4 Commits

Include renames

Author	SHA1	Message	Date
dongarandClaude Opus 5.5	3cf4cefacd	Rename the delegate and consultant roles to helper and expert ... Architecture L9's role names, for the two roles with a direct counterpart: the delegation role is now 'helper' and the ask_expert role 'expert', in RoleMap, configuration (roles.helper, roles.expert), recorded events and tests. 'planner' and 'executor' stay distinct for now; they become 'driver' when the new loop merges them (Development Plan M2.3). Configurations must rename their keys: nisse-dev.example.yaml and tests/integration/nisse-test.yaml are updated here. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PPQ14L3LikyefCMFBqEbKE	2026-10-01 23:04:37 +00:00
dongarandClaude Opus 5.5	1ad0b2147d	Retire the old build spec, and point every reference at the architecture (M0.1) ... Development Plan M0.1. Every section reference in code, tests, specs/, the example config, the tuning guide, and the CLAUDE.md and README files now cites docs/Architecture.md (P, L, D, O, X, Q) instead of the old spec's A-H, and docs/Architecture-Build-Spec.md is deleted (git keeps it). The plan's old-to-new table goes with it. Mostly mechanical, with a per-site choice where one old section split: A4 became L2 where it meant stop/abandon/the loop and L3 where it meant approvals; A10 became L6 in the context-budget code and L7 elsewhere; B2 became D4 for outbound Gitea and publishing and D5 for review intake; 'A3 step N' became the matching step of L8's boot sequence. Comments describing behaviour the architecture drops (planning always escalating, thresholds tuned at an old build step) now describe the current code and point at the Development Plan. docs/Architecture.md gains one line the rewrite missed: intake outages delay but never fail work (old B2), now in L5, where the poller and Matrix code cite it. Comments and docs only; no behaviour change. Co-Authored-By: Claude Opus 5.5 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01PPQ14L3LikyefCMFBqEbKE	2026-10-01 00:17:48 +00:00
dongarandClaude Opus 5	2b7651fb37	Add ask_expert and eval capture (A14/A16) — step 7c ... Completes step 7. - expert.py: one stateless call for a question needing no repo access. Structured output is contracted at the prompt level, since vendors differ on JSON enforcement, so the reply is parsed and validated locally with one retry — tolerating a fenced code block, because models wrap JSON habitually, but not missing fields - The per-task budget is counted from the canonical log rather than memory, so it survives a restart and cannot hand a circling executor a fresh allowance. Exhaustion raises rather than answering: a caller out of consults should get on with the work or escalate - Consults are recorded as delegation_started/completed with role consultant. A16 asks for a "consult/delegation eval set", and reusing the composite events gets consult evaluation for free rather than inventing a parallel record - evals.py pairs starts with completions into eval records, with verdicts kept outside the canonical log: the log records what happened, a verdict is a later judgement about it, and judgements get revised. Schema v3 adds the outcomes table, so a v1 store now traverses two migrations — a better exercise of the hook than one - ask_expert is offered to the executor as a tool only when a desk is configured, in addition to the observable escalation triggers and never instead of them (A12). Consulting is not mutating, so a completion claim backed only by consults is still challenged Found live: passing an empty message list and putting the question in the system prompt fails outright — the Messages API requires at least one non-system message. The question now travels as a synthesised user message that is never appended to the log, which keeps the consult stateless while remaining a valid request. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>	2026-09-08 19:48:13 +00:00
dongarandClaude Fable 5	ac81dd6234	Add canonical event log and renderer skeleton (A10) ... Build-order step 4, sequenced before the LLM client (step 3) because the client interface consumes the canonical log. - canonical.py: typed events for the full A10 table (user_message through compaction); canonical tool-call IDs minted locally, provider IDs never a join key; strict payload validation on load - StateStore: canonical_events table via schema v2 — the first real migration, exercised in a test against a hand-built v1 database — with append_event/read_events on the same fsync-per-commit path - render.py: request bodies rendered from the log at call time; first adapter targets the OpenAI-compatible shape of LiteLLM's normalized route; compaction events replace their id range at render time while staying in the durable log - Crash integration test now also verifies transcript appends survive process death Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>	2026-09-06 19:51:58 +00:00