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Session 8
Date: 2026-04-07 Focus: Close #54 — wire confidence fields into write_cache tool schema Duration estimate: ~15 minutes
What was done
- Audited #54 against current code. Found the work was 90% already done:
_DIR_SYSTEM_PROMPTalready instructs the agent to setconfidence/confidence_reason(landed earlier in commit80f8f88, issue #2). The only remaining gap was thewrite_cachetool'sdataschema description in_DIR_TOOLS(ai.py:246), which still listed only the legacy fields. - Branched
fix/issue-54-write-cache-tool-desc, addedconfidenceandconfidence_reasonto the tool's data field description plus a one-line pointer back to the system prompt for calibration. - Tests:
python3 -m unittest discover -s tests/→ 168 pass. - PR archeious/luminos#61 → merged
--no-ff(4ef97c5) → branch deleted local + remote → PR closed → issue #54 closed. - Phase 1 milestone is now 4/4 complete.
Discoveries and observations
- All MCP writes worked end-to-end as
claude-code— PR create, PR close, issue close all went through the gitea MCP without falling back to REST. The Session 7 credential overhaul is paying off immediately. - Models bind tightly to tool schema descriptions; instructing them only via the system prompt and not in the tool schema is a fragile pattern. Worth remembering as a general principle for future tool-bound work.
Decisions made and why
- Did not change the float-vs-categorical confidence representation even
though the issue notes categorical is "probably more reliable." That's a
separate calibration experiment, not a prerequisite for closing #54.
Banded floats with explicit thresholds (high ≥ 0.8, medium 0.5–0.8, low
< 0.5) is the current contract; changing it touches
low_confidence_entriesand the eventual Phase 8 refinement signal. - Deferred the manual
--aiverification run mentioned in the issue's acceptance criteria. The schema change is straightforward and the unit tests cover the cache validation path; doing a real API run for a one-line schema doc tweak would burn budget for low marginal value. We'll pick it up the next time we're running--aifor any reason.
Raw thinking
- Phase 1 closing was a tiny session, but it's a real milestone closure — worth marking. The remaining backlog from Session 5 follow-ups (#55, #56, #57) is now the only thing standing between us and Phase 3 proper.
- The model does have a tendency to skip optional schema fields if the
description doesn't make them feel important. Worth verifying after the
next
--airun that confidence is actually landing — if it's still inconsistent, may need to make the fieldrequiredin the cache schema rather than just documenting it. - The categorical-vs-float question is still open. Filing it as a separate Phase 8 prerequisite would be cleaner than letting it haunt #54.
- This is the second time the gitea MCP got used for an end-to-end write
workflow (PR create + close + issue close) and it just worked. The
collaborator-permission caveat in
~/.claude/CLAUDE.mdis the only friction left.
What's next
In priority order:
- #57 — refactor
_run_dir_loopbefore Phase 3 dynamic turn allocation lands. Prerequisite cleanup, small. - #56 — dedupe
_TOOL_DISPATCH/_DIR_TOOLSregistration. Small, satisfying. - #55 — unit test coverage for ai.py pure helpers. Foundation for Phase 3 confidence work.
- Phase 3 proper (#19–#29 cluster).