| name | lessons |
| description | How to propose and query distilled lessons (the experiential memory). Only project-steward persists; every other agent proposes/queries. Use when you discover a durable lesson or need prior experience for the current task. |
Lessons — distilled experiential memory
Store: .claude/memory/lessons.jsonl (local, capped 200, archived on overflow). Only project-steward writes.
Query (any agent, on-demand)
node .claude/hooks/lessons.mjs query --domain export
node .claude/hooks/lessons.mjs query --category Performance
node .claude/hooks/lessons.mjs query --text "pagination"
Returns only matching ≤5-line lessons — never bulk-loaded. The review-gate auto-queries by touched domain/globs and folds matches into its prompt.
Propose (any agent)
Surface as: LESSON · <category> · Context: … · Decision: … · Outcome: … (≤5 lines). project-steward dedupes & persists.
Tag the memory type in --tags — a free-form convention (not enforced by lessons.mjs), following the 2026 agent-memory taxonomy: episodic (a specific past event/fix), semantic (a durable fact/convention), or procedural (a workflow / review convention / test command / tool-use habit). Procedural lessons are the highest-leverage — capture "how we do X here."
Categories (exactly one)
Architecture decision · Failed approach · Proven approach · Performance · Security · ATS · Scraping · AI-provider · Export · Testing discovery.
Rules
- Distilled lessons only — never raw conversations / task-histories / review-outputs.
Context · Decision · Outcome, ≤5 lines.- Dedupe on add; cap 200 active; archive the rest.
- An Architecture-decision lesson that graduates to an ADR (
docs/knowledge/decision-records/) is removed from the log — the ADR becomes its single source.
- Context priority stays: graphify → source → docs/knowledge → lessons.
