WHERE id = ?",
+                (utc_now(), outcome, note, run_id),
+            )
+        )
+
+    def record(
+        self,
+        *,
+        at: str,
+        seconds: float,
+        model: str,
+        answered_by: str | None,
+        error: str | None,
+        usage: Mapping[str, int],
+        exchange: Mapping[str, Any] | None,
+        provenance: Provenance,
+        estimate: int | None,
+        factor: float,
+        trim: Mapping[str, Any] | None,
+    ) -> None:
+        scope = _scope.get()
+
+        def write(conn: sqlite3.Connection) -> None:
+            request = response = route = status = None
+            timings: Mapping[str, Any] = {}
+            if exchange is not None:
+                route = exchange.get("route")
+                status = exchange.get("status")
+                body = exchange.get("request")
+                if isinstance(body, Mapping):
+                    request = json.dumps(_split(conn, self, body))
+                if "response" in exchange:
+                    raw = exchange["response"]
+                    response = self._blob(conn, raw)
+                    if isinstance(raw, Mapping) and isinstance(
+                        raw.get("timings"), Mapping
+                    ):
+                        timings = raw["timings"]
+            sent = [
+                [
+                    s.id,
+                    s.actor,
+                    event_type(s.event),
+                    self._blob(conn, to_payload(s.event)),
+                ]
+                for s in provenance.sent
+            ]
+            conn.execute(
+                """
+                INSERT INTO calls (
+                    at, seconds, run, work_item, role, purpose, model, answered_by,
+                    outcome, error, tokens_in, tokens_out, tokens_cached, cache_n,
+                    prompt_n, estimate, factor, route, status, request,
+                    response, sent, compacted, shortened, dropped, trim
+                ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?,
+                          ?, ?, ?, ?, ?, ?, ?, ?)
+                """,
+                (
+                    at,
+                    round(seconds, 3),
+                    scope.run,
+                    scope.work_item,
+                    scope.role,
+                    scope.purpose,
+                    model,
+                    answered_by,
+                    "failed" if error is not None else "answered",
+                    error,
+                    usage.get("input"),
+                    usage.get("output"),
+                    usage.get("cached"),
+                    _int(timings.get("cache_n")),
+                    _int(timings.get("prompt_n")),
+                    estimate,
+                    factor,
+                    route,
+                    status,
+                    request,
+                    response,
+                    json.dumps(sent),
+                    json.dumps({str(k): v for k, v in provenance.compacted.items()}),
+                    json.dumps({str(k): v for k, v in provenance.shortened.items()}),
+                    json.dumps(list(provenance.dropped)),
+                    json.dumps(dict(trim)) if trim is not None else None,
+                ),
+            )
+
+        self._write(write)
+
+    def close(self) -> None:
+        with self._lock:
+            self.active = False
+            if self._conn is not None:
+                with contextlib.suppress(sqlite3.Error):
+                    self._conn.close()
+                self._conn = None
+
+
+def _int(value: Any) -> int | None:
+    return (
+        int(value)
+        if isinstance(value, int | float) and not isinstance(value, bool)
+        else None
+    )
+
+
+def _split(
+    conn: sqlite3.Connection, recorder: CallRecorder, body: Mapping[str, Any]
+) -> dict[str, Any]:
+    """A request body as hashes: each top-level field once, and the messages
+    one by one, since each call repeats the conversation before it."""
+    fields: list[list[Any]] = []
+    for key, value in body.items():
+        if key == "messages" and isinstance(value, list):
+            fields.append([key, [recorder._blob(conn, m) for m in value]])
+        else:
+            fields.append([key, recorder._blob(conn, value)])
+    return {"fields": fields}
+
+
+# Reading it back: the status page's side, and the tests'.
+
+
+class UnknownLayout(RuntimeError):
+    pass
+
+
+class CallReader:
+    """Opens a call record read-only and never writes to it (``readonly``)."""
+
+    def __init__(self, path: str | Path) -> None:
+        self._conn = readonly.connect(path)
+        row = self._conn.execute(
+            "SELECT value FROM meta WHERE key = 'layout_version'"
+        ).fetchone()
+        self.layout_version = int(row["value"]) if row else 0
+        if self.layout_version != LAYOUT_VERSION:
+            self._conn.close()
+            raise UnknownLayout(
+                f"call record layout {self.layout_version}; this reader knows "
+                f"{LAYOUT_VERSION}"
+            )
+        row = self._conn.execute(
+            "SELECT value FROM meta WHERE key = 'started_at'"
+        ).fetchone()
+        # When recording began: work before it has its log but no requests.
+        self.started_at: str | None = row["value"] if row else None
+
+    def blob(self, digest: str) -> Any:
+        row = self._conn.execute(
+            "SELECT data FROM blobs WHERE hash = ?", (digest,)
+        ).fetchone()
+        if row is None:
+            raise KeyError(digest)
+        return json.loads(zlib.decompress(row["data"]).decode())
+
+    def runs(self) -> list[dict[str, Any]]:
+        return [
+            dict(r)
+            for r in self._conn.execute("SELECT * FROM runs ORDER BY started_at")
+        ]
+
+    def calls(self, *, run: str | None = None) -> list[dict[str, Any]]:
+        if run is None:
+            rows = self._conn.execute("SELECT * FROM calls ORDER BY id")
+        else:
+            rows = self._conn.execute(
+                "SELECT * FROM calls WHERE run = ? ORDER BY id", (run,)
+            )
+        return self._decoded(rows)
+
+    def calls_for(self, work_item: str | None) -> list[dict[str, Any]]:
+        """One work item's calls, or the agent-level ones (None)."""
+        if work_item is None:
+            rows = self._conn.execute(
+                "SELECT * FROM calls WHERE work_item IS NULL ORDER BY id"
+            )
+        else:
+            rows = self._conn.execute(
+                "SELECT * FROM calls WHERE work_item = ? ORDER BY id", (work_item,)
+            )
+        return self._decoded(rows)
+
+    def call(self, call_id: int) -> dict[str, Any] | None:
+        rows = self._conn.execute("SELECT * FROM calls WHERE id = ?", (call_id,))
+        found = self._decoded(rows)
+        return found[0] if found else None
+
+    def _decoded(self, rows: Iterable[sqlite3.Row]) -> list[dict[str, Any]]:
+        out = []
+        for row in rows:
+            call = dict(row)
+            for key in ("sent", "compacted", "shortened", "dropped"):
+                call[key] = json.loads(call[key])
+            call["trim"] = json.loads(call["trim"]) if call["trim"] else None
+            out.append(call)
+        return out
+
+    def request(self, call: Mapping[str, Any]) -> dict[str, Any] | None:
+        """The request body exactly as sent, rebuilt."""
+        if not call.get("request"):
+            return None
+        body: dict[str, Any] = {}
+        for key, value in json.loads(call["request"])["fields"]:
+            body[key] = (
+                [self.blob(h) for h in value]
+                if isinstance(value, list)
+                else self.blob(value)
+            )
+        return body
+
+    def response(self, call: Mapping[str, Any]) -> Any:
+        return self.blob(call["response"]) if call.get("response") else None
+
+    def close(self) -> None:
+        self._conn.close()

nisse-core/src/nisse_core/models/compact.py

@@ -39,6 +39,7 @@ from nisse_core.log.canonical import (
     ToolCall,
     UserMessage,
 )
+from nisse_core.models import calls
 from nisse_core.models.context import _MODEL_SIDE, _turn_starts
 from nisse_core.models.llm import LLMError
 from nisse_core.models.render import effective_events
@@ -207,6 +208,7 @@ class Compactor:
         ask = StoredEvent(
             id=0, ts="", event=UserMessage(text=NOTES_REQUEST, source="compaction")
         )
+        with calls.purpose("compaction"):
             produced = self._client.complete(
                 [*events, ask], tools, model, system=system, require_tool_call=False
             )

nisse-core/src/nisse_core/models/context.py

@@ -31,6 +31,7 @@ dangerous direction.
 """
 
 import json
+import time
 from collections.abc import Callable, Sequence
 from dataclasses import dataclass, replace
 from typing import Any
@@ -38,6 +39,7 @@ from typing import Any
 from nisse_core.log.canonical import (
     AssistantText,
     CanonicalEvent,
+    Compaction,
     DelegationStarted,
     PlanSubmitted,
     StoredEvent,
@@ -45,6 +47,7 @@ from nisse_core.log.canonical import (
     ToolResult,
     UserMessage,
 )
+from nisse_core.models import calls
 from nisse_core.models.llm import DEFAULT_MAX_OUTPUT_TOKENS, LLMError
 from nisse_core.models.render import effective_events
 from nisse_core.oplog import OpLog
@@ -263,8 +266,12 @@ class BudgetedClient:
         safety_margin: float = 0.1,
         enforces_tool_choice: Callable[[str], bool] = lambda model: False,
         oplog: OpLog | None = None,
+        call_recorder: calls.CallRecorder | None = None,
     ) -> None:
         self._inner = inner
+        # Every call is recorded here for the operator's study (L7), while it
+        # is active; the benchmark swaps it per run.
+        self.call_recorder = call_recorder
         self._oplog = oplog
         self._limits_for = limits_for
         # Whether a model's server holds it to the offered tools when asked
@@ -297,6 +304,31 @@ class BudgetedClient:
     def last_rate_limit_wait_s(self) -> float:
         return float(getattr(self._inner, "last_rate_limit_wait_s", 0.0) or 0.0)
 
+    def _log_call(self, model: str, started: float, error: str | None = None) -> None:
+        """One event per model call: how long it took and what it used, so a
+        slow turn shows whether reading or writing took the time."""
+        if self._oplog is None:
+            return
+        fields: dict[str, Any] = {
+            "model": model,
+            "seconds": round(time.monotonic() - started, 1),
+        }
+        if error is not None:
+            self._oplog.emit("llm.call", cause="failed", error=error, **fields)
+            return
+        usage = self.last_usage
+        answered = self.last_model
+        if answered and answered != model:
+            fields["answered_by"] = answered
+        self._oplog.emit(
+            "llm.call",
+            cause="answered",
+            input_tokens=int(usage.get("input", 0)),
+            output_tokens=int(usage.get("output", 0)),
+            cached_tokens=int(usage.get("cached", 0)),
+            **fields,
+        )
+
     def budget_for(self, model: str) -> Budget:
         window, model_max_output = self._limits_for(model)
         ceiling = self._max_output_tokens
@@ -333,10 +365,36 @@ class BudgetedClient:
         """``require_tool_call``: None asks for a tool call whenever tools
         are offered (and the model's server enforces it); False lets the
         model answer in prose, as compaction's notes do."""
+        recorder = self.call_recorder
+        if recorder is not None and not recorder.active:
+            recorder = None
+        if recorder is not None:
+            # The agent is told its calls are recorded, while they are (L7).
+            system = calls.with_notice(system)
         budget = self.budget_for(model)
         factor = self._factors.get(model, 1.0)
-        events = effective_events(list(events))
+        given = list(events)
+        events = effective_events(given)
+        at = calls.utc_now()
+        started = time.monotonic()
+        try:
             fitted, trim = fit_report(events, system, tools, budget, factor)
+        except ContextOverflow as exc:
+            if recorder is not None:
+                self._record(
+                    recorder,
+                    at,
+                    started,
+                    model,
+                    given,
+                    events,
+                    events,
+                    None,
+                    factor,
+                    exchange=None,
+                    error=f"ContextOverflow: {exc}",
+                )
+            raise
         self.last_trim = trim
         if trim is not None:
             # Counted so the benchmark can report how often a model's window
@@ -360,6 +418,9 @@ class BudgetedClient:
                 )
         if require_tool_call is None:
             require_tool_call = bool(tools) and self._enforces_tool_choice(model)
+        before = getattr(self._inner, "last_exchange", None)
+        started = time.monotonic()
+        try:
             produced = self._inner.complete(
                 fitted,
                 tools,
@@ -371,9 +432,139 @@ class BudgetedClient:
                 # ask_human, a delegation with hand_back.
                 require_tool_call=require_tool_call,
             )
+        except BaseException as e:
+            if isinstance(e, Exception):
+                self._log_call(model, started, error=type(e).__name__)
+            if recorder is not None:
+                self._record(
+                    recorder,
+                    at,
+                    started,
+                    model,
+                    given,
+                    events,
+                    fitted,
+                    trim,
+                    factor,
+                    exchange=self._exchange(before),
+                    error=f"{type(e).__name__}: {e}"[:1000],
+                    tools=tools,
+                    system=system,
+                )
+            raise
+        self._log_call(model, started)
+        if recorder is not None:
+            self._record(
+                recorder,
+                at,
+                started,
+                model,
+                given,
+                events,
+                fitted,
+                trim,
+                factor,
+                exchange=self._exchange(before),
+                error=None,
+                tools=tools,
+                system=system,
+            )
         reported = int(self.last_usage.get("input", 0))
         if reported > 0:
             estimated = estimate_tokens(fitted, system, tools)
             observed = reported / max(estimated, 1)
             self._factors[model] = max(factor, observed)
         return produced
+
+    def _exchange(self, before: Any) -> dict[str, Any] | None:
+        """This call's request and response, if the client set them anew."""
+        exchange = getattr(self._inner, "last_exchange", None)
+        return (
+            exchange if isinstance(exchange, dict) and exchange is not before else None
+        )
+
+    def _record(
+        self,
+        recorder: calls.CallRecorder,
+        at: str,
+        started: float,
+        model: str,
+        given: list[StoredEvent],
+        effective: list[StoredEvent],
+        fitted: list[StoredEvent],
+        trim: Trim | None,
+        factor: float,
+        *,
+        exchange: dict[str, Any] | None,
+        error: str | None,
+        tools: list[dict[str, Any]] | None = None,
+        system: str | None = None,
+    ) -> None:
+        answered = None if error is not None else self.last_model
+        recorder.record(
+            at=at,
+            seconds=time.monotonic() - started,
+            model=model,
+            answered_by=answered if answered and answered != model else None,
+            error=error,
+            usage={} if error is not None else dict(self.last_usage),
+            exchange=exchange,
+            provenance=provenance(given, effective, fitted),
+            estimate=(
+                estimate_tokens(fitted, system, tools, factor)
+                if error is None or exchange is not None
+                else None
+            ),
+            factor=factor,
+            trim=None
+            if trim is None
+            else {
+                "step": trim.step,
+                "tokens_before": trim.tokens_before,
+                "tokens_after": trim.tokens_after,
+                "limit": trim.limit,
+                "results_cut": trim.results_cut,
+                "events_dropped": trim.events_dropped,
+            },
+        )
+
+
+def provenance(
+    given: Sequence[StoredEvent],
+    effective: Sequence[StoredEvent],
+    fitted: Sequence[StoredEvent],
+) -> calls.Provenance:
+    """What compaction and fitting did to the events a call was given (L6),
+    for its record: which a compaction replaced, which fitting shortened and
+    by how much, and which it dropped. Events the harness made up for one
+    call (id 0) are in what was sent, and in nothing else."""
+    compactions = [e for e in effective if isinstance(e.event, Compaction)]
+    kept = {e.id for e in effective}
+    compacted: dict[int, int | None] = {}
+    for stored in given:
+        if stored.id == 0 or stored.id in kept or isinstance(stored.event, Compaction):
+            continue
+        compacted[stored.id] = next(
+            (
+                c.id
+                for c in compactions
+                if c.event.replaces[0] <= stored.id <= c.event.replaces[1]
+            ),
+            None,
+        )
+    by_id = {e.id: e for e in effective if e.id != 0}
+    sent_ids = {e.id for e in fitted}
+    shortened: dict[int, int] = {}
+    for stored in fitted:
+        original = by_id.get(stored.id)
+        if (
+            original is not None
+            and isinstance(stored.event, ToolResult)
+            and isinstance(original.event, ToolResult)
+            and stored.event.result != original.event.result
+        ):
+            shortened[stored.id] = len(original.event.result) - len(stored.event.result)
+    dropped = [i for i in by_id if i not in sent_ids]
+    return calls.Provenance(
+        sent=list(fitted), compacted=compacted, shortened=shortened, dropped=dropped
+    )

nisse-core/src/nisse_core/models/llm.py

@@ -188,6 +188,10 @@ class LiteLLMClient:
         # Set even when the call then fails: time spent waiting out a rate
         # limit is the proxy's, not the model's (the benchmark subtracts it).
         self.last_rate_limit_wait_s: float = 0.0
+        # The last call's request body and what came back, for the call
+        # record (L7): a new dict each call, set before it is sent. Never the
+        # headers, which carry the token.
+        self.last_exchange: dict[str, Any] | None = None
 
     def complete(
         self,
@@ -208,10 +212,12 @@ class LiteLLMClient:
         # nothing to check against. A caller that knows the model's limits
         # (the context budget) passes a tighter one.
         body["max_tokens"] = max_tokens or self._max_tokens
+        self.last_exchange = exchange = {"route": "chat", "request": body}
         self.last_rate_limit_wait_s = 0.0  # not the last call's, if this one raises
         response, self.last_rate_limit_wait_s = _post_with_rate_limit_retry(
             self._http, "/chat/completions", body, self._sleep
         )
+        _keep_response(exchange, response)
         if response.status_code != 200:
             _raise_for_upstream(response)
             raise LLMError(
@@ -244,6 +250,10 @@ class LiteLLMClient:
         self.last_usage = {
             "input": int(usage.get("prompt_tokens") or 0),
             "output": int(usage.get("completion_tokens") or 0),
+            # Prompt tokens the server reused from its cache, when it says.
+            "cached": int(
+                (usage.get("prompt_tokens_details") or {}).get("cached_tokens") or 0
+            ),
         }
         out: list[CanonicalEvent] = []
         if message.get("content"):
@@ -317,6 +327,10 @@ class AnthropicPassthroughClient:
         # Set even when the call then fails: time spent waiting out a rate
         # limit is the proxy's, not the model's (the benchmark subtracts it).
         self.last_rate_limit_wait_s: float = 0.0
+        # The last call's request body and what came back, for the call
+        # record (L7): a new dict each call, set before it is sent. Never the
+        # headers, which carry the token.
+        self.last_exchange: dict[str, Any] | None = None
 
     def complete(
         self,
@@ -337,10 +351,12 @@ class AnthropicPassthroughClient:
         )
         if require_tool_call and tools:
             body["tool_choice"] = {"type": "any"}  # Anthropic's name for it
+        self.last_exchange = exchange = {"route": "messages", "request": body}
         self.last_rate_limit_wait_s = 0.0  # not the last call's, if this one raises
         response, self.last_rate_limit_wait_s = _post_with_rate_limit_retry(
             self._http, "/v1/messages", body, self._sleep
         )
+        _keep_response(exchange, response)
         if response.status_code != 200:
             _raise_for_upstream(response)
             raise LLMError(
@@ -371,6 +387,7 @@ class AnthropicPassthroughClient:
         self.last_usage = {
             "input": int(usage.get("input_tokens") or 0),
             "output": int(usage.get("output_tokens") or 0),
+            "cached": int(usage.get("cache_read_input_tokens") or 0),
         }
         out: list[CanonicalEvent] = []
         for block in content:
@@ -439,6 +456,16 @@ def _post_with_rate_limit_retry(
 # Model families we have a native renderer adapter for. L9: delegations take
 # the vendor's passthrough route because a normalising middlebox is lossy
 # exactly where a long-running delegation lives.
+def _keep_response(exchange: dict[str, Any], response: httpx.Response) -> None:
+    """What came back, for the call record: the JSON as the server sent it
+    (reasoning included), or its text when it isn't JSON."""
+    exchange["status"] = response.status_code
+    try:
+        exchange["response"] = response.json()
+    except ValueError:
+        exchange["response"] = {"text": response.text[:20000]}
+
+
 def _response_cost(response: httpx.Response) -> float:
     try:
         return float(response.headers.get("x-litellm-response-cost") or 0.0)

