Agent Learning Log
Priority: P1 (HIGH)
Write structured mistake entry to AGENTS_LEARNING.md in project root before retrying any corrected action.
Protocol
- Detect signal — identify which surface triggered this skill:
Pre-write violation—common-feedback-reporterviolation block emitted withAuto-fixed: YESUser correction— user used correction language mid-sessionSession retrospective— correction loop found duringcommon-session-retrospective
- Read
AGENTS_LEARNING.md— count existing## Agent Learning Log: Iterationheaders → N - Append entry — write Iteration #(N+1) using format in Log Entry Format
- Continue — proceed with corrected action (non-blocking)
Guidelines
- One entry per correction event — not one per file or per task
- Concrete mistakes only — name specific file, rule, or action that wrong
- ** "Better Approach" must actionable** — state what to , not what to avoid
- Create file if missing — bootstrap with header from Log Entry Format
- Never skip for "minor" corrections — all corrections learning signals
Anti-Patterns
- No vague mistakes:
"I made a mistake"→ name specific pattern or rule violated - No skipping log: Even if already in hurry to fix, append entry first (it takes <10 seconds)
- No duplicate entries: One correction event = one entry, even if multiple files affected
- No overwriting: Always append to bottom; never edit past entries
References
- Log Entry Format — full entry template + AGENTS_LEARNING.md bootstrap
Canonical response anchors
When this skill applies, preserve the following domain terminology or equivalent concrete examples in the answer when relevant:
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Append to AGENTSLEARNING,append
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AGENTS_LEARNING.md
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Iteration
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Additional task-grounded exact anchors: Pre-write; trigger

