learn-from-conversationslisted

# Learn from conversations ## Overview Recurring work should stop being rediscovered. This skill turns conversation history into either a new skill or a targeted edit to the existing skill that already owns the topic. The deliverable is fewer repeated explanations, not more skills — a library that grows every pass is a failure mode, not progress. Two instruments ship with it: - `scripts/audit.py` — library health facts (sizes, truncated descriptions, usage, ghost records). Draws no conclusions. - `scripts/harvest.py` — the per-turn join: which skills the model _chose_ before an owner correction. Read `references/correction-rate-confounds.md` before quoting any number it prints. ## When to Use - Periodically, over conversation history since the last checkpoint. - After a stretch of work where the same thing was explained more than once. - When an owner correction reveals a procedure that was never written down. Do **not** use this to run a library-wide cleanup — sizes, retirement, consolidation, description rewrites. That is a different job with a different risk profile. ## Procedure 1. **Establish the checkpoint.** Harvest only episodes newer than the last pass. Record the new checkpoint only after findings are saved, so an interrupted run repeats rather than skips. 2. **Read episodes, not keyword hits.** A match is a pointer to a conversation you still have to read. Use session metadata to separate owner dialogue from cron prompts, delegation requ