nisse-core/src/nisse_core/models/render.py

@@ -88,13 +88,34 @@ class OpenAIChatRenderer:
         model: str,
         system: str | None = None,
     ) -> dict[str, Any]:
+        messages, _ = self._messages(events, system)
+        body: dict[str, Any] = {"model": model, "messages": messages}
+        if tools:
+            body["tools"] = tools
+        return body
+
+    def message_indexes(
+        self, events: list[StoredEvent], system: str | None = None
+    ) -> list[int | None]:
+        """For each event, the index of the request message ``render`` puts it
+        in, or None where a compaction stands in for it: so a request can be
+        read against the log it was made from (X6). Several events share an
+        index where one turn's text and tool calls fold into one message."""
+        _, where = self._messages(events, system)
+        return [where.get(id(stored)) for stored in events]
+
+    def _messages(
+        self, events: list[StoredEvent], system: str | None
+    ) -> tuple[list[dict[str, Any]], dict[int, int]]:
         messages: list[dict[str, Any]] = []
+        where: dict[int, int] = {}  # id() of an event given -> its message
         if system is not None:
             messages.append({"role": "system", "content": system})
         kept = effective_events(events)
         answered = {e.event.call_id for e in kept if isinstance(e.event, ToolResult)}
         for stored in kept:
             _append_merged(messages, self._message_for(stored.event))
+            where[id(stored)] = len(messages) - 1
             # Providers reject a tool call with no result following it. One
             # can legitimately be missing: a crash between the call and its
             # result (L8), or a turn-ending gate tool. Render a placeholder so
@@ -109,10 +130,7 @@ class OpenAIChatRenderer:
                         "content": "[no result recorded]",
                     }
                 )
-        body: dict[str, Any] = {"model": model, "messages": messages}
+        return messages, where
-        if tools:
-            body["tools"] = tools
-        return body
 
     def _message_for(self, event: object) -> dict[str, Any]:
         match event:

nisse-core/src/nisse_core/state/readonly.py

@@ -0,0 +1,26 @@
+"""Opening an agent's SQLite file without writing to it (X6), for readers
+beside the agent: the status page, the call record's reader.
+
+``mode=ro`` alone still creates the ``-wal`` and ``-shm`` files of a
+database whose writer has closed, which writes to the agent's volume and
+fails on a read-only mount. With no ``-wal`` file there is no writer, so the
+file is opened immutable instead: nothing is created, nothing is locked.
+With one, a writer is (or was) there, and SQLite's own read-only WAL
+reading applies.
+"""
+
+import sqlite3
+from pathlib import Path
+from urllib.parse import quote
+
+
+def connect(path: str | Path, *, timeout: float = 5.0) -> sqlite3.Connection:
+    path = Path(path)
+    if not path.is_file():
+        raise sqlite3.OperationalError(f"unable to open database file: {path}")
+    mode = "ro" if Path(f"{path}-wal").exists() else "ro&immutable=1"
+    conn = sqlite3.connect(
+        f"file:{quote(str(path.resolve()))}?mode={mode}", uri=True, timeout=timeout
+    )
+    conn.row_factory = sqlite3.Row
+    return conn

nisse-core/tests/test_calls.py

@@ -0,0 +1,394 @@
+"""The call record (architecture L7): every model call, as sent and answered,
+with where its request came from, for the operator's study."""
+
+import io
+import json
+import sqlite3
+import zlib
+from pathlib import Path
+from typing import Any
+
+import httpx
+import pytest
+
+from nisse_core.log.canonical import (
+    AssistantText,
+    CanonicalEvent,
+    Compaction,
+    StoredEvent,
+    ToolCall,
+    ToolResult,
+    UserMessage,
+)
+from nisse_core.loop.driver import Driver
+from nisse_core.loop.tools import tool
+from nisse_core.models import calls
+from nisse_core.models.context import BudgetedClient, ContextOverflow
+from nisse_core.models.llm import LiteLLMClient, LLMError
+from nisse_core.oplog import OpLog
+from nisse_core.state.store import StateStore
+
+TOKEN = "sk-secret-litellm-token"
+FINISH = tool("finish", "finish the work", summary="what was done")
+
+
+def stored(events: list[CanonicalEvent], start: int = 1) -> list[StoredEvent]:
+    return [
+        StoredEvent(id=start + i, ts="t", event=e, work_item="w", actor="driver")
+        for i, e in enumerate(events)
+    ]
+
+
+def reply(
+    content: str = "",
+    *,
+    tool_call: str | None = None,
+    reasoning: str = "",
+    timings: dict[str, int] | None = None,
+) -> dict[str, Any]:
+    message: dict[str, Any] = {"role": "assistant", "content": content}
+    if reasoning:
+        message["reasoning_content"] = reasoning
+    if tool_call:
+        message["tool_calls"] = [
+            {
+                "id": "x",
+                "type": "function",
+                "function": {"name": tool_call, "arguments": '{"summary": "done"}'},
+            }
+        ]
+    data: dict[str, Any] = {
+        "model": "local",
+        "choices": [{"message": message, "finish_reason": "stop"}],
+        "usage": {"prompt_tokens": 120, "completion_tokens": 7},
+    }
+    if timings is not None:
+        data["timings"] = timings
+    return data
+
+
+class Server:
+    """A fake LiteLLM: answers each request in turn and keeps what it got."""
+
+    def __init__(self, *answers: tuple[int, dict[str, Any]]) -> None:
+        self.answers = list(answers)
+        self.bodies: list[dict[str, Any]] = []
+
+    def __call__(self, request: httpx.Request) -> httpx.Response:
+        self.bodies.append(json.loads(request.content))
+        status, data = self.answers.pop(0) if self.answers else (200, reply("ok"))
+        return httpx.Response(status, json=data)
+
+
+def budgeted(
+    server: Server, recorder: calls.CallRecorder | None, window: int = 32768
+) -> BudgetedClient:
+    inner = LiteLLMClient(
+        "https://litellm.test", TOKEN, transport=httpx.MockTransport(server)
+    )
+    return BudgetedClient(inner, lambda m: (window, 1024), call_recorder=recorder)
+
+
+@pytest.fixture
+def recorder(tmp_path: Path) -> calls.CallRecorder:
+    return calls.CallRecorder(tmp_path / "state.calls.db")
+
+
+def read(recorder: calls.CallRecorder) -> calls.CallReader:
+    return calls.CallReader(recorder.path)
+
+
+# --- what each call was --------------------------------------------------------
+
+
+def test_a_call_is_recorded_exactly_as_sent_with_its_reasoning(
+    recorder: calls.CallRecorder,
+) -> None:
+    server = Server(
+        (
+            200,
+            reply(
+                "Finishing.",
+                tool_call="finish",
+                reasoning="The tests pass, so the work is done.",
+                timings={"cache_n": 90, "prompt_n": 30},
+            ),
+        )
+    )
+    client = budgeted(server, recorder)
+    client.complete(
+        stored([UserMessage(text="go", source="t")]), [FINISH], "local", system="sys"
+    )
+
+    reader = read(recorder)
+    [call] = reader.calls()
+    # The request rebuilt from the record is the body the server got.
+    assert reader.request(call) == server.bodies[0]
+    response = reader.response(call)
+    assert (
+        response["choices"][0]["message"]["reasoning_content"]
+        == "The tests pass, so the work is done."
+    )
+    assert call["outcome"] == "answered"
+    assert (call["tokens_in"], call["tokens_out"]) == (120, 7)
+    assert (call["cache_n"], call["prompt_n"]) == (90, 30)
+    assert call["route"] == "chat" and call["status"] == 200
+
+
+def test_the_token_is_nowhere_in_the_record(recorder: calls.CallRecorder) -> None:
+    client = budgeted(Server(), recorder)
+    client.complete(stored([UserMessage(text="go", source="t")]), None, "local")
+    recorder.close()
+
+    raw = recorder.path.read_bytes()
+    conn = sqlite3.connect(recorder.path)
+    blobs = b"".join(
+        zlib.decompress(d) for (d,) in conn.execute("SELECT data FROM blobs")
+    )
+    rows = json.dumps(conn.execute("SELECT * FROM calls").fetchall()).encode()
+    conn.close()
+    assert TOKEN.encode() not in raw + blobs + rows
+
+
+def test_a_failed_call_is_recorded_with_its_error(recorder: calls.CallRecorder) -> None:
+    server = Server((400, {"error": {"message": "bad request: no such model"}}))
+    client = budgeted(server, recorder)
+    with pytest.raises(LLMError):
+        client.complete(stored([UserMessage(text="go", source="t")]), None, "local")
+
+    reader = read(recorder)
+    [call] = reader.calls()
+    assert call["outcome"] == "failed"
+    assert "LLMError" in call["error"]
+    assert call["status"] == 400
+    assert reader.request(call) == server.bodies[0]
+    assert reader.response(call) == {"error": {"message": "bad request: no such model"}}
+
+
+def test_a_request_too_big_to_send_is_recorded_without_one(
+    recorder: calls.CallRecorder,
+) -> None:
+    server = Server()
+    client = budgeted(server, recorder, window=4096)
+    with pytest.raises(ContextOverflow):
+        client.complete(
+            stored([UserMessage(text="go", source="t")]),
+            None,
+            "local",
+            system="s" * 20_000,
+        )
+
+    [call] = read(recorder).calls()
+    assert server.bodies == []
+    assert call["outcome"] == "failed" and "ContextOverflow" in call["error"]
+    assert call["request"] is None
+
+
+def test_a_growing_conversation_is_stored_once(recorder: calls.CallRecorder) -> None:
+    client = budgeted(Server(), recorder)
+    events: list[CanonicalEvent] = [
+        UserMessage(text="message 0 " + "x" * 2000, source="t")
+    ]
+    for n in range(1, 6):
+        client.complete(stored(events), None, "local")
+        events.append(AssistantText(text=f"reply {n} " + "y" * 2000, model="local"))
+        events.append(UserMessage(text=f"message {n} " + "z" * 2000, source="t"))
+
+    conn = sqlite3.connect(recorder.path)
+    stored_chars = sum(
+        len(zlib.decompress(d)) for (d,) in conn.execute("SELECT data FROM blobs")
+    )
+    conn.close()
+    # Five calls resend 1 + 3 + 5 + 7 + 9 messages of about 2 kB; stored
+    # once each, that's 9 messages (as sent, and as events), not 25.
+    assert stored_chars < 2 * 9 * 2100 + 20_000
+
+
+# --- where each request came from ---------------------------------------------
+
+
+def test_compaction_shortening_and_dropping_are_recorded(
+    recorder: calls.CallRecorder,
+) -> None:
+    long = "line\n" * 2000
+    events = stored(
+        [
+            UserMessage(text="start", source="t"),  # 1
+            AssistantText(text="old thinking", model="m"),  # 2, compacted
+            AssistantText(text="more old thinking", model="m"),  # 3, compacted
+            Compaction(summary="notes so far", model="m", replaces=[2, 3]),  # 4
+        ]
+    )
+    for n in range(8):  # turns 5.. : a command and its long output each
+        events += stored(
+            [
+                ToolCall(
+                    call_id=f"c{n}", tool="run_command", arguments={"command": "make"}
+                ),
+                ToolResult(call_id=f"c{n}", result=long, success=True),
+            ],
+            start=len(events) + 1,
+        )
+    client = BudgetedClient(
+        LiteLLMClient(
+            "https://litellm.test", TOKEN, transport=httpx.MockTransport(Server())
+        ),
+        lambda m: (12_000, 1024),
+        keep_recent_turns=2,
+        call_recorder=recorder,
+    )
+    client.complete(events, None, "local")
+
+    [call] = read(recorder).calls()
+    assert call["compacted"] == {"2": 4, "3": 4}
+    assert call["shortened"], "older results were cut to fit"
+    assert all(cut > 0 for cut in call["shortened"].values())
+    sent_ids = [entry[0] for entry in call["sent"]]
+    assert 4 in sent_ids and 2 not in sent_ids
+    assert set(map(int, call["shortened"])) <= set(sent_ids)
+    assert not set(call["dropped"]) & set(sent_ids)
+
+
+def test_runs_nest_and_label_their_calls(recorder: calls.CallRecorder) -> None:
+    client = budgeted(Server(), recorder)
+    events = stored([UserMessage(text="go", source="t")])
+    with calls.run(recorder, work_item="w", role="driver") as outer:
+        client.complete(events, None, "local")
+        with calls.purpose("consult", role="expert"):
+            client.complete(events, None, "local")
+        with calls.run(
+            recorder, work_item="w", role="helper", kind="delegation"
+        ) as inner:
+            client.complete(events, None, "local")
+            inner.end("handback", "done")
+        outer.end("wait", "")
+
+    reader = read(recorder)
+    runs = {r["kind"]: r for r in reader.runs()}
+    assert runs["delegation"]["parent"] == runs["run"]["id"]
+    assert runs["run"]["outcome"] == "wait" and runs["run"]["ended_at"]
+    assert runs["delegation"]["outcome"] == "handback"
+    turn, consult, helped = reader.calls()
+    assert (turn["run"], turn["role"], turn["purpose"]) == (
+        runs["run"]["id"],
+        "driver",
+        None,
+    )
+    assert (consult["role"], consult["purpose"]) == ("expert", "consult")
+    assert (helped["run"], helped["role"]) == (runs["delegation"]["id"], "helper")
+    assert {c["work_item"] for c in (turn, consult, helped)} == {"w"}
+
+
+def test_a_driver_run_is_recorded_with_how_it_ended(
+    tmp_path: Path, recorder: calls.CallRecorder
+) -> None:
+    store = StateStore(tmp_path / "state.db", oplog=OpLog("t", io.StringIO()))
+    store.open_work_item("w", title="t", position="RUNNING", cause="test")
+    store.transcript("w", "operator").append(UserMessage(text="go", source="t"))
+    client = budgeted(Server((200, reply(tool_call="finish"))), recorder)
+
+    outcome = Driver(client, "local").run(
+        store.transcript("w", "driver"),
+        system="sys",
+        tools=[FINISH],
+        waiting=("finish",),
+        workspace=None,
+    )
+
+    reader = read(recorder)
+    [run] = reader.runs()
+    assert outcome.kind == "wait"
+    assert (run["work_item"], run["role"], run["outcome"]) == ("w", "driver", "wait")
+    [call] = reader.calls(run=run["id"])
+    # Each event sent is the log's, by id, so the page can read it against
+    # the state store.
+    assert [entry[:3] for entry in call["sent"]] == [[1, "operator", "user_message"]]
+
+
+# --- the agent is told, and nothing depends on the record ----------------------
+
+
+def test_the_agent_is_told_exactly_while_it_is_recorded(tmp_path: Path) -> None:
+    on, off = Server(), Server()
+    budgeted(on, calls.CallRecorder(tmp_path / "a.calls.db")).complete(
+        stored([UserMessage(text="go", source="t")]), None, "local", system="sys"
+    )
+    budgeted(off, None).complete(
+        stored([UserMessage(text="go", source="t")]), None, "local", system="sys"
+    )
+    assert on.bodies[0]["messages"][0]["content"] == f"sys\n\n{calls.NOTICE}"
+    assert off.bodies[0]["messages"][0]["content"] == "sys"
+
+
+def test_a_recorder_that_fails_never_fails_the_call(tmp_path: Path) -> None:
+    out = io.StringIO()
+    recorder = calls.CallRecorder(tmp_path / "state.calls.db", oplog=OpLog("t", out))
+    recorder._conn.close()  # the disk went away, say
+    client = budgeted(Server(), recorder)
+
+    first = client.complete(stored([UserMessage(text="go", source="t")]), None, "local")
+    second = client.complete(
+        stored([UserMessage(text="go", source="t")]), None, "local"
+    )
+
+    assert [e.text for e in first + second] == ["ok", "ok"]  # type: ignore[union-attr]
+    assert not recorder.active
+    logged = [json.loads(line) for line in out.getvalue().splitlines()]
+    assert [e["event"] for e in logged].count("calls.record_failed") == 1
+
+
+def test_the_record_is_new_each_start(tmp_path: Path) -> None:
+    path = tmp_path / "state.calls.db"
+    path.write_bytes(b"an older layout, or not a database at all")
+    Path(f"{path}-wal").write_bytes(b"stale")
+    recorder = calls.CallRecorder(path)
+    budgeted(Server(), recorder).complete(
+        stored([UserMessage(text="go", source="t")]), None, "local"
+    )
+    assert recorder.active
+    assert len(read(recorder).calls()) == 1
+
+    again = calls.CallRecorder(path)
+    assert again.active and read(again).calls() == []
+
+
+def test_off_means_no_file(tmp_path: Path) -> None:
+    assert calls.recorder_for(tmp_path / "state.db", False) is None
+    assert not list(tmp_path.iterdir())
+    recorder = calls.recorder_for(tmp_path / "state.db", True)
+    assert recorder is not None and recorder.path == tmp_path / "state.calls.db"
+
+
+def test_a_reader_refuses_a_layout_it_does_not_know(
+    recorder: calls.CallRecorder,
+) -> None:
+    recorder._conn.execute("UPDATE meta SET value = '99' WHERE key = 'layout_version'")
+    with pytest.raises(calls.UnknownLayout, match="layout 99"):
+        read(recorder)
+
+
+def test_the_reader_never_writes(recorder: calls.CallRecorder) -> None:
+    budgeted(Server(), recorder).complete(
+        stored([UserMessage(text="go", source="t")]), None, "local"
+    )
+    reader = read(recorder)
+    with pytest.raises(sqlite3.OperationalError, match="readonly"):
+        reader._conn.execute("DELETE FROM calls")
+
+
+def test_the_page_reads_one_items_calls_and_when_recording_began(
+    recorder: calls.CallRecorder,
+) -> None:
+    client = budgeted(Server(), recorder)
+    with calls.run(recorder, work_item="w", role="driver"):
+        client.complete(stored([UserMessage(text="go", source="t")]), None, "local")
+    with calls.run(recorder, work_item=None, role="classifier"):
+        client.complete(stored([UserMessage(text="hi", source="t")]), None, "local")
+    reader = read(recorder)
+    [mine] = reader.calls_for("w")
+    [agent_level] = reader.calls_for(None)
+    assert (mine["work_item"], agent_level["work_item"]) == ("w", None)
+    assert reader.call(agent_level["id"])["role"] == "classifier"
+    assert reader.call(999) is None
+    assert reader.started_at is not None
+    assert reader.started_at <= mine["at"]

nisse-core/tests/test_circles.py

@@ -0,0 +1,73 @@
+"""Runs going in circles (L2, X6), judged from the turns alone."""
+
+from nisse_core.loop.circles import Turn, find_circles
+
+NUDGE = "Your last reply was prose. Every reply must be a tool call."
+
+
+def comment(n: int) -> Turn:
+    return Turn(
+        text="",
+        calls=(("post_comment", f'{{"body": "Duplicate, please disregard. ({n})"}}'),),
+    )
+
+
+def test_near_identical_replies_in_a_row_are_a_circle() -> None:
+    # The Flash-Next review loop of 2026-10-24: the same comment posted over
+    # and over, differing only in a counter.
+    turns = [Turn(calls=(("read_file", '{"path": "a.py"}'),))]
+    turns += [comment(n) for n in range(6)]
+    turns += [Turn(calls=(("finish", "{}"),))]
+    [circle] = find_circles(turns)
+    assert circle.kind == "repeated reply"
+    assert circle.turns == (1, 2, 3, 4, 5, 6)
+
+
+def test_work_that_moves_on_is_no_circle() -> None:
+    turns = [
+        Turn(calls=(("read_file", '{"path": "a.py"}'),)),
+        Turn(calls=(("run_command", '{"command": "pytest -q"}'),)),
+        Turn(calls=(("edit_file", '{"path": "a.py", "old": "x", "new": "y"}'),)),
+        Turn(calls=(("run_command", '{"command": "pytest -q"}'),)),
+        Turn(text="Done.", calls=(("finish", "{}"),)),
+    ]
+    assert find_circles(turns) == []
+
+
+def test_two_alike_is_not_yet_a_circle() -> None:
+    assert find_circles([comment(1), comment(2), Turn(text="done")]) == []
+
+
+def test_one_correction_given_again_and_again_is_a_circle() -> None:
+    # Invented tools met with the prose reminder turn after turn, the replies
+    # themselves all different.
+    replies = [
+        "I'll run the linter first: <tool_call>lint_fix</tool_call>",
+        "<call>read_file src/review.py</call>",
+        "Installing the dependencies with install(requirements.txt) now.",
+        "Let me use the skill tool to summarise the diff for the review.",
+    ]
+    turns = [Turn(text=r, told=(NUDGE,) if i else ()) for i, r in enumerate(replies)]
+    [circle] = find_circles(turns)
+    assert circle.kind == "repeated correction"
+    assert circle.turns == (1, 2, 3)
+    assert NUDGE[:40] in circle.detail
+
+
+def test_apologies_over_and_over_are_a_circle() -> None:
+    turns = [
+        Turn(text="Sorry, I made an error reading the file."),
+        Turn(calls=(("read_file", '{"path": "b.py"}'),)),
+        Turn(text="My apologies, that was the wrong path."),
+        Turn(calls=(("list_files", "{}"),)),
+        Turn(text="Please disregard my previous comment."),
+    ]
+    [circle] = find_circles(turns)
+    assert circle.kind == "repeated apology"
+    assert circle.turns == (0, 2, 4)
+
+
+def test_the_limits_are_tuning() -> None:
+    turns = [comment(1), comment(2)]
+    assert [c.kind for c in find_circles(turns, repeats=2)] == ["repeated reply"]
+    assert find_circles([comment(1), comment(22), comment(333)], similar=1.0) == []

nisse-core/tests/test_context.py

@@ -1,6 +1,7 @@
 """The context budget (architecture L6)."""
 
