The call record: every model call, for the operator's study (M6.6a)

nisse-core records each model call of every agent into a file beside its
state store (<state>.calls.db), for the status page (L7, X6):

- the request body exactly as sent (never headers), the raw response with
  its reasoning, the model asked and the one that answered, time, tokens
  and llama-server's own prompt reuse (timings.cache_n);
- its work item, role, run and purpose: Driver.run and nisse-dev's
  delegation loop open runs, nested; compaction, expert consults, the
  classifier and the go-ahead reader label their calls;
- provenance, worked out in BudgetedClient by comparing the events at
  each stage: each event sent with its log id and content as sent, which
  a compaction replaced, which fitting shortened (by how much) and
  dropped.

Content is stored once by hash, compressed. It is diagnostic only: the
agent never reads it, a failed write is logged once and recording stops
while the call goes on, and the file is deleted when the agent starts,
so its layout never migrates; CallReader refuses a layout it doesn't
know. While recording, the system prompt ends with one sentence saying
so. `call_record: false` in either agent's YAML turns it off.

The benchmark records each run beside that run's own state store, and
`--keep-runs DIR` keeps both for the page.

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

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