Agent Learning Log

Priority: P1 (OPERATIONAL)

Write a structured mistake entry to AGENTS_LEARNING.md in the project root before retrying any corrected action.

Protocol

1. Detect signal — identify which surface triggered this skill:
   • Pre-write violation — a common-feedback-reporter violation block was emitted with Auto-fixed: YES
   • User correction — user used correction language mid-session
   • Session retrospective — a correction loop was found during common-session-retrospective
2. Read AGENTS_LEARNING.md — count existing ## Agent Learning Log: Iteration headers → N
3. Append entry — write Iteration #(N+1) using the format in Log Entry Format
4. Continue — proceed with the corrected action (non-blocking)

Guidelines

• One entry per correction event — not one per file or per task
• Concrete mistakes only — name the specific file, rule, or action that was wrong
• The "Better Approach" must be actionable — state what to do, not what to avoid
• Create file if missing — bootstrap with the header from Log Entry Format
• Never skip for "minor" corrections — all corrections are learning signals

Anti-Patterns

• No vague mistakes: "I made a mistake" → name the specific pattern or rule violated
• No skipping the log: Even if already in a hurry to fix, append the entry first (it takes <10 seconds)
• No duplicate entries: One correction event = one entry, even if multiple files were affected
• No overwriting: Always append to the bottom; never edit past entries

References

• Log Entry Format — full entry template + AGENTS_LEARNING.md bootstrap