 import io
+import json
 from pathlib import Path
 from typing import Any
 
@@ -25,6 +26,7 @@ from nisse_core.models.context import (
     fit,
     head_and_tail,
 )
+from nisse_core.models.llm import LLMError
 from nisse_core.oplog import OpLog
 from nisse_core.state.store import StateStore
 
@@ -190,7 +192,7 @@ def test_reported_usage_only_ever_raises_the_estimate() -> None:
     assert under_then_over._factors["m"] == 2.0  # never loosened
 
 
-def test_a_request_that_fits_is_sent_whole_and_nothing_is_logged() -> None:
+def test_a_request_that_fits_is_sent_whole_and_no_cut_is_logged() -> None:
     stream = io.StringIO()
     client = BudgetedClient(
         RecordingClient(), lambda m: (100_000, None), oplog=OpLog("t", stream)
@@ -198,7 +200,49 @@ def test_a_request_that_fits_is_sent_whole_and_nothing_is_logged() -> None:
     events = transcript(3, 100)
     client.complete(events, None, "m")
     assert client.last_trim is None
-    assert stream.getvalue() == ""
+    assert "context.trimmed" not in stream.getvalue()
+
+
+def logged(stream: io.StringIO, event: str) -> list[dict[str, Any]]:
+    records = [json.loads(line) for line in stream.getvalue().splitlines()]
+    return [r for r in records if r["event"] == event]
+
+
+def test_every_call_logs_its_time_and_tokens() -> None:
+    # A slow turn should show whether reading or writing took the time (#174).
+    stream = io.StringIO()
+    inner = RecordingClient(reported_input=900)
+    inner.last_usage["cached"] = 800
+    inner.last_model = "fallback-model"
+    client = BudgetedClient(inner, lambda m: (100_000, None), oplog=OpLog("t", stream))
+    client.complete(transcript(1, 10), None, "m")
+    [call] = logged(stream, "llm.call")
+    assert call["cause"] == "answered"
+    assert call["model"] == "m"
+    assert call["answered_by"] == "fallback-model"
+    assert (call["input_tokens"], call["output_tokens"], call["cached_tokens"]) == (
+        900,
+        5,
+        800,
+    )
+    assert isinstance(call["seconds"], float)
+
+
+def test_a_failed_call_logs_how_long_it_ran_and_still_raises() -> None:
+    class TimesOut(RecordingClient):
+        def complete(self, *args, **kwargs):
+            raise LLMError("LLM request returned 408: timed out")
+
+    stream = io.StringIO()
+    client = BudgetedClient(
+        TimesOut(), lambda m: (100_000, None), oplog=OpLog("t", stream)
+    )
+    with pytest.raises(LLMError):
+        client.complete(transcript(1, 10), None, "m")
+    [call] = logged(stream, "llm.call")
+    assert call["cause"] == "failed"
+    assert call["error"] == "LLMError"
+    assert "input_tokens" not in call
 
 
 def test_a_cut_is_recorded_and_logged() -> None:

nisse-core/tests/test_llm.py

@@ -484,6 +484,48 @@ def test_the_answering_model_is_recorded() -> None:
     assert client.last_model == "gpt-test-1"
 
 
+def test_usage_includes_what_the_server_reused_from_its_cache() -> None:
+    client = make_client(
+        lambda request: httpx.Response(
+            200,
+            json={
+                "model": "qwen",
+                "choices": [{"message": {"role": "assistant", "content": "hi"}}],
+                "usage": {
+                    "prompt_tokens": 900,
+                    "completion_tokens": 40,
+                    "prompt_tokens_details": {"cached_tokens": 800},
+                },
+            },
+        )
+    )
+    client.complete(EVENTS, tools=None, model="qwen")
+    assert client.last_usage == {"input": 900, "output": 40, "cached": 800}
+
+    passthrough = AnthropicPassthroughClient(
+        "https://litellm.test",
+        "tok",
+        transport=httpx.MockTransport(
+            lambda request: httpx.Response(
+                200,
+                json={
+                    "model": "claude-opus-5-5",
+                    "stop_reason": "end_turn",
+                    "content": [{"type": "text", "text": "hi"}],
+                    "usage": {
+                        "input_tokens": 50,
+                        "output_tokens": 7,
+                        "cache_read_input_tokens": 30,
+                    },
+                },
+            )
+        ),
+        sleep=lambda _s: None,
+    )
+    passthrough.complete(EVENTS, tools=None, model="claude-opus-5-5")
+    assert passthrough.last_usage == {"input": 50, "output": 7, "cached": 30}
+
+
 # --- outages delay, never fail (L5) --------------------------------------------
 
 

nisse-core/tests/test_readonly.py

@@ -0,0 +1,43 @@
+"""Readers beside an agent open its files without writing to them (X6)."""
+
+import sqlite3
+from pathlib import Path
+
+import pytest
+
+from nisse_core.state import readonly
+
+
+def wal_db(path: Path) -> sqlite3.Connection:
+    conn = sqlite3.connect(path, isolation_level=None)
+    conn.execute("PRAGMA journal_mode=WAL")
+    conn.execute("CREATE TABLE t (v TEXT)")
+    conn.execute("INSERT INTO t VALUES ('one')")
+    return conn
+
+
+def test_a_closed_database_is_read_without_creating_any_file(tmp_path: Path) -> None:
+    wal_db(tmp_path / "a.db").close()
+    assert sorted(p.name for p in tmp_path.iterdir()) == ["a.db"]
+    conn = readonly.connect(tmp_path / "a.db")
+    assert conn.execute("SELECT v FROM t").fetchall()[0]["v"] == "one"
+    conn.close()
+    assert sorted(p.name for p in tmp_path.iterdir()) == ["a.db"]
+
+
+def test_a_live_database_is_read_as_its_writer_commits(tmp_path: Path) -> None:
+    writer = wal_db(tmp_path / "a.db")
+    conn = readonly.connect(tmp_path / "a.db")
+    writer.execute("INSERT INTO t VALUES ('two')")
+    assert [r["v"] for r in conn.execute("SELECT v FROM t")] == ["one", "two"]
+    with pytest.raises(sqlite3.OperationalError):
+        conn.execute("INSERT INTO t VALUES ('three')")
+    conn.close()
+    writer.execute("INSERT INTO t VALUES ('four')")  # no lock left behind
+    writer.close()
+
+
+def test_a_missing_file_is_an_error_not_a_new_database(tmp_path: Path) -> None:
+    with pytest.raises(sqlite3.OperationalError):
+        readonly.connect(tmp_path / "none.db")
+    assert not (tmp_path / "none.db").exists()

nisse-core/tests/test_render.py

@@ -163,3 +163,47 @@ def test_roles_never_repeat_for_strict_templates() -> None:
     roles = _roles(OpenAIChatRenderer().render(events, tools=None, model="q"))
     for first, second in pairwise(roles):
         assert not (first == second and first in ("user", "assistant")), roles
+
+
+def test_each_event_maps_to_the_message_render_puts_it_in() -> None:
+    # A turn's text and tool call fold into one message; a call with no
+    # result gets a placeholder that came from no event; the system prompt
+    # is message 0.
+    events = stored(
+        [
+            UserMessage(text="go", source="m:1"),
+            AssistantText(text="Looking.", model="m"),
+            ToolCall(call_id="c1", tool="read_file", arguments={"path": "a"}),
+            ToolResult(call_id="c1", result="text", success=True),
+            ToolCall(call_id="c2", tool="finish", arguments={}),
+            UserMessage(text="and then?", source="m:2"),
+        ]
+    )
+    renderer = OpenAIChatRenderer()
+    body = renderer.render(events, tools=None, model="m", system="sys")
+    indexes = renderer.message_indexes(events, system="sys")
+    assert indexes == [1, 2, 2, 3, 4, 6]
+    assert body["messages"][5]["content"] == "[no result recorded]"
+    for event, index in zip(events, indexes, strict=True):
+        message = body["messages"][index]
+        if isinstance(event.event, ToolCall):
+            ids = [c["id"] for c in message["tool_calls"]]
+            assert event.event.call_id in ids
+        elif isinstance(event.event, (UserMessage, AssistantText)):
+            assert event.event.text in message["content"]
+    assert renderer.message_indexes(events) == [i - 1 for i in indexes]
+
+
+def test_events_a_compaction_replaced_map_to_no_message() -> None:
+    events = stored(
+        [
+            UserMessage(text="one", source="m:1"),
+            AssistantText(text="two", model="m"),
+            UserMessage(text="three", source="m:3"),
+            Compaction(summary="one and two", model="m", replaces=[1, 2]),
+        ]
+    )
+    # The summary takes the place of what it replaced, and the user message
+    # after it folds into the same user message.
+    indexes = OpenAIChatRenderer().message_indexes(events)
+    assert indexes == [None, None, 0, 0]

nisse-dev/src/nisse_dev/bench/runner.py

@@ -1,11 +1,13 @@
 """Running one task once with one driver model, and recording it."""
 
+import contextlib
 import io
 import shlex
 import subprocess
 import tempfile
 import time
 import uuid
+from collections.abc import Iterator
 from dataclasses import asdict, dataclass, field
 from datetime import UTC, datetime
 from pathlib import Path
@@ -21,6 +23,7 @@ from nisse_core.log.canonical import (
     UserMessage,
 )
 from nisse_core.loop.driver import Driver, RunOutcome
+from nisse_core.models import calls
 from nisse_core.models.catalog import ModelFacts
 from nisse_core.models.compact import Compactor
 from nisse_core.oplog import OpLog
@@ -184,6 +187,37 @@ def _count(events: list[StoredEvent]) -> tuple[int, int]:
     return failed, invented
 
 
+@contextlib.contextmanager
+def _run_dir(keep: Path | None, workdir: Path | None, name: str) -> Iterator[Path]:
+    """Where a run's state store and call record go: kept under ``keep``
+    for the status page (X6), or a temporary directory."""
+    if keep is not None:
+        root = keep / f"{name}-{uuid.uuid4().hex[:8]}"
+        root.mkdir(parents=True)
+        yield root
+        return
+    with tempfile.TemporaryDirectory(dir=workdir) as tmp:
+        yield Path(tmp)
+
+
+@contextlib.contextmanager
+def _recording(client: Any, root: Path) -> Iterator[None]:
+    """The run's calls recorded beside its own state store (L7), as the
+    agent records its own, so the run measures what the agent would do."""
+    recorder = calls.CallRecorder(calls.path_for(root / "state.db"))
+    had = hasattr(client, "call_recorder")
+    previous = getattr(client, "call_recorder", None)
+    client.call_recorder = recorder
+    try:
+        yield
+    finally:
+        if had:
+            client.call_recorder = previous
+        else:
+            del client.call_recorder
+        recorder.close()
+
+
 def run_task(
     task: Task,
     facts: ModelFacts,
@@ -194,6 +228,7 @@ def run_task(
     note: str = "",
     commit: str = "",
     workdir: Path | None = None,
+    keep: Path | None = None,
 ) -> RunRecord:
     """Run one task once: seed a workspace, hand the driver an agreed item
     whose restatement is the task's plan, then judge the result with the
@@ -202,8 +237,7 @@ def run_task(
     It is the loop's own driver, system prompt and tools, so what is measured
     is what the agent would do, without the harness around it: the milestone
     is started but no branch is cut, and finishing it ends the run."""
-    with tempfile.TemporaryDirectory(dir=workdir) as tmp:
+    with _run_dir(keep, workdir, task.name) as root, _recording(client, root):
-        root = Path(tmp)
         # The workspace is on the build VM, like the agent's own (L13).
         workspace = Workspace(
             host,

nisse-dev/src/nisse_dev/bench/tasks.py

@@ -5,7 +5,8 @@ Each task is a directory under ``tasks/``:
 - ``task.yaml``: ``title``, ``plan`` (the approved milestone plan, written the
   way the driver restates them), and ``check`` (a shell command run
   in the workspace afterwards).
-- ``seed/``: the project the driver starts from.
+- ``seed/``: the project the driver starts from, committed as a git
+  repository's first commit (``GIT_SEED``).
 - ``hidden/``: files the check needs, copied in only after the run, into
   ``.bench_check/``. The driver never sees them.
 - ``solution/``: a reference solution, overlaid on the seed by the tests to
@@ -28,6 +29,18 @@ if TYPE_CHECKING:
 TASKS_DIR = Path(__file__).parent / "tasks"
 CHECK_DIR = ".bench_check"
 
+# The seed is committed as a git repository's first commit, as the agent's
+# own workspace is a clone: a model that starts with `git log` or `git
+# status` shouldn't fail where it would succeed in production.
+GIT_SEED = (
+    "git init -q -b main && git add -A && "
+    "git -c user.name=nisse-bench -c user.email=bench@nisse.invalid "
+    "commit -q -m seed"
+)
+# How a workspace is set up, part of every task's hash: runs from before a
+# change here are not comparable with runs after it.
+SEED_SETUP = f"seed committed: {GIT_SEED}"
+
 
 @dataclass(frozen=True)
 class Task:
@@ -42,7 +55,7 @@ class Task:
         """What the task is, so a changed task is never compared with runs of
         its earlier version. Covers everything the model or the check sees;
         not the reference solution."""
-        digest = hashlib.sha256()
+        digest = hashlib.sha256(SEED_SETUP.encode())
         for part in ("task.yaml", "seed", "hidden"):
             root = self.path / part
             files = [root] if root.is_file() else sorted(root.rglob("*"))
@@ -54,6 +67,7 @@ class Task:
 
     def seed_into(self, workspace: Path) -> None:
         shutil.copytree(self.path / "seed", workspace, dirs_exist_ok=True)
+        subprocess.run(GIT_SEED, shell=True, cwd=workspace, check=True)
 
     def apply_solution(self, workspace: Path) -> None:
         shutil.copytree(self.path / "solution", workspace, dirs_exist_ok=True)
@@ -84,6 +98,9 @@ class Task:
 
     def seed_workspace(self, workspace: "Workspace") -> None:
         workspace.upload_tree(self.path / "seed")
+        result = workspace.host.execute(GIT_SEED, cwd=str(workspace.root), timeout_s=60)
+        if result.exit_code != 0:
+            raise RuntimeError(f"committing the seed failed: {result.stderr.strip()}")
 
     def check_workspace(
         self, workspace: "Workspace", timeout_s: int = 300

nisse-dev/src/nisse_dev/config.py

@@ -63,6 +63,8 @@ OPTIONAL_KEYS = (
     "roles.classifier",
     "llm.max_output_tokens",
     "llm.request_timeout_s",
+    # Record every model call for the operator's study (L7); on unless false.
+    "call_record",
 )
 # Settings the old loop had (until M2.8), and what to do instead.
 RETIRED_KEYS = {
@@ -444,6 +446,7 @@ class AgentConfig:
     profiles: Mapping[str, Profile] = field(default_factory=dict)
     max_output_tokens: int = DEFAULT_MAX_OUTPUT_TOKENS
     request_timeout_s: float = DEFAULT_REQUEST_TIMEOUT_S
+    call_record: bool = True  # every model call recorded for the operator (L7)
     tuning: Tuning = field(default_factory=Tuning)
     vault: VaultConfig | None = None
     config_file: Path | None = None
@@ -521,6 +524,9 @@ class AgentConfig:
             errors.append("unset or empty — " + ", ".join(missing))
 
         max_output, request_timeout = llm_numbers(values, errors)
+        record = values.get("call_record", True)
+        if not isinstance(record, bool):
+            errors.append("call_record: true or false")
         if errors:
             raise ConfigError("cannot start: " + "; ".join(errors))
 
@@ -548,6 +554,7 @@ class AgentConfig:
             profiles=profiles,
             max_output_tokens=max_output,
             request_timeout_s=request_timeout,
+            call_record=record,
             tuning=tuning,
             vault=vault,
             config_file=config_file,

nisse-dev/src/nisse_dev/delegation.py

@@ -38,6 +38,7 @@ from nisse_core.log.canonical import (
     ToolCall,
     ToolResult,
 )
+from nisse_core.models import calls
 from nisse_core.models.llm import LLMClient, LLMError, UpstreamUnavailable
 from nisse_core.state.cancel import Cancel, skip_calls
 from nisse_core.state.reconcile import Reconciler
@@ -333,6 +334,21 @@ class Delegation:
 
     def _loop(
         self, transcript: Transcript, brief: str, branch: str, started_at: float
+    ) -> DelegationResult:
+        """The delegation's turns, recorded as a run of its own, inside the
+        driver's (L7)."""
+        with calls.run(
+            calls.recorder_of(self._client),
+            work_item=transcript.work_item,
+            role=transcript.actor,
+            kind="delegation",
+        ) as recorded:
+            result = self._turns(transcript, brief, branch, started_at)
+            recorded.end(result.status, result.note)
+            return result
+
+    def _turns(
+        self, transcript: Transcript, brief: str, branch: str, started_at: float
     ) -> DelegationResult:
         system = (
             f"{SYSTEM_PROMPT.format(reader=self._reader)}\n\n"

nisse-dev/src/nisse_dev/loop/build.py

@@ -14,6 +14,7 @@ from nisse_core.gitea import GiteaClient
 from nisse_core.knowledge.memory import Memory
 from nisse_core.knowledge.vault import Vault
 from nisse_core.loop.driver import Driver
+from nisse_core.models import calls
 from nisse_core.models.catalog import ModelCatalog, select_client
 from nisse_core.models.compact import Compactor
 from nisse_core.models.context import BudgetedClient
@@ -126,6 +127,9 @@ def make_llm_clients(
         assert facts.max_input_tokens is not None  # require_limits checked
         return facts.max_input_tokens, facts.max_output_tokens
 
+    # Both routes record into one file (L7).
+    recorder = calls.recorder_for(config.state_db, config.call_record, oplog)
+
     def budgeted(client: object) -> BudgetedClient:
         # Every request, on either route, is fitted to its model's window.
         return BudgetedClient(
@@ -138,6 +142,7 @@ def make_llm_clients(
                 catalog.facts(m).supports_tool_choice is True
             ),
             oplog=oplog,  # a cut that fitting has to make is logged
+            call_recorder=recorder,
         )
 
     normalized = budgeted(

nisse-dev/src/nisse_dev/loop/classifier.py

@@ -18,6 +18,7 @@ from typing import Any
 
 from nisse_core.authority.actions import CONTAINED, DANGEROUS, Action, Verdict
 from nisse_core.log.canonical import StoredEvent, ToolCall, UserMessage
+from nisse_core.models.calls import purpose
 from nisse_core.models.llm import LLMClient, LLMError
 
 SAFE = "safe"
@@ -120,6 +121,7 @@ class ActionClassifier:
         shown = f"{model} ({resolved})" if resolved and resolved != model else model
         prompt = self.input_for(action, scope, workspace)
         try:
+            with purpose("classification", role="classifier"):
                 produced = self._client.complete(
                     [
                         StoredEvent(

nisse-dev/src/nisse_dev/loop/reader.py

@@ -11,6 +11,7 @@ The driver's model reads for now; the classifier role takes over in M2.6.
 from typing import Any
 
 from nisse_core.log.canonical import StoredEvent, ToolCall, UserMessage
+from nisse_core.models.calls import purpose
 from nisse_core.models.llm import LLMClient, LLMError
 
 
@@ -65,6 +66,7 @@ class GoAheadReader:
             return False
         prompt = f"The proposal:\n\n{proposal}\n\nThe operator's reply:\n\n{reply}"
         try:
+            with purpose("go-ahead reading", role="classifier"):
                 produced = self._client.complete(
                     [
                         StoredEvent(

nisse-dev/tests/test_bench.py

@@ -151,6 +151,33 @@ def test_a_changed_task_gets_a_new_hash(tmp_path: Path) -> None:
     assert copy.content_hash != task.content_hash
 
 
+def test_the_seed_is_a_git_repository_with_one_clean_commit(tmp_path: Path) -> None:
+    # The agent works in a clone; a model that starts with `git log` must not
+    # fail here where it would succeed in production.
+    import subprocess
+
+    [task] = load_tasks(["write-function"])
+    task.seed_into(tmp_path)
+
+    def git(*args: str) -> str:
+        return subprocess.run(
+            ["git", *args], cwd=tmp_path, capture_output=True, text=True, check=True
+        ).stdout
+
+    assert git("log", "--oneline").count("\n") == 1
+    assert git("status", "--short") == ""
+
+
+def test_how_the_seed_is_set_up_is_part_of_the_hash(monkeypatch) -> None:
+    # Runs from before the seed was committed are not comparable.
+    import nisse_dev.bench.tasks as tasks_module
+
+    [task] = load_tasks(["write-function"])
+    before = task.content_hash
+    monkeypatch.setattr(tasks_module, "SEED_SETUP", "seed copied")
+    assert task.content_hash != before
+
+
 def test_an_unknown_task_is_refused() -> None:
     with pytest.raises(ValueError, match="unknown task"):
         load_tasks(["nope"])
@@ -211,6 +238,17 @@ def test_a_solved_task_is_a_success(tmp_path: Path) -> None:
     assert record.tuning["driver"]["max_turns"] == 40
 
 
+def test_the_model_can_read_the_history_on_the_build_vm(tmp_path: Path) -> None:
+    [task] = load_tasks(["write-function"])
+    turns = [
+        [call("run_command", "g", command="git log --oneline && git status --short")],
+        *SOLVE_SLUGIFY,
+    ]
+    record = run_task(task, FACTS, Scripted(turns), Tuning(), host=HOST, note="n")
+    assert record.success
+    assert record.failed_commands == 0
+
+
 def test_saying_finished_is_not_success(tmp_path: Path) -> None:
     # Success is the hidden check passing, never the model's own claim.
     [task] = load_tasks(["write-function"])
@@ -429,3 +467,26 @@ def test_runs_from_before_the_driver_read_as_its_defaults() -> None:
     old["tuning"]["executor"] = old["tuning"].pop("driver")
     [row] = summarise([old], current)
     assert row.tuning == ""
+
+
+def test_a_kept_run_leaves_its_state_and_call_record(tmp_path: Path) -> None:
+    # As the agent records itself (L7), so the status page can open a
+    # benchmark run (X6); each run gets its own record, and the client is
+    # left as it was.
+    from nisse_core.models.calls import CallReader
+
+    [task] = load_tasks(["write-function"])
+    client = Scripted(list(SOLVE_SLUGIFY))
+    record = run_task(task, FACTS, client, Tuning(), host=HOST, keep=tmp_path / "runs")
+
+    [kept] = list((tmp_path / "runs").iterdir())
+    assert kept.name.startswith("write-function-")
+    assert (kept / "state.db").exists()
+    [run] = CallReader(kept / "state.calls.db").runs()
+    assert (run["work_item"], run["role"], run["outcome"]) == (
+        "bench",
+        "driver",
+        "wait",
+    )
+    assert record.success
+    assert not hasattr(client, "call_recorder")

nisse-dev/tests/test_config.py

@@ -573,3 +573,28 @@ def test_the_vault_is_read() -> None:
 def test_a_bad_vault_is_refused(vault: dict[str, Any], said: str) -> None:
     with pytest.raises(ConfigError, match=re.escape(said)):
         build(vault=vault)
+
+
+def test_the_call_record_is_on_unless_turned_off() -> None:
+    assert build().call_record is True
+    assert build(call_record=False).call_record is False
+    with pytest.raises(ConfigError, match="call_record"):
+        build(call_record="no")
+
+
+def test_both_routes_record_into_one_file_beside_the_state_store(
+    tmp_path: Path,
+) -> None:
+    from nisse_core.models.catalog import ModelCatalog
+    from nisse_dev.loop.build import make_llm_clients
+
+    normalized, passthrough = make_llm_clients(
+        build(state_db=str(tmp_path / "state.db")), ModelCatalog({})
+    )
+    assert normalized.call_recorder is passthrough.call_recorder
+    assert normalized.call_recorder.path == tmp_path / "state.calls.db"
+    off, _ = make_llm_clients(
+        build(state_db=str(tmp_path / "other.db"), call_record=False), ModelCatalog({})
+    )
+    assert off.call_recorder is None
+    assert not (tmp_path / "other.calls.db").exists()

nisse-dev/tests/test_delegation.py

@@ -702,3 +702,25 @@ def test_a_bad_request_is_not_given_the_benefit_of_the_doubt(
     result = build(BadRequestClient([]), store, ws, repo).run(brief="b", branch="d")
     assert result.status == "failed"
     assert not result.interrupted
+
+
+def test_a_delegation_is_recorded_as_a_run_of_its_own(
+    store: StateStore, ws: Workspace, repo: GitRepo
+) -> None:
+    # Its calls are the helper's turns (L7), inside the run that delegated.
+    from nisse_core.models import calls
+
+    seen: list[calls.Scope] = []
+
+    class Watching(ScriptedClient):
+        def complete(self, *args: Any, **kwargs: Any) -> list[CanonicalEvent]:
+            seen.append(calls.current())
+            return super().complete(*args, **kwargs)
+
+    client = Watching([[hand_back(succeeded=False, changed="nothing")]])
+    with calls.run(None, work_item=ITEM, role="driver"):
+        outer = calls.current().run
+        build(client, store, ws, repo).run(brief="look into it", branch="d1")
+    [scope] = seen
+    assert (scope.role, scope.work_item, scope.parent) == ("helper", ITEM, outer)
+    assert scope.run not in (None, outer)

nisse-dev/tests/test_loop_classifier.py

@@ -346,3 +346,27 @@ def test_the_export_script_reads_a_store(tmp_path: Path) -> None:
     lines = [json.loads(line) for line in run.stdout.splitlines()]
     assert [line["verdict"] for line in lines] == ["needs_discussion", "safe"]
     assert lines[0]["input"]["action"]["arguments"] == {"command": "x"}
+
+
+def test_the_classifiers_calls_are_recorded_as_its_own() -> None:
+    # In the call record (L7), a verdict is the classifier's call, not a
+    # turn of the run that asked for it.
+    from nisse_core.models import calls
+
+    seen: list[calls.Scope] = []
+
+    class Watching(Judge):
+        def complete(self, events, tools, model, system=None) -> list[Any]:
+            seen.append(calls.current())
+            return super().complete(events, tools, model, system)
+
+    classifier = ActionClassifier(Watching(verdict("contained")), "local")  # type: ignore[arg-type]
+    with calls.run(None, work_item="w", role="driver"):
+        classifier.judge(Action("run_command", {"command": "make"}), SCOPE, "/w")
+    [scope] = seen
+    assert (scope.role, scope.purpose, scope.work_item) == (
+        "classifier",
+        "classification",
+        "w",
+    )
+    assert scope.run is not None

nisse-dev/tests/test_loop_labels.py

@@ -316,3 +316,19 @@ def test_a_restatement_that_asks_is_sent_back(tmp_path: Path) -> None:
         if hasattr(e.event, "result")
     ]
     assert any("a restatement asks no questions" in r for r in results)
+
+
+def test_the_go_ahead_readers_calls_are_recorded_as_the_classifiers() -> None:
+    from nisse_core.models import calls
+
+    seen: list[calls.Scope] = []
+
+    class Watching(_Model):
+        def complete(self, *args: Any, **kwargs: Any) -> Any:
+            seen.append(calls.current())
+            return super().complete(*args, **kwargs)
+
+    yes = [ToolCall(call_id="v", tool="verdict", arguments={"answer": "yes"})]
+    GoAheadReader(Watching(yes), "m").agrees("add count_words", "ok")  # type: ignore[arg-type]
+    [scope] = seen
+    assert (scope.role, scope.purpose) == ("classifier", "go-ahead reading")

nisse-review/src/nisse_review/build.py

@@ -9,6 +9,7 @@ from nisse_core.knowledge.memory import Memory
 from nisse_core.knowledge.vault import Vault
 from nisse_core.loop.driver import Driver
 from nisse_core.loop.expert import ExpertDesk
+from nisse_core.models import calls
 from nisse_core.models.catalog import ModelCatalog
 from nisse_core.models.compact import Compactor
 from nisse_core.models.context import BudgetedClient
@@ -94,6 +95,7 @@ def llm_client(config: ReviewConfig, oplog: OpLog | None = None) -> BudgetedClie
         safety_margin=tuning.safety_margin,
         enforces_tool_choice=lambda m: catalog.facts(m).supports_tool_choice is True,
         oplog=oplog,  # a cut that fitting has to make is logged
+        call_recorder=calls.recorder_for(config.state_db, config.call_record, oplog),
     )
 
 

nisse-review/src/nisse_review/config.py

@@ -47,6 +47,8 @@ OPTIONAL_KEYS = (
     # Patterns of the repositories it reviews ("dev/nisse", "dev/*", "*/*"),
     # public ones included; unset, every one it was given (R1, ``access``).
     "repositories",
+    # Record every model call for the operator's study (L7); on unless false.
+    "call_record",
 )
 
 
@@ -108,6 +110,7 @@ class ReviewConfig:
     gitea_operators: frozenset[str]  # whose comments are the operator's (R4)
     max_output_tokens: int = DEFAULT_MAX_OUTPUT_TOKENS
     request_timeout_s: float = DEFAULT_REQUEST_TIMEOUT_S
+    call_record: bool = True  # every model call recorded for the operator (L7)
     tuning: Tuning = field(default_factory=Tuning)
     vault: VaultConfig | None = None
     repositories: frozenset[str] | None = None  # None: all it can read
@@ -158,6 +161,9 @@ class ReviewConfig:
             owner, slash, name = pattern.partition("/")
             if not (owner and slash and name) or "/" in name:
                 errors.append(f"repositories: {pattern!r} is not owner/name")
+        record = values.get("call_record", True)
+        if not isinstance(record, bool):
+            errors.append("call_record: true or false")
         if errors:
             raise ConfigError("cannot start: " + "; ".join(errors))
         reviewer = str(values["roles.reviewer"])
@@ -173,6 +179,7 @@ class ReviewConfig:
             gitea_operators=people(values["gitea.operators"]),
             max_output_tokens=max_output,
             request_timeout_s=timeout,
+            call_record=record,
             tuning=tuning,
             vault=vault,
             repositories=patterns,

nisse-review/tests/test_review.py

@@ -645,3 +645,43 @@ def test_code_git_cannot_give_fails_the_run(tmp_path: Path) -> None:
     w["scheduler"].round()
     assert (item(w).position, pr_of(item(w)).attempts) == (READY, 1)
     assert w["gitea"].posted == []
+
+
+def test_the_review_agent_records_its_calls_unless_told_not_to(
+    tmp_path: Path, monkeypatch: pytest.MonkeyPatch
+) -> None:
+    from nisse_core.config import ConfigError
+    from nisse_core.models.catalog import ModelCatalog
+    from nisse_review import build as review_build
+    from nisse_review.config import ReviewConfig
+
+    tree = {
+        "state_db": str(tmp_path / "s.db"),
+        "llm": {"base_url": "http://llm", "token": "k"},
+        "roles": {"reviewer": "local", "expert": "frontier"},
+        "gitea": {"url": "https://g", "token": "t", "operators": ["don"]},
+    }
+    limits = {"max_input_tokens": 32768, "max_output_tokens": 4096}
+    catalog = ModelCatalog.from_payload(
+        {
+            "data": [
+                {
+                    "model_name": m,
+                    "litellm_params": {"model": f"x/{m}"},
+                    "model_info": limits,
+                }
+                for m in ("local", "frontier")
+            ]
+        }
+    )
+    monkeypatch.setattr(review_build.ModelCatalog, "discover", lambda *a, **k: catalog)
+
+    on = review_build.llm_client(ReviewConfig.from_tree(tree, {}))
+    assert on.call_recorder is not None
+    assert on.call_recorder.path == tmp_path / "s.calls.db"
+    off = review_build.llm_client(
+        ReviewConfig.from_tree({**tree, "call_record": False}, {})
+    )
+    assert off.call_recorder is None
+    with pytest.raises(ConfigError, match="call_record"):
+        ReviewConfig.from_tree({**tree, "call_record": "yes"}, {})

nisse-ui/README.md

@@ -0,0 +1,40 @@
+# nisse-ui
+
+The status page (architecture X6): a read-only view of what the agents did
+and how, for studying context, compaction and memory in practice.
+
+It reads each agent's state store and the call record beside it (L7), and
+never writes to either. It runs no model and holds no credentials.
+
+    uv run nisse-ui --source dev=/var/lib/nisse-dev/state.db \
+                    --source review=/var/lib/nisse-review/state.db \
+                    --runs /path/to/kept-runs
+
+- `--source NAME=STATE_DB`: an agent's state store. Its call record is
+  `<stem>.calls.db` beside it.
+- `--runs DIR`: runs the benchmark kept (`scripts/benchmark.py run
+  --keep-runs DIR`). Each folder holding a `state.db` is a source.
+
+It listens on 127.0.0.1:8765, because it shows everything the models saw,
+including what other people wrote. Until it sits behind Caddy and Authelia
+(M6.6d), reach it through an SSH tunnel:
+
+    ssh -L 8765:localhost:8765 <this VM>
+
+then open http://localhost:8765/.
+
+**What it shows:** for each work item, its steps (what people and the
+orchestrator said, and each run), each run's turns, and for each turn:
+
+- the request exactly as sent, message by message, beside the log events
+  each came from and what rendering did to them;
+- what changed since the turn before, and where prompt reuse had to stop,
+  next to the server's own count;
+- the reply, with its reasoning;
+- the raw JSON.
+
+Runs going in circles are flagged (`nisse_core.loop.circles`).
+
+**Safety:** everything is escaped, and the page sends a Content Security
+Policy that runs no script at all. Files are opened through
+`nisse_core.state.readonly`, which never creates or locks anything.

nisse-ui/pyproject.toml

@@ -0,0 +1,16 @@
+[project]
+name = "nisse-ui"
+version = "0.1.0"
+description = "Status page: a read-only view of what the agents did and how (X6)"
+requires-python = ">=3.12"
+dependencies = ["nisse-core", "jinja2>=3.1"]
+
+[project.scripts]
+nisse-ui = "nisse_ui.main:main"
+
+[tool.uv.sources]
+nisse-core = { workspace = true }
+
+[build-system]
+requires = ["uv_build>=0.12,<0.13"]
+build-backend = "uv_build"

nisse-ui/src/nisse_ui/__init__.py

@@ -0,0 +1 @@
+"""nisse-ui: the operator's read-only view of the agents (architecture X6)."""

nisse-ui/src/nisse_ui/app.py

@@ -0,0 +1,230 @@
+"""The page's routes, as a plain function from a path to a response, so the
+tests drive it without a socket (X6).
+
+    /                         the sources: agents and kept runs
+    /s/<source>/              a source's work items
+    /s/<source>/item/<id>     an item's walkthrough ("-": the agent-level log)
+    /s/<source>/call/<n>      one turn, read against its log
+    /s/<source>/event/<n>     one log event in full
+"""
+
+import json
+import sqlite3
+from dataclasses import dataclass, field
+from importlib import resources
+from typing import Any
+from urllib.parse import quote, unquote, urlsplit
+
+from jinja2 import Environment, PackageLoader, StrictUndefined
+
+from nisse_core.models import calls
+from nisse_ui import walk
+from nisse_ui.sources import Source, StateReader, UnknownSchema, call_record
+
+AGENT_LEVEL = "-"  # the item id that stands for the agent-level log
+
+# Everything shown is untrusted text (L11): escaped by the templates, and
+# the browser runs no script at all, loads nothing from elsewhere, and
+# sends no referrer.
+HEADERS = {
+    "Content-Security-Policy": (
+        "default-src 'none'; style-src 'self'; img-src 'self'; base-uri 'none'; "
+        "form-action 'none'; frame-ancestors 'none'"
+    ),
+    "X-Content-Type-Options": "nosniff",
+    "Referrer-Policy": "no-referrer",
+    "Cache-Control": "no-store",
+}
+
+
+@dataclass(frozen=True)
+class Response:
+    status: int
+    body: bytes
+    content_type: str = "text/html; charset=utf-8"
+    headers: dict[str, str] = field(default_factory=lambda: dict(HEADERS))
+
+
+def _when(ts: Any) -> str:
+    return str(ts)[:19].replace("T", " ") if ts else "—"
+
+
+def _num(n: Any) -> str:
+    return f"{n:,}" if isinstance(n, int) and not isinstance(n, bool) else "—"
+
+
+def _pretty(text: Any) -> str:
+    """JSON text indented, anything else as it is."""
+    if not isinstance(text, str):
+        return json.dumps(text, indent=2, ensure_ascii=False)
+    try:
+        return json.dumps(json.loads(text), indent=2, ensure_ascii=False)
+    except ValueError:
+        return text
+
+
+def _clip(text: Any, limit: int = 300) -> str:
+    text = str(text or "")
+    return (
+        text
+        if len(text) <= limit
+        else text[:limit] + f" … [{len(text) - limit:,} more]"
+    )
+
+
+def summary(kind: str, payload: dict[str, Any]) -> str:
+    """One event as a line of text: what it said or did."""
+    match kind:
+        case "user_message" | "assistant_text" | "fact":
+            return str(payload.get("text", ""))
+        case "tool_call":
+            args = json.dumps(payload.get("arguments", {}), ensure_ascii=False)
+            return f"{payload.get('tool', '?')}({args})"
+        case "tool_result":
+            mark = "ok" if payload.get("success") else "FAILED"
+            return f"{mark}: {payload.get('result', '')}"
+        case "plan_submitted":
+            return str(payload.get("plan", ""))
+        case "gate_opened":
+            return f"{payload.get('gate', '')}: {payload.get('reason', '')}"
+        case "delegation_started":
+            return f"({payload.get('model', '')}) {payload.get('brief', '')}"
+        case "delegation_completed":
+            return f"[{payload.get('exit_status', '')}] {payload.get('handback', '')}"
+        case "compaction":
+            first, last = (payload.get("replaces") or ["?", "?"])[:2]
+            return f"replaces {first}–{last}: {payload.get('summary', '')}"
+        case "action_verdict":
+            return (
+                f"{payload.get('tool', '')}: {payload.get('effect', '')} → "
+                f"{payload.get('decision', '')} ({payload.get('reason', '')})"
+            )
+        case _:
+            return json.dumps(payload, ensure_ascii=False)
+
+
+def _reply_line(reply: walk.Reply) -> str:
+    calls_made = "; ".join(f"{tool}({args})" for tool, args in reply.calls)
+    text = " ".join(reply.text.split())
+    return " · ".join(p for p in (text, calls_made) if p) or "(no reply)"
+
+
+class App:
+    def __init__(self, sources: list[Source]) -> None:
+        self.sources = list(sources)
+        self.by_name = {s.name: s for s in sources}
+        env = Environment(
+            loader=PackageLoader("nisse_ui", "templates"),
+            autoescape=True,  # always: every page shows untrusted text
+            undefined=StrictUndefined,
+            trim_blocks=True,
+            lstrip_blocks=True,
+        )
+        env.filters.update(
+            u=lambda s: quote(str(s), safe=""),
+            when=_when,
+            num=_num,
+            pretty=_pretty,
+            clip=_clip,
+            reply_line=_reply_line,
+        )
+        env.globals.update(summary=summary, AGENT_LEVEL=AGENT_LEVEL)
+        self.env = env
+
+    def page(self, template: str, status: int = 200, **values: Any) -> Response:
+        html = self.env.get_template(template).render(**values)
+        return Response(status, html.encode())
+
+    def problem(self, status: int, title: str, detail: str) -> Response:
+        return self.page("problem.html", status, title=title, detail=detail)
+
+    def handle(self, raw_path: str) -> Response:
+        path = urlsplit(raw_path).path
+        parts = [unquote(p) for p in path.split("/")[1:]]
+        if parts in ([], [""]):
+            return self.home()
+        if parts == ["static", "style.css"]:
+            css = resources.files("nisse_ui").joinpath("static/style.css").read_bytes()
+            return Response(200, css, "text/css; charset=utf-8")
+        if len(parts) >= 2 and parts[0] == "s":
+            source = self.by_name.get(parts[1])
+            if source is None:
+                return self.problem(404, "No such source", parts[1])
+            rest = parts[2:]
+            try:
+                if rest in ([], [""]):
+                    return self.items(source)
+                if len(rest) == 2 and rest[0] == "item":
+                    item = None if rest[1] == AGENT_LEVEL else rest[1]
+                    return self.item(source, item)
+                if (
+                    len(rest) == 2
+                    and rest[0] in ("call", "event")
+                    and rest[1].isdigit()
+                ):
+                    if rest[0] == "call":
+                        return self.call(source, int(rest[1]))
+                    return self.event(source, int(rest[1]))
+            except UnknownSchema as exc:
+                return self.problem(
+                    409, "A state store this page doesn't know", str(exc)
+                )
+            except calls.UnknownLayout as exc:
+                return self.problem(
+                    409, "A call record this page doesn't know", str(exc)
+                )
+            except sqlite3.Error as exc:
+                return self.problem(503, "Couldn't read the store", str(exc))
+        return self.problem(404, "Not found", path)
+
+    # --- pages ---------------------------------------------------------------------
+
+    def home(self) -> Response:
+        rows = []
+        for source in self.sources:
+            row: dict[str, Any] = {"source": source, "count": None, "note": ""}
+            try:
+                with StateReader(source.state_db) as state:
+                    row["count"] = state.count_items()
+                    row["schema"] = state.schema_version
+            except (UnknownSchema, sqlite3.Error) as exc:
+                row["note"] = str(exc)
+            row["record"] = source.calls_db.is_file()
+            rows.append(row)
+        return self.page("sources.html", rows=rows)
+
+    def items(self, source: Source) -> Response:
+        with StateReader(source.state_db) as state:
+            return self.page(
+                "items.html",
+                source=source,
+                items=state.items(),
+                active=state.active_item(),
+            )
+
+    def item(self, source: Source, item_id: str | None) -> Response:
+        with StateReader(source.state_db) as state:
+            if item_id is not None and state.item(item_id) is None:
+                return self.problem(404, "No such work item", item_id)
+            try:
+                with call_record(source) as reader:
+                    view = walk.walkthrough(state, reader, item_id)
+            except calls.UnknownLayout as exc:
+                view = walk.walkthrough(state, None, item_id, record_note=str(exc))
+            return self.page("item.html", source=source, view=view)
+
+    def call(self, source: Source, call_id: int) -> Response:
+        with StateReader(source.state_db) as state, call_record(source) as reader:
+            if reader is None:
+                return self.problem(404, "No call record", str(source.calls_db))
+            view = walk.turn(state, reader, call_id)
+            if view is None:
+                return self.problem(404, "No such call", str(call_id))
+            return self.page("call.html", source=source, view=view)
+
+    def event(self, source: Source, event_id: int) -> Response:
+        with StateReader(source.state_db) as state:
+            found = state.event(event_id)
+            if found is None:
+                return self.problem(404, "No such event", str(event_id))
+            return self.page("event.html", source=source, event=found)

nisse-ui/src/nisse_ui/main.py

@@ -0,0 +1,70 @@
+"""Serve the status page (X6), read-only, on this machine only.
+
+    nisse-ui --source dev=/var/lib/nisse-dev/state.db --runs bench-kept/
+
+Each source is an agent's state store; its call record is found beside it.
+``--runs`` names folders of runs the benchmark kept (``--keep-runs``). It
+listens on 127.0.0.1: until it sits behind Authelia (M6.6d), reach it
+through an SSH tunnel, since it shows everything the models saw.
+"""
+
+import argparse
+import sys
+from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
+from pathlib import Path
+
+from nisse_ui.app import App
+from nisse_ui.sources import discover
+
+
+def _source(text: str) -> tuple[str, Path]:
+    name, sep, path = text.partition("=")
+    if not sep or not name or not path:
+        raise argparse.ArgumentTypeError("expected NAME=STATE_DB")
+    return name, Path(path)
+
+
+def handler_for(app: App) -> type[BaseHTTPRequestHandler]:
+    class Handler(BaseHTTPRequestHandler):
+        server_version = "nisse-ui"
+        sys_version = ""
+
+        def do_GET(self) -> None:
+            response = app.handle(self.path)
+            self.send_response(response.status)
+            self.send_header("Content-Type", response.content_type)
+            self.send_header("Content-Length", str(len(response.body)))
+            for key, value in response.headers.items():
+                self.send_header(key, value)
+            self.end_headers()
+            self.wfile.write(response.body)
+
+        def log_message(self, format: str, *args: object) -> None:
+            sys.stderr.write(f"nisse-ui {self.address_string()} {format % args}\n")
+
+    return Handler
+
+
+def main(argv: list[str] | None = None) -> int:
+    parser = argparse.ArgumentParser(description=__doc__.splitlines()[0])
+    parser.add_argument(
+        "--source", action="append", type=_source, default=[], metavar="NAME=STATE_DB"
+    )
+    parser.add_argument("--runs", action="append", type=Path, default=[], metavar="DIR")
+    parser.add_argument("--host", default="127.0.0.1")
+    parser.add_argument("--port", type=int, default=8765)
+    args = parser.parse_args(argv)
+    app = App(discover(args.source, args.runs))
+    server = ThreadingHTTPServer((args.host, args.port), handler_for(app))
+    print(f"nisse-ui on http://{args.host}:{args.port}/", file=sys.stderr)
+    try:
+        server.serve_forever()
+    except KeyboardInterrupt:
+        pass
+    finally:
+        server.server_close()
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

nisse-ui/src/nisse_ui/sources.py

@@ -0,0 +1,229 @@
+"""Where the page reads from (X6): each agent's state store and the call
+record beside it, and the runs the benchmark kept. Everything is opened
+read-only (SQLite ``mode=ro``), one short connection per page, so the agent
+stays the only writer of its state (L8) and nothing here can lock it."""
+
+import contextlib
+import json
+import re
+import sqlite3
+from collections.abc import Iterator
+from dataclasses import dataclass, field
+from pathlib import Path
+from typing import Any, Self
+
+from nisse_core.models import calls
+from nisse_core.state import readonly
+
+# The state store schema versions this page knows: the shared store's, and
+# each agent's that adds tables of its own. The page reads only the shared
+# tables, but says so for any version it doesn't know rather than guessing.
+KNOWN_SCHEMAS = {4: "nisse-core (nisse-review)", 5: "nisse-dev"}
+
+
+class UnknownSchema(RuntimeError):
+    pass
+
+
+@dataclass(frozen=True)
+class Source:
+    name: str  # what the page calls it, safe in a URL
+    state_db: Path
+    kind: str  # "agent" | "run" (a kept benchmark run)
+
+    @property
+    def calls_db(self) -> Path:
+        return calls.path_for(self.state_db)
+
+
+def safe_name(text: str) -> str:
+    return re.sub(r"[^A-Za-z0-9._-]+", "-", text).strip("-") or "source"
+
+
+def discover(agents: list[tuple[str, Path]], runs: list[Path]) -> list[Source]:
+    """The agents named on the command line, then each run kept under the
+    runs folders (a folder holding a ``state.db``), newest first."""
+    found = [Source(safe_name(name), path, "agent") for name, path in agents]
+    for folder in runs:
+        kept = sorted(
+            (p for p in folder.glob("*/state.db") if p.is_file()),
+            key=lambda p: p.stat().st_mtime,
+            reverse=True,
+        )
+        found += [
+            Source(safe_name(f"{folder.name}.{p.parent.name}"), p, "run") for p in kept
+        ]
+    names: set[str] = set()
+    unique = []
+    for source in found:
+        name, n = source.name, 2
+        while name in names:
+            name, n = f"{source.name}-{n}", n + 1
+        names.add(name)
+        unique.append(Source(name, source.state_db, source.kind))
+    return unique
+
+
+@dataclass(frozen=True)
+class Item:
+    id: str
+    title: str
+    status: str
+    outcome: str | None
+    position: str
+    scope: str | None
+    opened_at: str
+    updated_at: str
+    closed_at: str | None
+    data: dict[str, Any] = field(default_factory=dict)
+
+
+@dataclass(frozen=True)
+class Event:
+    id: int
+    ts: str
+    type: str
+    payload: dict[str, Any]
+    work_item: str | None
+    actor: str
+
+
+def _loads(text: str | None) -> Any:
+    """Item data and payloads, read tolerantly: whatever doesn't parse is kept
+    as text, so a field from a newer agent never breaks the page."""
+    if text is None:
+        return None
+    try:
+        return json.loads(text)
+    except (TypeError, ValueError):
+        return {"unreadable": text}
+
+
+def connect(path: Path) -> sqlite3.Connection:
+    return readonly.connect(path)
+
+
+class StateReader:
+    """A state store, read-only. Use as a context manager: it closes at the
+    end of the page that opened it."""
+
+    def __init__(self, path: Path) -> None:
+        self.path = path
+        self._conn = connect(path)
+        try:
+            row = self._conn.execute(
+                "SELECT value FROM meta WHERE key = 'schema_version'"
+            ).fetchone()
+        except sqlite3.Error as exc:
+            self._conn.close()
+            raise UnknownSchema(f"not a state store: {exc}") from exc
+        self.schema_version = int(row["value"]) if row else 0
+        if self.schema_version not in KNOWN_SCHEMAS:
+            self._conn.close()
+            known = ", ".join(str(v) for v in sorted(KNOWN_SCHEMAS))
+            raise UnknownSchema(
+                f"state store schema {self.schema_version}, not known to this "
+                f"page (it knows {known})"
+            )
+
+    def __enter__(self) -> Self:
+        return self
+
+    def __exit__(self, *exc: object) -> None:
+        self.close()
+
+    def close(self) -> None:
+        self._conn.close()
+
+    def active_item(self) -> str | None:
+        row = self._conn.execute(
+            "SELECT active_item FROM agent WHERE id = 1"
+        ).fetchone()
+        return row["active_item"] if row else None
+
+    def items(self) -> list[Item]:
+        rows = self._conn.execute(
+            "SELECT * FROM work_items ORDER BY opened_at DESC, id"
+        ).fetchall()
+        return [self._item(r) for r in rows]
+
+    def item(self, item_id: str) -> Item | None:
+        row = self._conn.execute(
+            "SELECT * FROM work_items WHERE id = ?", (item_id,)
+        ).fetchone()
+        return self._item(row) if row else None
+
+    def _item(self, row: sqlite3.Row) -> Item:
+        data = _loads(row["data"])
+        return Item(
+            id=row["id"],
+            title=row["title"],
+            status=row["status"],
+            outcome=row["outcome"],
+            position=row["position"],
+            scope=row["scope"],
+            opened_at=row["opened_at"],
+            updated_at=row["updated_at"],
+            closed_at=row["closed_at"],
+            data=data if isinstance(data, dict) else {"unreadable": row["data"]},
+        )
+
+    def events(self, work_item: str | None) -> list[Event]:
+        """One item's log, or the agent-level log (None)."""
+        if work_item is None:
+            rows = self._conn.execute(
+                "SELECT * FROM canonical_events WHERE work_item IS NULL ORDER BY id"
+            )
+        else:
+            rows = self._conn.execute(
+                "SELECT * FROM canonical_events WHERE work_item = ? ORDER BY id",
+                (work_item,),
+            )
+        return [self._event(r) for r in rows]
+
+    def event(self, event_id: int) -> Event | None:
+        row = self._conn.execute(
+            "SELECT * FROM canonical_events WHERE id = ?", (event_id,)
+        ).fetchone()
+        return self._event(row) if row else None
+
+    def events_by_id(self, ids: list[int]) -> dict[int, Event]:
+        found: dict[int, Event] = {}
+        wanted = sorted({i for i in ids if i > 0})
+        for start in range(0, len(wanted), 500):
+            chunk = wanted[start : start + 500]
+            marks = ",".join("?" * len(chunk))
+            for row in self._conn.execute(
+                f"SELECT * FROM canonical_events WHERE id IN ({marks})", chunk
+            ):
+                found[row["id"]] = self._event(row)
+        return found
+
+    def count_items(self) -> int:
+        return self._conn.execute("SELECT COUNT(*) FROM work_items").fetchone()[0]
+
+    def _event(self, row: sqlite3.Row) -> Event:
+        payload = _loads(row["payload"])
+        return Event(
+            id=row["id"],
+            ts=row["ts"],
+            type=row["type"],
+            payload=payload if isinstance(payload, dict) else {"value": payload},
+            work_item=row["work_item"],
+            actor=row["actor"],
+        )
+
+
+@contextlib.contextmanager
+def call_record(source: Source) -> Iterator[calls.CallReader | None]:
+    """The source's call record, or None when there is none (an agent
+    started before M6.6a, or recording turned off). An unknown layout raises
+    ``calls.UnknownLayout`` for the page to report."""
+    if not source.calls_db.is_file():
+        yield None
+        return
+    reader = calls.CallReader(source.calls_db)
+    try:
+        yield reader
+    finally:
+        reader.close()

nisse-ui/src/nisse_ui/static/style.css

@@ -0,0 +1,77 @@
+/* nisse-ui: plain, readable, no external assets (X6). */
+:root {
+  --bg: #fbfbfa; --fg: #1d1d1b; --muted: #6b6b66; --line: #deded8;
+  --panel: #f2f2ee; --accent: #2f5d8a; --bad: #a3322a; --warn: #8a5a00;
+  --new: #e3f0e0; --change: #fbe6c8; --flag: #f6d9d6;
+  --mono: ui-monospace, "SF Mono", Menlo, Consolas, monospace;
+}
+@media (prefers-color-scheme: dark) {
+  :root {
+    --bg: #161615; --fg: #e6e6e1; --muted: #9a9a93; --line: #34342f;
+    --panel: #20201e; --accent: #8fb8e0; --bad: #ec8a80; --warn: #e2b462;
+    --new: #233523; --change: #3d2f17; --flag: #432522;
+  }
+}
+* { box-sizing: border-box; }
+body { margin: 0; background: var(--bg); color: var(--fg);
+  font: 15px/1.5 system-ui, -apple-system, "Segoe UI", sans-serif; }
+main { max-width: 1100px; margin: 0 auto; padding: 0 16px 64px; }
+a { color: var(--accent); }
+h1 { font-size: 1.5rem; margin: 1.2rem 0 .4rem; }
+h2 { font-size: 1.15rem; margin: 1.8rem 0 .6rem; border-bottom: 1px solid var(--line); }
+h3 { font-size: 1rem; margin: 1.2rem 0 .4rem; }
+.top { border-bottom: 1px solid var(--line); background: var(--panel); }
+.crumbs { max-width: 1100px; margin: 0 auto; padding: 8px 16px; }
+.muted, .meta { color: var(--muted); }
+.meta { font-size: .9rem; }
+.bad { color: var(--bad); }
+.path { font-family: var(--mono); font-size: .85rem; word-break: break-all; }
+pre, code { font-family: var(--mono); font-size: .85rem; }
+pre { background: var(--panel); border: 1px solid var(--line); border-radius: 4px;
+  padding: 8px 10px; overflow-x: auto; white-space: pre-wrap; word-break: break-word; margin: .4rem 0; }
+table { border-collapse: collapse; width: 100%; margin: .6rem 0; font-size: .92rem; }
+th, td { text-align: left; vertical-align: top; padding: 4px 8px; border-bottom: 1px solid var(--line); }
+th { color: var(--muted); font-weight: 600; }
+tr.active td { background: var(--new); }
+table.facts th { width: 14%; white-space: nowrap; }
+table.log td.text { font-family: var(--mono); font-size: .8rem; word-break: break-word; }
+details { margin: .4rem 0; }
+summary { cursor: pointer; }
+.tag { display: inline-block; font-size: .78rem; padding: 0 6px; border-radius: 3px;
+  background: var(--panel); border: 1px solid var(--line); margin-right: 2px; }
+.tag.warn { color: var(--warn); }
+.flag { display: inline-block; font-size: .78rem; padding: 0 6px; border-radius: 3px;
+  background: var(--flag); color: var(--bad); margin-left: 4px; }
+.badge { display: inline-block; font-size: .78rem; padding: 0 6px; border-radius: 3px; }
+.badge.new { background: var(--new); }
+.badge.change { background: var(--change); }
+.note { background: var(--panel); border-left: 3px solid var(--accent); padding: 6px 10px; }
+.circle { background: var(--flag); color: var(--bad); padding: 4px 10px; border-radius: 4px; }
+.timeline > * { margin: .5rem 0; }
+.step { border-left: 3px solid var(--line); padding: 2px 10px; }
+.step .text { white-space: pre-wrap; word-break: break-word; }
+.step-user_message { border-left-color: var(--accent); }
+.step-gate_opened, .step-fact { border-left-color: var(--warn); }
+.run { border: 1px solid var(--line); border-radius: 6px; padding: 4px 10px; background: var(--bg); }
+.run .run { margin: .4rem 0 .4rem 12px; }
+.run > summary { padding: 4px 0; }
+.turn { padding: 4px 0 4px 8px; border-top: 1px dashed var(--line); }
+.turn.flagged { background: var(--flag); }
+.turn-no { font-weight: 600; margin-right: 6px; }
+.turn .reply { font-family: var(--mono); font-size: .82rem; color: var(--muted); word-break: break-word; }
+.told { font-size: .82rem; color: var(--warn); }
+.pager { display: flex; justify-content: space-between; margin-top: 1rem; }
+.msg { border: 1px solid var(--line); border-radius: 6px; padding: 6px 10px; margin: .6rem 0; }
+.msg.first-change { border-color: var(--warn); border-width: 2px; }
+.msg-head { font-size: .88rem; }
+.msg-head .role { font-weight: 700; text-transform: uppercase; letter-spacing: .03em; margin-right: 4px; }
+.role-user { border-left: 4px solid var(--accent); }
+.role-assistant { border-left: 4px solid #6a8f4e; }
+.role-tool { border-left: 4px solid var(--muted); }
+.role-system { border-left: 4px solid var(--warn); }
+ul.from { margin: .3rem 0; padding-left: 1.2rem; font-size: .85rem; }
+ul.from .text { font-family: var(--mono); font-size: .8rem; color: var(--muted); }
+.toolcall { margin: .3rem 0; }
+@media (max-width: 640px) {
+  table.facts th, table.facts td { display: block; width: auto; border: 0; }
+}

nisse-ui/src/nisse_ui/templates/base.html

@@ -0,0 +1,17 @@
+<!doctype html>
+<html lang="en">
+<head>
+<meta charset="utf-8">
+<meta name="viewport" content="width=device-width, initial-scale=1">
+<title>{% block title %}Agents{% endblock %} · nisse-ui</title>
+<link rel="stylesheet" href="/static/style.css">
+</head>
+<body>
+<header class="top">
+  <nav class="crumbs"><a href="/">nisse-ui</a>{% block crumbs %}{% endblock %}</nav>
+</header>
+<main>
+{% block main %}{% endblock %}
+</main>
+</body>
+</html>

nisse-ui/src/nisse_ui/templates/call.html

@@ -0,0 +1,93 @@
+{% extends "base.html" %}
+{% from "macros.html" import src_link, item_href, event_link, flags %}
+{% set c = view.call %}
+{% block title %}Turn {{ view.number }}{% endblock %}
+{% block crumbs %} › {{ src_link(source) }} › <a href="{{ item_href(source, c.work_item) }}">{{ c.work_item or "agent" }}</a> › {% if view.run %}{{ view.run.kind }} {{ view.run.role }} › {% endif %}turn {{ view.number }}{% endblock %}
+{% block main %}
+<nav class="pager">
+  {% if view.previous %}<a href="/s/{{ source.name|u }}/call/{{ view.previous }}">← turn {{ view.number - 1 }}</a>{% else %}<span class="muted">first turn</span>{% endif %}
+  {% if view.following %}<a href="/s/{{ source.name|u }}/call/{{ view.following }}">turn {{ view.number + 1 }} →</a>{% else %}<span class="muted">last turn</span>{% endif %}
+</nav>
+<h1>Turn {{ view.number }}{% if c.purpose %}: {{ c.purpose }}{% endif %} {{ flags(view.flags) }}</h1>
+
+<table class="facts">
+  <tr><th>Role</th><td>{{ c.role or "—" }}</td><th>Time</th><td>{{ c.at|when }}, {{ "%.2f"|format(c.seconds) }}s</td></tr>
+  <tr><th>Model asked</th><td>{{ c.model }}</td><th>Answered by</th><td>{{ c.answered_by or "—" }}</td></tr>
+  <tr><th>Tokens</th><td>{{ c.tokens_in|num }} in · {{ c.tokens_out|num }} out</td><th>Prompt reuse (server)</th><td>{{ view.reused or "not reported" }}</td></tr>
+  <tr><th>Estimate</th><td>{{ c.estimate|num }} tokens (factor {{ c.factor }})</td><th>Route</th><td>{{ c.route or "—" }}, HTTP {{ c.status or "—" }}</td></tr>
+  <tr><th>Outcome</th><td{% if c.outcome != "answered" %} class="bad"{% endif %}>{{ c.outcome }}</td><th>Fitting</th><td>{% if c.trim %}{{ c.trim|pretty }}{% else %}nothing cut{% endif %}</td></tr>
+</table>
+{% if c.error %}<pre class="bad">{{ c.error }}</pre>{% endif %}
+
+<h2>The reply</h2>
+{% if view.reply.reasoning %}
+<details open class="reasoning"><summary>Reasoning ({{ view.reply.reasoning|length|num }} characters)</summary><pre class="text">{{ view.reply.reasoning }}</pre></details>
+{% endif %}
+{% if view.reply.text %}<pre class="text">{{ view.reply.text }}</pre>{% endif %}
+{% for tool, args in view.reply.calls %}
+<div class="toolcall"><span class="tag">tool call</span> <b>{{ tool }}</b><pre>{{ args|pretty }}</pre></div>
+{% endfor %}
+{% if not view.reply.text and not view.reply.calls and not view.reply.reasoning %}<p class="muted">No reply recorded.</p>{% endif %}
+{% if view.reply.finish %}<p class="meta">Finish reason: {{ view.reply.finish }}</p>{% endif %}
+
+<h2>The request</h2>
+{% if view.settings %}
+<table class="facts">{% for k, v in view.settings.items() %}<tr><th>{{ k }}</th><td><code>{{ v|pretty }}</code></td></tr>{% endfor %}</table>
+{% endif %}
+{% if view.tools %}
+<details><summary>{{ view.tools|length }} tools offered{% if view.tools_changed %} <span class="flag">changed since the turn before</span>{% endif %}</summary>
+<p>{{ view.tools|join(", ") }}</p></details>
+{% endif %}
+{% if view.compared %}
+<p class="note">Messages marked <span class="badge new">new</span> weren't in the turn before. <span class="badge change">first change</span> marks where this request first differs from the last one: prompt reuse can't go past it. The server reused {{ view.reused or "an unreported number of" }} tokens.</p>
+{% endif %}
+{% if view.match_note %}<p class="note">{{ view.match_note }}</p>{% endif %}
+
+{% for m in view.messages %}
+<section class="msg role-{{ m.role }}{% if m.first_change %} first-change{% endif %}" id="m{{ m.index }}">
+  <div class="msg-head">
+    <span class="role">{{ m.role }}</span>{% if m.index >= 0 %} <span class="muted">#{{ m.index }}</span>{% endif %}
+    {% if m.new %}<span class="badge new">new</span>{% endif %}
+    {% if m.first_change %}<span class="badge change">first change</span>{% endif %}
+    {% if m.tool_call_id %}<span class="muted">result of {{ m.tool_call_id }}</span>{% endif %}
+    <span class="muted">{{ m.text|length|num }} characters</span>
+  </div>
+  {% if m.role == "system" %}
+  <details><summary>System prompt</summary><pre class="text">{{ m.text }}</pre></details>
+  {% elif m.text %}<pre class="text">{{ m.text }}</pre>{% endif %}
+  {% for id, tool, args in m.tool_calls %}
+  <div class="toolcall"><span class="tag">tool call</span> <b>{{ tool }}</b> <span class="muted">{{ id }}</span><pre>{{ args|pretty }}</pre></div>
+  {% endfor %}
+  {% if m.events %}
+  <ul class="from">
+    {% for s in m.events %}<li>from {{ event_link(source, s.id) }} {{ s.type|replace("_", " ") }} by {{ s.actor }}: {% for t in s.tags %}<span class="tag{% if t != 'unchanged' %} warn{% endif %}">{{ t }}</span>{% endfor %}</li>{% endfor %}
+  </ul>
+  {% endif %}
+</section>
+{% endfor %}
+
+{% if view.unmatched %}
+<h3>Events sent{% if view.match_note %}, not matched to messages{% else %} but replaced by a compaction{% endif %}</h3>
+<ul class="from">
+{% for s in view.unmatched %}<li>{{ event_link(source, s.id) }} {{ s.type|replace("_", " ") }} by {{ s.actor }}: {% for t in s.tags %}<span class="tag{% if t != 'unchanged' %} warn{% endif %}">{{ t }}</span>{% endfor %}
+  <div class="text">{{ summary(s.type, s.payload if s.payload is mapping else {})|clip(300) }}</div></li>{% endfor %}
+</ul>
+{% endif %}
+
+{% if view.compacted %}
+<h3>Replaced by compaction</h3>
+<p>{{ view.compacted|length }} events of the log stood behind a compaction in this request:
+{% for e, comp in view.compacted %}{{ event_link(source, e) }}{% if comp %} → {{ event_link(source, comp) }}{% endif %}{% if not loop.last %}, {% endif %}{% endfor %}</p>
+{% endif %}
+
+{% if view.dropped %}
+<h3>Dropped by fitting</h3>
+<ul class="from">
+{% for id, e in view.dropped %}<li>{{ event_link(source, id) }}{% if e %} {{ e.type|replace("_", " ") }} by {{ e.actor }}: {{ summary(e.type, e.payload)|clip(200) }}{% else %} <span class="muted">(not in this store)</span>{% endif %}</li>{% endfor %}
+</ul>
+{% endif %}
+
+<h2>Raw</h2>
+<details><summary>Request JSON, exactly as sent ({{ view.raw_request|length|num }} characters)</summary><pre>{{ view.raw_request or "(not recorded)" }}</pre></details>
+<details><summary>Response JSON, as received ({{ view.raw_response|length|num }} characters)</summary><pre>{{ view.raw_response or "(not recorded)" }}</pre></details>
+{% endblock %}

nisse-ui/src/nisse_ui/templates/event.html

@@ -0,0 +1,10 @@
+{% extends "base.html" %}
+{% from "macros.html" import src_link, item_href %}
+{% block title %}Event {{ event.id }}{% endblock %}
+{% block crumbs %} › {{ src_link(source) }} › <a href="{{ item_href(source, event.work_item) }}">{{ event.work_item or "agent" }}</a> › event {{ event.id }}{% endblock %}
+{% block main %}
+<h1>Event #{{ event.id }}: {{ event.type|replace("_", " ") }}</h1>
+<p class="meta">{{ event.ts|when }} · by {{ event.actor }} · work item {{ event.work_item or "(agent-level)" }}</p>
+<pre class="text">{{ summary(event.type, event.payload) }}</pre>
+<details><summary>Payload</summary><pre>{{ event.payload|pretty }}</pre></details>
+{% endblock %}

nisse-ui/src/nisse_ui/templates/item.html

@@ -0,0 +1,37 @@
+{% extends "base.html" %}
+{% from "macros.html" import src_link, run_node, turn_row, step, event_link %}
+{% set title = view.item.title if view.item else "Agent-level log" %}
+{% block title %}{{ title }}{% endblock %}
+{% block crumbs %} › {{ src_link(source) }} › {{ view.item.id if view.item else "agent" }}{% endblock %}
+{% block main %}
+<h1>{{ title }}</h1>
+{% if view.item %}
+<p class="meta">{{ view.item.id }} · {{ view.item.status }}{% if view.item.outcome %} ({{ view.item.outcome }}){% endif %}
+  · position {{ view.item.position }} · opened {{ view.item.opened_at|when }}{% if view.item.closed_at %} · closed {{ view.item.closed_at|when }}{% endif %}</p>
+<details><summary>Item data</summary><pre>{{ view.item.data|pretty }}</pre></details>
+{% endif %}
+
+{% if view.record_note %}<p class="note">{{ view.record_note }}</p>
+{% elif view.before_record %}<p class="note">Recording began {{ view.started_at|when }}: steps before then have no requests.</p>{% endif %}
+
+<h2>Steps</h2>
+<div class="timeline">
+{% for kind, obj in view.timeline %}
+  {% if kind == "event" %}{{ step(source, obj) }}
+  {% elif kind == "run" %}{{ run_node(source, obj) }}
+  {% else %}{{ turn_row(source, obj) }}{% endif %}
+{% else %}
+  <p class="muted">Nothing recorded yet.</p>
+{% endfor %}
+</div>
+
+<h2>The log</h2>
+<details{% if view.record_note %} open{% endif %}>
+  <summary>All {{ view.log|length }} events, as stored</summary>
+  <table class="log">
+  {% for e in view.log %}
+    <tr><td>{{ event_link(source, e.id) }}</td><td>{{ e.ts|when }}</td><td>{{ e.actor }}</td><td>{{ e.type }}</td><td class="text">{{ summary(e.type, e.payload)|clip(200) }}</td></tr>
+  {% endfor %}
+  </table>
+</details>
+{% endblock %}

nisse-ui/src/nisse_ui/templates/items.html

@@ -0,0 +1,26 @@
+{% extends "base.html" %}
+{% from "macros.html" import item_href %}
+{% block title %}{{ source.name }}{% endblock %}
+{% block crumbs %} › {{ source.name }}{% endblock %}
+{% block main %}
+<h1>{{ source.name }}</h1>
+<p class="muted path">{{ source.state_db }}</p>
+<p><a href="{{ item_href(source, none) }}">Agent-level log</a>: what happened outside any work item.</p>
+<table>
+  <thead><tr><th>Work item</th><th>Title</th><th>Status</th><th>Position</th><th>Opened</th><th>Updated</th></tr></thead>
+  <tbody>
+  {% for item in items %}
+    <tr{% if item.id == active %} class="active"{% endif %}>
+      <td><a href="{{ item_href(source, item.id) }}">{{ item.id }}</a>{% if item.id == active %} <span class="tag">active</span>{% endif %}</td>
+      <td>{{ item.title }}</td>
+      <td>{{ item.status }}{% if item.outcome %} ({{ item.outcome }}){% endif %}</td>
+      <td>{{ item.position }}</td>
+      <td>{{ item.opened_at|when }}</td>
+      <td>{{ item.updated_at|when }}</td>
+    </tr>
+  {% else %}
+    <tr><td colspan="6" class="muted">No work items.</td></tr>
+  {% endfor %}
+  </tbody>
+</table>
+{% endblock %}

nisse-ui/src/nisse_ui/templates/macros.html

@@ -0,0 +1,48 @@
+{% macro src_link(source) %}<a href="/s/{{ source.name|u }}/">{{ source.name }}</a>{% endmacro %}
+
+{% macro item_href(source, item_id) %}/s/{{ source.name|u }}/item/{{ (item_id if item_id is not none else AGENT_LEVEL)|u }}{% endmacro %}
+
+{% macro event_link(source, id) %}{% if id > 0 %}<a href="/s/{{ source.name|u }}/event/{{ id }}">#{{ id }}</a>{% else %}<span class="muted">(no id)</span>{% endif %}{% endmacro %}
+
+{% macro flags(names) %}{% for f in names %}<span class="flag">{{ f }}</span>{% endfor %}{% endmacro %}
+
+{% macro turn_row(source, t) %}
+<div class="turn{% if t.flags %} flagged{% endif %}">
+  <a class="turn-no" href="/s/{{ source.name|u }}/call/{{ t.call.id }}">turn {{ t.number }}</a>
+  <span class="meta">
+    {% if t.call.purpose %}<span class="tag">{{ t.call.purpose }}</span>{% endif %}
+    {{ t.call.role or "" }} · {{ t.call.model }}{% if t.call.answered_by and t.call.answered_by != t.call.model %} → {{ t.call.answered_by }}{% endif %}
+    · {{ "%.1f"|format(t.call.seconds) }}s · {{ t.call.tokens_in|num }} in / {{ t.call.tokens_out|num }} out
+    {% if t.reused %} · reused {{ t.reused }}{% endif %}
+    {% if t.call.outcome != "answered" %} · <span class="bad">{{ t.call.outcome }}</span>{% endif %}
+  </span>
+  {{ flags(t.flags) }}
+  {% for told in t.told %}<div class="told">orchestrator: {{ told|clip(160) }}</div>{% endfor %}
+  <div class="reply">{{ t.reply|reply_line|clip(240) }}</div>
+</div>
+{% endmacro %}
+
+{% macro run_node(source, node) %}
+<details class="run" open>
+  <summary>
+    <span class="tag">{{ node.run.kind }}</span> {{ node.run.role }}
+    · {{ node.run.outcome or "running" }}
+    · {{ node.run.started_at|when }} → {{ node.run.ended_at|when }}
+    · {{ node.turns|length }} turns
+    {% if node.run.note %}<span class="muted"> · {{ node.run.note|clip(160) }}</span>{% endif %}
+  </summary>
+  {% for c in node.circles %}
+  <p class="circle">Going in circles: {{ c.kind }} at turns {% for i in c.turns %}{{ i + 1 }}{% if not loop.last %}, {% endif %}{% endfor %}: {{ c.detail }}</p>
+  {% endfor %}
+  {% for kind, obj in node.entries %}
+    {% if kind == "turn" %}{{ turn_row(source, obj) }}{% elif kind == "event" %}{{ step(source, obj) }}{% else %}{{ run_node(source, obj) }}{% endif %}
+  {% endfor %}
+</details>
+{% endmacro %}
+
+{% macro step(source, e) %}
+<div class="step step-{{ e.type }}">
+  <span class="meta">{{ event_link(source, e.id) }} {{ e.ts|when }} · {{ e.actor }} · <span class="tag">{{ e.type|replace("_", " ") }}</span></span>
+  <div class="text">{{ summary(e.type, e.payload)|clip(600) }}</div>
+</div>
+{% endmacro %}

nisse-ui/src/nisse_ui/templates/problem.html

@@ -0,0 +1,6 @@
+{% extends "base.html" %}
+{% block title %}{{ title }}{% endblock %}
+{% block main %}
+<h1>{{ title }}</h1>
+<p class="note">{{ detail }}</p>
+{% endblock %}

nisse-ui/src/nisse_ui/templates/sources.html

@@ -0,0 +1,21 @@
+{% extends "base.html" %}
+{% from "macros.html" import src_link %}
+{% block title %}Sources{% endblock %}
+{% block main %}
+<h1>Agents and recorded runs</h1>
+{% if not rows %}<p class="muted">No sources. Start with <code>--source NAME=STATE_DB</code> or <code>--runs DIR</code>.</p>{% endif %}
+<table>
+  <thead><tr><th>Source</th><th>Kind</th><th>Work items</th><th>Call record</th><th>State store</th></tr></thead>
+  <tbody>
+  {% for r in rows %}
+    <tr>
+      <td>{{ src_link(r.source) }}</td>
+      <td>{{ r.source.kind }}</td>
+      <td>{% if r.count is not none %}{{ r.count }}{% else %}<span class="bad">{{ r.note }}</span>{% endif %}</td>
+      <td>{{ "yes" if r.record else "none" }}</td>
+      <td class="path">{{ r.source.state_db }}</td>
+    </tr>
+  {% endfor %}
+  </tbody>
+</table>
+{% endblock %}

nisse-ui/src/nisse_ui/walk.py

@@ -0,0 +1,543 @@
+"""What the pages show, built from the two stores (X6): an item's
+walkthrough (its steps, runs and turns) and one turn read against the log it
+was made from. Pure reading: nothing here writes."""
+
+import json
+from dataclasses import dataclass, field
+from typing import Any
+
+from nisse_core.log.canonical import StoredEvent, from_payload
+from nisse_core.loop.circles import Circle, Turn, find_circles
+from nisse_core.models import calls
+from nisse_core.models.render import OpenAIChatRenderer
+from nisse_ui.sources import Event, Item, StateReader
+
+# The log events shown as steps between runs: what people and the
+# orchestrator said and decided. A model's own turns are shown as turns.
+STEP_TYPES = {
+    "user_message",
+    "fact",
+    "gate_opened",
+    "plan_submitted",
+    "delegation_started",
+    "delegation_completed",
+    "compaction",
+}
+_TURN_TYPES = {"assistant_text", "tool_call", "tool_result", "action_verdict"}
+
+
+# --- a model's reply ------------------------------------------------------------
+
+
+@dataclass(frozen=True)
+class Reply:
+    text: str = ""
+    reasoning: str = ""
+    calls: tuple[tuple[str, str], ...] = ()  # (tool, arguments as sent)
+    finish: str | None = None
+
+
+def _text(content: Any) -> str:
+    if content is None:
+        return ""
+    if isinstance(content, str):
+        return content
+    if isinstance(content, list):
+        parts = []
+        for part in content:
+            if isinstance(part, dict) and isinstance(part.get("text"), str):
+                parts.append(part["text"])
+            else:
+                parts.append(json.dumps(part, ensure_ascii=False))
+        return "\n".join(parts)
+    return json.dumps(content, ensure_ascii=False)
+
+
+def _arguments(value: Any) -> str:
+    return value if isinstance(value, str) else json.dumps(value, ensure_ascii=False)
+
+
+def reply_of(response: Any) -> Reply:
+    """The reply in a raw response, from either route: the OpenAI-shaped chat
+    route or Anthropic's messages route. Anything else is no reply."""
+    if not isinstance(response, dict):
+        return Reply()
+    choices = response.get("choices")
+    if isinstance(choices, list) and choices and isinstance(choices[0], dict):
+        message = choices[0].get("message") or {}
+        reasoning = message.get("reasoning_content") or message.get("reasoning") or ""
+        tool_calls = []
+        for call in message.get("tool_calls") or []:
+            function = (call.get("function") or {}) if isinstance(call, dict) else {}
+            tool_calls.append(
+                (str(function.get("name", "?")), _arguments(function.get("arguments")))
+            )
+        return Reply(
+            text=_text(message.get("content")),
+            reasoning=_text(reasoning),
+            calls=tuple(tool_calls),
+            finish=choices[0].get("finish_reason"),
+        )
+    blocks = response.get("content")
+    if isinstance(blocks, list):
+        texts, thinking, tool_calls = [], [], []
+        for block in blocks:
+            if not isinstance(block, dict):
+                continue
+            match block.get("type"):
+                case "text":
+                    texts.append(str(block.get("text", "")))
+                case "thinking":
+                    thinking.append(str(block.get("thinking", "")))
+                case "tool_use":
+                    tool_calls.append(
+                        (str(block.get("name", "?")), _arguments(block.get("input")))
+                    )
+        return Reply(
+            text="\n".join(texts),
+            reasoning="\n".join(thinking),
+            calls=tuple(tool_calls),
+            finish=response.get("stop_reason"),
+        )
+    return Reply()
+
+
+# --- an item's walkthrough --------------------------------------------------------
+
+
+@dataclass
+class TurnRow:
+    """One call, as a line of the walkthrough."""
+
+    call: dict[str, Any]
+    number: int  # within its run, from 1
+    reply: Reply
+    told: tuple[str, ...]  # corrections given since the turn before
+    flags: list[str] = field(default_factory=list)
+
+    @property
+    def reused(self) -> str | None:
+        return reuse(self.call)
+
+
+@dataclass
+class RunNode:
+    run: dict[str, Any]
+    entries: list[tuple[str, Any]] = field(default_factory=list)  # turns, runs
+    turns: list[TurnRow] = field(default_factory=list)
+    circles: list[Circle] = field(default_factory=list)
+
+
+@dataclass
+class Walkthrough:
+    item: Item | None  # None: the agent-level log
+    timeline: list[
+        tuple[str, Any]
+    ]  # ("event", Event) | ("run", RunNode) | ("turn", TurnRow)
+    log: list[Event]
+    record_note: str | None  # why there are no requests, when there aren't
+    started_at: str | None
+    before_record: bool  # some of this work happened before recording began
+
+
+def reuse(call: dict[str, Any]) -> str | None:
+    """Prompt reuse as the server counted it: cached tokens of the prompt."""
+    cached, fresh = call.get("cache_n"), call.get("prompt_n")
+    if isinstance(cached, int) and isinstance(fresh, int):
+        return f"{cached:,} of {cached + fresh:,}"
+    return None
+
+
+def _corrections(
+    reader: calls.CallReader, call: dict[str, Any], before: set[int]
+) -> tuple[str, ...]:
+    """The orchestrator's statements first sent in this call: a correction
+    is appended to the log each time it's given, so it is new each time."""
+    told = []
+    for event_id, actor, kind, digest in call["sent"]:
+        if kind == "fact" and actor == "orchestrator" and event_id not in before:
+            try:
+                told.append(str(reader.blob(digest).get("text", "")))
+            except (KeyError, AttributeError):
+                continue
+    return tuple(told)
+
+
+def _response(reader: calls.CallReader, call: dict[str, Any]) -> Any:
+    try:
+        return reader.response(call)
+    except KeyError:
+        return None
+
+
+def walkthrough(
+    state: StateReader,
+    reader: calls.CallReader | None,
+    item_id: str | None,
+    *,
+    record_note: str | None = None,
+) -> Walkthrough:
+    item = state.item(item_id) if item_id is not None else None
+    log = state.events(item_id)
+    steps = [e for e in log if e.type in STEP_TYPES or e.type not in _TURN_TYPES]
+    timeline: list[tuple[str, str, Any]] = []
+    started_at = None
+    if reader is None:
+        record_note = record_note or "No call record: requests weren't recorded."
+    else:
+        started_at = reader.started_at
+        nodes = {
+            r["id"]: RunNode(r) for r in reader.runs() if r["work_item"] == item_id
+        }
+        seen: dict[str | None, set[int]] = {}
+        numbers: dict[str | None, int] = {}
+        loose: list[TurnRow] = []
+        for call in reader.calls_for(item_id):
+            run = call["run"] if call["run"] in nodes else None
+            before = seen.setdefault(run, set())
+            numbers[run] = numbers.get(run, 0) + 1
+            row = TurnRow(
+                call=call,
+                number=numbers[run],
+                reply=reply_of(_response(reader, call)),
+                told=_corrections(reader, call, before),
+            )
+            before.update(entry[0] for entry in call["sent"])
+            if run is None:
+                loose.append(row)
+            else:
+                nodes[run].turns.append(row)
+        # A step taken while a run was going on (a correction, a fact) is
+        # shown inside the innermost run it happened during.
+        inside: dict[str, list[tuple[str, str, Any]]] = {}
+        for e in steps:
+            during = [n for n in nodes.values() if _during(n.run, e.ts)]
+            if during:
+                innermost = max(during, key=lambda n: n.run["started_at"])
+                inside.setdefault(innermost.run["id"], []).append(("event", e.ts, e))
+            else:
+                timeline.append(("event", e.ts, e))
+        steps = []
+        for node in nodes.values():
+            node.circles = find_circles(
+                [Turn(t.reply.text, t.reply.calls, t.told) for t in node.turns]
+            )
+            for circle in node.circles:
+                for i in circle.turns:
+                    node.turns[i].flags.append(circle.kind)
+            children = [n for n in nodes.values() if n.run["parent"] == node.run["id"]]
+            entries = [("turn", t.call["at"], t) for t in node.turns]
+            entries += [("run", c.run["started_at"], c) for c in children]
+            entries += inside.get(node.run["id"], [])
+            node.entries = [(kind, obj) for kind, _, obj in sorted(entries, key=_when)]
+        for node in nodes.values():
+            if node.run["parent"] not in nodes:
+                timeline.append(("run", node.run["started_at"], node))
+        timeline += [("turn", t.call["at"], t) for t in loose]
+    timeline += [("event", e.ts, e) for e in steps]
+    ordered = [(kind, obj) for kind, _, obj in sorted(timeline, key=_when)]
+    before_record = reader is None or (
+        started_at is not None and bool(log) and log[0].ts < started_at
+    )
+    return Walkthrough(item, ordered, log, record_note, started_at, before_record)
+
+
+def _during(run: dict[str, Any], ts: str) -> bool:
+    ended = run.get("ended_at")
+    return run["started_at"] <= ts and (ended is None or ts <= ended)
+
+
+def _when(entry: tuple[str, str, Any]) -> str:
+    return entry[1] or ""
+
+
+# --- one turn, read against its log -----------------------------------------------
+
+
+@dataclass
+class SentEvent:
+    id: int
+    actor: str
+    type: str
+    payload: Any
+    tags: list[str]
+    log: Event | None
+
+
+@dataclass
+class Message:
+    index: int
+    role: str
+    text: str
+    tool_calls: list[tuple[str, str, str]]  # (id, tool, arguments)
+    tool_call_id: str | None
+    events: list[SentEvent] = field(default_factory=list)
+    new: bool = False  # not in the turn before
+    first_change: bool = False  # where this request first differs from the last
+
+
+@dataclass
+class TurnView:
+    call: dict[str, Any]
+    number: int
+    run: dict[str, Any] | None
+    previous: int | None
+    following: int | None
+    request: dict[str, Any] | None
+    response: Any
+    reply: Reply
+    messages: list[Message]
+    unmatched: list[SentEvent]  # sent events not matched to a message
+    match_note: str | None
+    dropped: list[tuple[int, Event | None]]
+    compacted: list[tuple[int, int | None]]
+    tools: list[str]
+    tools_changed: bool
+    settings: dict[str, Any]  # the request's other fields: tool_choice, limits
+    compared: bool  # whether there was a turn before to compare with
+    flags: list[str]
+    raw_request: str
+    raw_response: str
+
+    @property
+    def reused(self) -> str | None:
+        return reuse(self.call)
+
+
+def _fields(call: dict[str, Any] | None) -> dict[str, Any]:
+    if not call or not call.get("request"):
+        return {}
+    try:
+        return dict(json.loads(call["request"])["fields"])
+    except (ValueError, KeyError, TypeError):
+        return {}
+
+
+def _tags(
+    entry: list[Any], payload: Any, log: Event | None, call: dict[str, Any]
+) -> list[str]:
+    event_id, _, kind, _ = entry
+    tags: list[str] = []
+    cut = call["shortened"].get(str(event_id))
+    if event_id == 0:
+        tags.append("made for this call, not in the log")
+    elif kind == "compaction" and isinstance(payload, dict):
+        first, last = (payload.get("replaces") or [None, None])[:2]
+        tags.append(f"compaction of events {first}–{last}")
+    elif log is None:
+        tags.append("not in this state store")
+    elif log.payload == payload and log.type == kind:
+        tags.append("unchanged")
+    else:
+        # A role's view says another's work as a labelled statement (L6):
+        # a tool step narrated, a fact or someone's message labelled.
+        source = payload.get("source", "") if isinstance(payload, dict) else ""
+        viewed = kind == "user_message" and str(source).startswith("view:")
+        was = f"{log.type.replace('_', ' ')} by {log.actor}"
+        if viewed and log.type in ("tool_call", "tool_result"):
+            tags.append(f"narrated from {was}")
+        elif viewed:
+            tags.append(
+                "labelled for this role"
+                + ("" if log.type == "user_message" else f" (a {was})")
+            )
+        elif log.type != kind:
+            tags.append(f"rewritten from {was}")
+        elif cut is None:
+            tags.append("changed for this call")
+    if cut is not None:
+        tags.append(f"shortened by {int(cut):,} characters")
+    return tags
+
+
+def turn(state: StateReader, reader: calls.CallReader, call_id: int) -> TurnView | None:
+    call = reader.call(call_id)
+    if call is None:
+        return None
+    run = next((r for r in reader.runs() if r["id"] == call["run"]), None)
+    siblings = (
+        reader.calls(run=call["run"])
+        if call["run"]
+        else [c for c in reader.calls_for(call["work_item"]) if not c["run"]]
+    )
+    at = next(i for i, c in enumerate(siblings) if c["id"] == call_id)
+    before = siblings[at - 1] if at > 0 else None
+    after = siblings[at + 1] if at + 1 < len(siblings) else None
+
+    try:
+        request = reader.request(call)
+    except KeyError:
+        request = None
+    response = _response(reader, call)
+    reply = reply_of(response)
+
+    logged = state.events_by_id([entry[0] for entry in call["sent"]])
+    dropped = state.events_by_id(call["dropped"])
+    sent: list[SentEvent] = []
+    for entry in call["sent"]:
+        try:
+            payload = reader.blob(entry[3])
+        except KeyError:
+            payload = None
+        log = logged.get(entry[0])
+        sent.append(
+            SentEvent(
+                entry[0],
+                entry[1],
+                entry[2],
+                payload,
+                _tags(entry, payload, log, call),
+                log,
+            )
+        )
+
+    raw_messages = (request or {}).get("messages")
+    messages: list[Message] = []
+    if isinstance(raw_messages, list):
+        for i, m in enumerate(raw_messages):
+            m = m if isinstance(m, dict) else {"role": "?", "content": m}
+            calls_made = []
+            for c in m.get("tool_calls") or []:
+                function = (c.get("function") or {}) if isinstance(c, dict) else {}
+                calls_made.append(
+                    (
+                        str(c.get("id", "")) if isinstance(c, dict) else "",
+                        str(function.get("name", "?")),
+                        _arguments(function.get("arguments")),
+                    )
+                )
+            if isinstance(m.get("content"), list):  # Anthropic content blocks
+                for block in m["content"]:
+                    if isinstance(block, dict) and block.get("type") == "tool_use":
+                        calls_made.append(
+                            (
+                                str(block.get("id", "")),
+                                str(block.get("name", "?")),
+                                _arguments(block.get("input")),
+                            )
+                        )
+            messages.append(
+                Message(
+                    index=i,
+                    role=str(m.get("role", "?")),
+                    text=_text(m.get("content")),
+                    tool_calls=calls_made,
+                    tool_call_id=m.get("tool_call_id"),
+                )
+            )
+
+    unmatched, note = _match(call, request, sent, messages)
+
+    mine, theirs = _fields(call), _fields(before)
+    compared = bool(theirs)
+    if compared:
+        old = theirs.get("messages") or []
+        new = mine.get("messages") or []
+        old_set = set(old)
+        for message, digest in zip(messages, new, strict=False):
+            message.new = digest not in old_set
+        change = next(
+            (i for i, (a, b) in enumerate(zip(old, new, strict=False)) if a != b),
+            min(len(old), len(new)),
+        )
+        if change < len(messages):
+            messages[change].first_change = True
+
+    tools_raw = (request or {}).get("tools") or []
+    tools = []
+    for t in tools_raw if isinstance(tools_raw, list) else []:
+        if isinstance(t, dict):
+            tools.append(
+                str((t.get("function") or {}).get("name") or t.get("name", "?"))
+            )
+    settings = {
+        k: v
+        for k, v in (request or {}).items()
+        if k not in ("messages", "tools", "system")
+    }
+    if isinstance(request, dict) and "system" in request:
+        messages.insert(
+            0,
+            Message(
+                index=-1,
+                role="system",
+                text=_text(request["system"]),
+                tool_calls=[],
+                tool_call_id=None,
+            ),
+        )
+
+    flags = []
+    if run is not None:
+        node_turns = [
+            Turn(r.text, r.calls, ())
+            for r in (reply_of(_response(reader, c)) for c in siblings)
+        ]
+        flags = sorted({c.kind for c in find_circles(node_turns) if at in c.turns})
+
+    return TurnView(
+        call=call,
+        number=at + 1,
+        run=run,
+        previous=before["id"] if before else None,
+        following=after["id"] if after else None,
+        request=request,
+        response=response,
+        reply=reply,
+        messages=messages,
+        unmatched=unmatched,
+        match_note=note,
+        dropped=[(i, dropped.get(i)) for i in call["dropped"]],
+        compacted=[(int(k), v) for k, v in call["compacted"].items()],
+        tools=tools,
+        tools_changed=compared and mine.get("tools") != theirs.get("tools"),
+        settings=settings,
+        compared=compared,
+        flags=flags,
+        raw_request=json.dumps(request, indent=2, ensure_ascii=False)
+        if request is not None
+        else "",
+        raw_response=json.dumps(response, indent=2, ensure_ascii=False)
+        if response is not None
+        else "",
+    )
+
+
+def _match(
+    call: dict[str, Any],
+    request: dict[str, Any] | None,
+    sent: list[SentEvent],
+    messages: list[Message],
+) -> tuple[list[SentEvent], str | None]:
+    """Each sent event beside the message it went into, found with the same
+    renderer that built the request; when that can't be done exactly, the
+    events are listed apart, with why."""
+    if not sent:
+        return [], None
+    if request is None:
+        return sent, "The request wasn't recorded (the call failed before it)."
+    if call.get("route") != "chat":
+        return sent, "Messages-route requests are shown beside their events, unmatched."
+    try:
+        events = [
+            StoredEvent(id=s.id, ts="", event=from_payload(s.type, s.payload))
+            for s in sent
+        ]
+    except (ValueError, TypeError):
+        return sent, "Some events didn't read as this version's event types."
+    first = messages[0] if messages else None
+    system = first.text if first is not None and first.role == "system" else None
+    renderer = OpenAIChatRenderer()
+    expected = renderer.render(events, None, "m", system)["messages"]
+    if len(expected) != len(messages):
+        return sent, (
+            f"Rendering the sent events gives {len(expected)} messages, the request "
+            f"has {len(messages)}; shown apart."
+        )
+    unmatched = []
+    for s, index in zip(sent, renderer.message_indexes(events, system), strict=True):
+        if index is None:
+            unmatched.append(s)
+        else:
+            messages[index].events.append(s)
+    return unmatched, None

nisse-ui/tests/test_ui_contract.py

@@ -0,0 +1,102 @@
+"""The page and the agents are released together (X6): these fail in the PR
+that would break the page, not in the operator's browser."""
+
+import threading
+from pathlib import Path
+
+import httpx
+import pytest
+from ui_fixtures import recorded, store_at
+
+from nisse_core.models import calls
+from nisse_core.state.store import StateStore as CoreStore
+from nisse_dev.state import StateStore as DevStore
+from nisse_review.state import StateStore as ReviewStore
+from nisse_ui import main as ui_main
+from nisse_ui.app import App
+from nisse_ui.sources import KNOWN_SCHEMAS, discover
+
+
+@pytest.mark.parametrize("store", [CoreStore, DevStore, ReviewStore])
+def test_every_agents_schema_is_one_the_page_knows(store: type[CoreStore]) -> None:
+    # An agent that moves its schema on must teach the page too.
+    assert store.SCHEMA_VERSION in KNOWN_SCHEMAS
+
+
+@pytest.mark.parametrize("store_class", [DevStore, ReviewStore])
+def test_each_agents_own_store_opens(
+    tmp_path: Path, store_class: type[CoreStore]
+) -> None:
+    store = store_at(tmp_path, store_class)
+    store.open_work_item("i1", title="Agent item", position="NEW", cause="t")
+    store.close()
+    app = App(discover([("a", tmp_path / "state.db")], []))
+    assert app.handle("/s/a/").status == 200
+    assert "Agent item" in app.handle("/s/a/item/i1").body.decode()
+
+
+def test_runs_the_benchmark_kept_are_sources(tmp_path: Path) -> None:
+    # As bench --keep-runs leaves them: <dir>/<task>-<id>/state.db + record.
+    for name in ("fix-bug-1a2b3c4d", "trace-bug-5e6f7a8b"):
+        _, store = recorded(tmp_path / "kept" / name)
+        store.close()
+    (tmp_path / "kept" / "not-a-run").mkdir()
+    sources = discover([], [tmp_path / "kept"])
+    assert sorted(s.name for s in sources) == [
+        "kept.fix-bug-1a2b3c4d",
+        "kept.trace-bug-5e6f7a8b",
+    ]
+    assert all(s.kind == "run" and s.calls_db.is_file() for s in sources)
+    assert sources[0].calls_db == calls.path_for(sources[0].state_db)
+
+
+def test_source_names_are_safe_and_unique(tmp_path: Path) -> None:
+    sources = discover(
+        [("dev agent/1", tmp_path / "a"), ("dev agent/1", tmp_path / "b")], []
+    )
+    assert [s.name for s in sources] == ["dev-agent-1", "dev-agent-1-2"]
+
+
+def test_the_server_listens_on_this_machine_and_sends_the_headers(
+    tmp_path: Path,
+) -> None:
+    source, store = recorded(tmp_path / "a")
+    store.close()
+    server = ui_main.ThreadingHTTPServer(
+        ("127.0.0.1", 0), ui_main.handler_for(App([source]))
+    )
+    thread = threading.Thread(target=server.serve_forever, daemon=True)
+    thread.start()
+    try:
+        port = server.server_address[1]
+        response = httpx.get(f"http://127.0.0.1:{port}/s/agent/item/w1")
+        assert response.status_code == 200
+        assert "Fix the parser" in response.text
+        assert "default-src 'none'" in response.headers["content-security-policy"]
+        assert response.headers["x-content-type-options"] == "nosniff"
+        assert response.headers["server"].startswith("nisse-ui")
+    finally:
+        server.shutdown()
+        server.server_close()
+
+
+def test_the_command_line_defaults_to_this_machine_only(
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    assert ui_main._source("dev=/var/lib/nisse-dev/state.db") == (
+        "dev",
+        Path("/var/lib/nisse-dev/state.db"),
+    )
+    with pytest.raises(Exception, match="NAME=STATE_DB"):
+        ui_main._source("no-equals")
+
+    class Bound(Exception):
+        pass
+
+    def server(address: tuple[str, int], handler: object) -> None:
+        raise Bound(address)
+
+    monkeypatch.setattr(ui_main, "ThreadingHTTPServer", server)
+    with pytest.raises(Bound) as bound:
+        ui_main.main([])
+    assert bound.value.args[0] == ("127.0.0.1", 8765)

nisse-ui/tests/test_ui_pages.py

@@ -0,0 +1,316 @@
+"""The walkthrough (X6, M6.6b): an item's steps, its runs' turns, and each
+turn's request read against the log it was made from."""
+
+import hashlib
+import sqlite3
+from pathlib import Path
+
+import pytest
+from ui_fixtures import TOKEN, circling, recorded
+
+from nisse_core.log.canonical import UserMessage
+from nisse_core.models import calls
+from nisse_ui import walk
+from nisse_ui.app import App
+from nisse_ui.sources import Source, StateReader, call_record
+
+
+@pytest.fixture
+def agent(tmp_path: Path) -> Source:
+    source, store = recorded(tmp_path / "agent")
+    store.close()
+    return source
+
+
+def page(app: App, path: str, status: int = 200) -> str:
+    response = app.handle(path)
+    assert response.status == status, response.body.decode()[:500]
+    return response.body.decode()
+
+
+def view(source: Source, call_id: int) -> walk.TurnView:
+    with StateReader(source.state_db) as state, call_record(source) as reader:
+        assert reader is not None
+        found = walk.turn(state, reader, call_id)
+    assert found is not None
+    return found
+
+
+def steps(source: Source, item: str | None) -> walk.Walkthrough:
+    with StateReader(source.state_db) as state, call_record(source) as reader:
+        return walk.walkthrough(state, reader, item)
+
+
+# --- the way in -------------------------------------------------------------------
+
+
+def test_the_sources_and_an_agents_items_are_listed(agent: Source) -> None:
+    app = App([agent])
+    home = page(app, "/")
+    assert "/s/agent/" in home and ">1<" in home  # one work item
+    items = page(app, "/s/agent/")
+    assert "Fix the parser" in items and "/s/agent/item/w1" in items
+    assert "/s/agent/item/-" in items  # the agent-level log
+
+
+# --- the walkthrough --------------------------------------------------------------
+
+
+def test_an_items_steps_hold_its_runs_turns_and_what_the_orchestrator_said(
+    agent: Source,
+) -> None:
+    found = steps(agent, "w1")
+    kinds = [kind for kind, _ in found.timeline]
+    assert kinds == ["event", "event", "run"]  # the restatement, "go", the run
+    [run] = [obj for kind, obj in found.timeline if kind == "run"]
+    assert run.run["outcome"] == "wait"
+    assert [t.number for t in run.turns] == [1, 2, 3]
+    # The correction for the prose reply came during the run: it's shown
+    # inside it, between the turns it fell between.
+    inner = [kind for kind, _ in run.entries]
+    assert inner == ["turn", "turn", "event", "turn"]
+    assert any("prose" in told for told in run.turns[2].told)
+    assert run.turns[0].reply.calls == (("read_file", '{"path": "parser.py"}'),)
+    assert run.turns[1].reused == "280 of 340"
+    html = page(App([agent]), "/s/agent/item/w1")
+    assert "turn 3" in html and "reused 330 of 350" in html
+
+
+def test_agent_level_calls_have_their_own_log(agent: Source) -> None:
+    found = steps(agent, None)
+    [run] = [obj for kind, obj in found.timeline if kind == "run"]
+    assert (run.run["kind"], run.run["role"]) == ("classification", "classifier")
+    assert "harmless" in page(App([agent]), "/s/agent/item/-")
+
+
+def test_work_from_before_recording_has_its_steps_but_no_requests(
+    tmp_path: Path,
+) -> None:
+    source, store = recorded(tmp_path / "a")
+    # The agent restarts: a fresh, empty record; the log persists.
+    calls.CallRecorder(source.calls_db).close()
+    store.close()
+    found = steps(source, "w1")
+    assert found.before_record
+    # The restatement, "go" and the correction: steps, with no runs to hold them.
+    assert [kind for kind, _ in found.timeline] == ["event", "event", "event"]
+    html = page(App([source]), "/s/agent/item/w1")
+    assert "Recording began" in html
+    assert "All 8 events" in html  # the log is all still there
+
+
+def test_without_a_call_record_the_log_is_shown(tmp_path: Path) -> None:
+    source, store = recorded(tmp_path / "a")
+    store.close()
+    source.calls_db.unlink()
+    html = page(App([source]), "/s/agent/item/w1")
+    assert "No call record" in html and "All 8 events" in html
+    page(App([source]), "/s/agent/call/1", 404)
+
+
+def test_a_run_going_in_circles_is_flagged(tmp_path: Path) -> None:
+    source = circling(tmp_path / "c")
+    found = steps(source, "pr-7")
+    [run] = [obj for kind, obj in found.timeline if kind == "run"]
+    [circle] = run.circles
+    assert (circle.kind, circle.turns) == ("repeated reply", (0, 1, 2, 3))
+    assert run.turns[0].flags == ["repeated reply"] and not run.turns[4].flags
+    assert "Going in circles: repeated reply at turns 1, 2, 3, 4" in page(
+        App([source]), "/s/circling/item/pr-7"
+    )
+    assert view(source, 2).flags == ["repeated reply"]
+
+
+# --- one turn ---------------------------------------------------------------------
+
+
+def test_each_message_is_shown_beside_the_log_events_it_came_from(
+    agent: Source,
+) -> None:
+    turn = view(agent, 2)
+    assert turn.match_note is None and turn.unmatched == []
+    roles = [m.role for m in turn.messages]
+    assert roles == ["system", "user", "assistant", "tool"]
+    # The restatement and "go" fold into one user message.
+    assert [s.id for s in turn.messages[1].events] == [1, 2]
+    assert [s.id for s in turn.messages[2].events] == [3]
+    assert [s.id for s in turn.messages[3].events] == [4]
+    assert all(s.tags == ["unchanged"] for m in turn.messages for s in m.events)
+    assert calls.NOTICE in turn.messages[0].text
+
+
+def test_what_changed_since_the_turn_before_is_marked(agent: Source) -> None:
+    first, second = view(agent, 1), view(agent, 2)
+    assert not first.compared and not any(m.new for m in first.messages)
+    assert second.compared
+    assert [m.new for m in second.messages] == [False, False, True, True]
+    assert [m.first_change for m in second.messages] == [False, False, True, False]
+    assert not second.tools_changed
+    assert (second.previous, second.following) == (1, 3)
+
+
+def test_the_turn_page_shows_the_reply_reasoning_and_raw_json(agent: Source) -> None:
+    html = page(App([agent]), "/s/agent/call/1")
+    assert "First, read the parser." in html  # the reasoning
+    assert "Request JSON, exactly as sent" in html
+    assert "local-backing" in html  # the model that answered
+    assert "reused" not in html or "0 of 300" in html
+
+
+def test_how_rendering_changed_an_event_is_named() -> None:
+    call = {"shortened": {"5": 1200}}
+    logged = walk.Event(5, "t", "tool_result", {"result": "long"}, "w", "driver")
+    sent = {"result": "lo"}
+    assert walk._tags([5, "driver", "tool_result", "h"], sent, logged, call) == [
+        "shortened by 1,200 characters"
+    ]
+    told = walk.Event(6, "t", "tool_call", {"tool": "x"}, "w", "helper")
+    narrated = {"text": "x → ok", "source": "view:helper"}
+    assert walk._tags(
+        [6, "helper", "user_message", "h"], narrated, told, {"shortened": {}}
+    ) == ["narrated from tool call by helper"]
+    fact = walk.Event(8, "t", "fact", {"text": "agreed"}, "w", "orchestrator")
+    as_said = {"text": "[orchestrator] agreed", "source": "view:orchestrator"}
+    assert walk._tags(
+        [8, "orchestrator", "user_message", "h"], as_said, fact, {"shortened": {}}
+    ) == ["labelled for this role (a fact by orchestrator)"]
+    said = walk.Event(
+        7, "t", "user_message", {"text": "hi", "source": "m"}, "w", "operator"
+    )
+    labelled = {"text": "[operator, matrix] hi", "source": "view:operator"}
+    assert walk._tags(
+        [7, "operator", "user_message", "h"], labelled, said, {"shortened": {}}
+    ) == ["labelled for this role"]
+    assert walk._tags(
+        [0, "harness", "fact", "h"], {"text": "x"}, None, {"shortened": {}}
+    ) == ["made for this call, not in the log"]
+    assert walk._tags(
+        [9, "driver", "compaction", "h"], {"replaces": [2, 8]}, None, {"shortened": {}}
+    ) == ["compaction of events 2–8"]
+
+
+def test_a_reply_reads_from_either_route() -> None:
+    chat = {
+        "choices": [
+            {
+                "message": {
+                    "content": "ok",
+                    "reasoning_content": "hm",
+                    "tool_calls": [{"function": {"name": "f", "arguments": "{}"}}],
+                },
+                "finish_reason": "tool_calls",
+            }
+        ]
+    }
+    assert walk.reply_of(chat) == walk.Reply("ok", "hm", (("f", "{}"),), "tool_calls")
+    messages = {
+        "content": [
+            {"type": "thinking", "thinking": "hm"},
+            {"type": "text", "text": "ok"},
+            {"type": "tool_use", "name": "f", "input": {"a": 1}},
+        ],
+        "stop_reason": "tool_use",
+    }
+    assert walk.reply_of(messages) == walk.Reply(
+        "ok", "hm", (("f", '{"a": 1}'),), "tool_use"
+    )
+    assert walk.reply_of("garbage") == walk.Reply()
+
+
+# --- untrusted text and read-only -------------------------------------------------
+
+
+def test_everything_shown_is_escaped_and_no_script_may_run(agent: Source) -> None:
+    app = App([agent])
+    for path in (
+        "/s/agent/item/w1",
+        "/s/agent/call/2",
+        "/s/agent/call/3",
+        "/s/agent/event/4",
+    ):
+        response = app.handle(path)
+        html = response.body.decode()
+        assert "<script>alert" not in html
+        assert "&lt;script&gt;alert" in html
+        assert "&lt;/pre&gt;&lt;/details&gt;" in html  # can't close the page's own
+        csp = response.headers["Content-Security-Policy"]
+        assert "default-src 'none'" in csp and "script-src" not in csp
+        assert TOKEN not in html
+
+
+def _digests(root: Path) -> dict[str, str]:
+    """Each file's content, except SQLite's shared-memory index, which
+    readers of a live WAL database take part in by design."""
+    return {
+        p.name: ""
+        if p.name.endswith("-shm")
+        else hashlib.sha256(p.read_bytes()).hexdigest()
+        for p in sorted(root.iterdir())
+        if p.is_file()
+    }
+
+
+def test_browsing_reads_only_and_leaves_no_lock_while_the_agent_writes(
+    tmp_path: Path,
+) -> None:
+    source, store = recorded(tmp_path / "a")  # the store stays open, as live
+    before = _digests(tmp_path / "a")
+    app = App([source])
+    for path in (
+        "/",
+        "/s/agent/",
+        "/s/agent/item/w1",
+        "/s/agent/item/-",
+        "/s/agent/call/1",
+        "/s/agent/call/2",
+        "/s/agent/event/1",
+    ):
+        page(app, path)
+    # No file changed, and none was created: the closed call record has no
+    # -wal or -shm, and opening it made none.
+    assert _digests(tmp_path / "a") == before
+    assert not Path(f"{source.calls_db}-wal").exists()
+    # The agent can still write at once: nothing here holds a lock.
+    store.transcript("w1", "operator").append(UserMessage(text="more", source="m:2"))
+    store.close()
+    assert "more" in page(app, "/s/agent/item/w1")
+
+
+# --- versions -----------------------------------------------------------------------
+
+
+def test_a_store_of_an_unknown_version_is_named_not_guessed(agent: Source) -> None:
+    with sqlite3.connect(agent.state_db) as conn:
+        conn.execute("UPDATE meta SET value = '99' WHERE key = 'schema_version'")
+    html = page(App([agent]), "/s/agent/item/w1", 409)
+    assert "schema 99, not known to this page" in html
+    assert "schema 99" in page(App([agent]), "/")
+
+
+def test_a_call_record_of_an_unknown_layout_leaves_the_log_readable(
+    agent: Source,
+) -> None:
+    with sqlite3.connect(agent.calls_db) as conn:
+        conn.execute("UPDATE meta SET value = '2' WHERE key = 'layout_version'")
+    html = page(App([agent]), "/s/agent/item/w1")
+    assert "call record layout 2" in html and "All 8 events" in html
+    page(App([agent]), "/s/agent/call/1", 409)
+
+
+def test_item_data_that_doesnt_parse_still_renders(agent: Source) -> None:
+    with sqlite3.connect(agent.state_db) as conn:
+        conn.execute("UPDATE work_items SET data = 'not json', position = 'NEW_STATE'")
+    html = page(App([agent]), "/s/agent/item/w1")
+    assert "not json" in html and "NEW_STATE" in html
+    assert "NEW_STATE" in page(App([agent]), "/s/agent/")
+
+
+def test_unknown_paths_are_not_found(agent: Source) -> None:
+    app = App([agent])
+    page(app, "/s/nobody/", 404)
+    page(app, "/s/agent/item/nope", 404)
+    page(app, "/s/agent/call/999", 404)
+    page(app, "/s/agent/event/999", 404)
+    page(app, "/s/agent/call/x", 404)
+    page(app, "/etc/passwd", 404)
+    assert app.handle("/static/style.css").content_type.startswith("text/css")

nisse-ui/tests/ui_fixtures.py

@@ -0,0 +1,149 @@
+"""Stores written by the agents' own code, for the page to read (X6): a real
+state store and a real call record from a driver run against a fake
+LiteLLM, so a change in nisse-core that breaks the page fails here."""
+
+import io
+import json
+from pathlib import Path
+from typing import Any
+
+import httpx
+
+from nisse_core.log.canonical import Fact, UserMessage
+from nisse_core.loop.driver import Driver
+from nisse_core.loop.tools import tool
+from nisse_core.models import calls
+from nisse_core.models.context import BudgetedClient
+from nisse_core.models.llm import LiteLLMClient
+from nisse_core.oplog import OpLog
+from nisse_core.state.store import StateStore
+from nisse_ui.sources import Source
+
+TOKEN = "sk-secret-litellm-token"
+HOSTILE = "<script>alert('x')</script></pre></details>"
+READ = tool("read_file", "read a file", path="the file")
+POST = tool("post_comment", "post a comment", body="the comment")
+FINISH = tool("finish", "finish the work", summary="what was done")
+
+
+def reply(
+    content: str = "",
+    *,
+    call: tuple[str, dict[str, Any]] | None = None,
+    reasoning: str = "",
+    timings: dict[str, int] | None = None,
+) -> dict[str, Any]:
+    message: dict[str, Any] = {"role": "assistant", "content": content}
+    if reasoning:
+        message["reasoning_content"] = reasoning
+    if call:
+        message["tool_calls"] = [
+            {
+                "id": f"x{abs(hash(json.dumps(call)))}",
+                "type": "function",
+                "function": {"name": call[0], "arguments": json.dumps(call[1])},
+            }
+        ]
+    data: dict[str, Any] = {
+        "model": "local-backing",
+        "choices": [{"message": message, "finish_reason": "stop"}],
+        "usage": {"prompt_tokens": 120, "completion_tokens": 7},
+    }
+    if timings is not None:
+        data["timings"] = timings
+    return data
+
+
+class Server:
+    """A fake LiteLLM answering each request in turn."""
+
+    def __init__(self, *answers: dict[str, Any]) -> None:
+        self.answers = list(answers)
+
+    def __call__(self, request: httpx.Request) -> httpx.Response:
+        data = self.answers.pop(0) if self.answers else reply("ok")
+        return httpx.Response(200, json=data)
+
+
+def client(server: Server, recorder: calls.CallRecorder) -> BudgetedClient:
+    inner = LiteLLMClient(
+        "https://litellm.test", TOKEN, transport=httpx.MockTransport(server)
+    )
+    return BudgetedClient(inner, lambda m: (32768, 1024), call_recorder=recorder)
+
+
+def store_at(root: Path, store_class: type[StateStore] = StateStore) -> StateStore:
+    return store_class(root / "state.db", oplog=OpLog("test", io.StringIO()))
+
+
+def recorded(root: Path) -> tuple[Source, StateStore]:
+    """One work item, one driver run of three turns: a tool call whose
+    result is hostile text, a prose reply the driver corrects, then the
+    finish. And one agent-level call. The store stays open, as a live
+    agent's does."""
+    root.mkdir(parents=True, exist_ok=True)
+    recorder = calls.CallRecorder(calls.path_for(root / "state.db"))
+    store = store_at(root)
+    store.open_work_item("w1", title="Fix the parser", position="RUNNING", cause="t")
+    store.transcript("w1", "orchestrator").append(
+        Fact(text="The operator agreed to this restatement: fix the parser.")
+    )
+    store.transcript("w1", "operator").append(UserMessage(text="go", source="m:1"))
+    server = Server(
+        reply(
+            call=("read_file", {"path": "parser.py"}),
+            reasoning="First, read the parser.",
+            timings={"cache_n": 0, "prompt_n": 300},
+        ),
+        reply(
+            "I believe the parser is fine now.",
+            timings={"cache_n": 280, "prompt_n": 60},
+        ),
+        reply(
+            call=("finish", {"summary": "fixed"}),
+            timings={"cache_n": 330, "prompt_n": 20},
+        ),
+    )
+    Driver(client(server, recorder), "local").run(
+        store.transcript("w1", "driver"),
+        system="You are the driver.",
+        tools=[READ, FINISH],
+        waiting=("finish",),
+        workspace=None,
+        handlers={"read_file": lambda args: (f"contents {HOSTILE}", True)},
+    )
+    store.transcript(None, "operator").append(UserMessage(text="hello", source="m:9"))
+    with calls.run(recorder, work_item=None, role="classifier", kind="classification"):
+        client(Server(reply("harmless")), recorder).complete(
+            store.transcript(None, "operator").read(), None, "local", system="Classify."
+        )
+    recorder.close()
+    return Source("agent", root / "state.db", "agent"), store
+
+
+def circling(root: Path) -> Source:
+    """A run that posts the same comment over and over, as Flash-Next did
+    on 2026-10-24, until the finish."""
+    root.mkdir(parents=True, exist_ok=True)
+    recorder = calls.CallRecorder(calls.path_for(root / "state.db"))
+    store = store_at(root)
+    store.open_work_item("pr-7", title="Review #7", position="RUNNING", cause="t")
+    store.transcript("pr-7", "operator").append(UserMessage(text="review", source="m"))
+    answers = [
+        reply(call=("post_comment", {"body": f"Duplicate, please disregard ({n})."}))
+        for n in range(4)
+    ]
+    Driver(
+        client(Server(*answers, reply(call=("finish", {"summary": "x"}))), recorder),
+        "local",
+    ).run(
+        store.transcript("pr-7", "driver"),
+        system="You review.",
+        tools=[POST, FINISH],
+        waiting=("finish",),
+        workspace=None,
+        handlers={"post_comment": lambda args: ("posted", True)},
+    )
+    recorder.close()
+    store.close()
+    return Source("circling", root / "state.db", "agent")

pyproject.toml

@@ -1,5 +1,5 @@
 [tool.uv.workspace]
-members = ["nisse-core", "nisse-dev", "nisse-ops", "nisse-review"]
+members = ["nisse-core", "nisse-dev", "nisse-ops", "nisse-review", "nisse-ui"]
 
 [dependency-groups]
 dev = [
@@ -14,6 +14,7 @@ testpaths = [
     "nisse-dev/tests",
     "nisse-ops/tests",
     "nisse-review/tests",
+    "nisse-ui/tests",
     "tests",
 ]
 # The seed is a test project's own code, pushed to each run's repository.
@@ -33,4 +34,4 @@ extend-exclude = ["tests/integration/seed"]  # a test project's own code
 extend-select = ["I"]
 
 [tool.ruff.lint.isort]
-known-first-party = ["nisse_core", "nisse_dev", "nisse_ops", "nisse_review"]
+known-first-party = ["nisse_core", "nisse_dev", "nisse_ops", "nisse_review", "nisse_ui"]

scripts/benchmark.py

@@ -66,6 +66,7 @@ def run(args: argparse.Namespace) -> int:
                     host=host,
                     note=args.note,
                     commit=commit,
+                    keep=args.keep_runs,
                 )
                 append(out, record)
                 verdict = "pass" if record.success else f"FAIL ({record.outcome})"
@@ -113,6 +114,11 @@ def main() -> int:
         "--note", default="", help='how the model was served, e.g. "vLLM 0.29, AWQ"'
     )
     run_p.add_argument("--config", help="agent config (default: NISSE_CONFIG)")
+    run_p.add_argument(
+        "--keep-runs",
+        type=Path,
+        help="keep each run's state store and call record here, for the status page",
+    )
     run_p.set_defaults(handler=run)
 
     report_p = sub.add_parser("report", help="compare stored results")

uv.lock

@@ -8,6 +8,7 @@ members = [
     "nisse-dev",
     "nisse-ops",
     "nisse-review",
+    "nisse-ui",
 ]
 
 [manifest.dependency-groups]
@@ -112,6 +113,131 @@ wheels = [
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 ]
 
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+
 [[package]]
 name = "nisse-core"
 version = "0.1.0"
@@ -166,6 +292,21 @@ dependencies = [
 [package.metadata]
 requires-dist = [{ name = "nisse-core", editable = "nisse-core" }]
 
+[[package]]
+name = "nisse-ui"
+version = "0.1.0"
+source = { editable = "nisse-ui" }
+dependencies = [
+    { name = "jinja2" },
+    { name = "nisse-core" },
+]
+
+[package.metadata]
+requires-dist = [
+    { name = "jinja2", specifier = ">=3.1" },
+    { name = "nisse-core", editable = "nisse-core" },
+]
+
 [[package]]
 name = "packaging"
 version = "26.3"