Lesson learned

<!-- AI-QUICK-REF ## /lesson-learned — Quick Reference - **Modes:** auto | review | session - **Output:** 1-2 lessons -> memory file (feedback/project type) or CLAUDE.md - **Rule:** Max 2 lessons per invocation, always anchored to real files - **No duplicates:** Read memory directory and MEMORY.md index, only add new items - **Format:** Problem -> Root Cause -> Solution -> Why -> How to apply -> Reference - **No noise:** Only insights that will save time in the future -->

/lesson-learned — Extract and Save Learnings

Analyzes current work (git diff, errors, fixes) and extracts 1-2 concrete learnings. Saves them as memory files in the file-based memory system and references them in the MEMORY.md index.

Problem

Errors and learnings are only captured manually. After a debugging session or fix round, one often forgets to write down the insights. Next time, the same mistake is repeated.

Memory System

The memory system is file-based:

• Memory directory: .claude/projects/.../memory/ (project-specific)
• MEMORY.md: Index file with links to individual memory files
• Memory files: Individual .md files with frontmatter (name, description, type)
• Each lesson is saved as a standalone memory file, not directly in MEMORY.md

Modes

Mode	Trigger	Description
auto	/lesson-learned auto	After a fixing round: analyze git diff, extract lessons
review	/lesson-learned review	Analyze last commit
session	/lesson-learned session	Retrospective evaluation of entire session

---

Mode: auto

Automatically after a fixing round. Analyzes recent changes.

Procedure

1. Load prior context: Read existing audit states for fixing pattern analysis:
   • .audit-state.json -> Which findings were fixed? Identify patterns
   • .project-audit-state.json -> Code quality fixing patterns
   • .astro-audit-state.json -> Extract migration learnings
   • Purpose: Extract patterns from fixed findings (e.g., "Fixed 3x missing type annotations -> Lesson: enable strict mode")
2. Read git diff HEAD~3..HEAD (last 3 commits)
3. Identify change patterns:
   • Bug fix pattern: What was broken? Why? How was it fixed?
   • Refactoring pattern: What was restructured? Why is it better?
   • New feature: What decision was made? Why?
4. Read memory directory and MEMORY.md index
5. Check: Does a memory file on this topic already exist?
6. If new: Formulate 1-2 lessons and save as memory files:
   • Create memory file in memory directory (filename: {short-title-kebab-case}.md)
   • Update MEMORY.md index (add link to new file)
7. If existing topic: Update existing memory file instead of creating a new one

Memory File Format

---
name: {short-title}
description: {one-line description}
type: feedback
---

**Problem:** {what went wrong}
**Root Cause:** {root cause}
**Solution:** {what worked}
**Why:** {why this matters}
**How to apply:** {when this insight is relevant}
**Reference:** `{file}:{line}`

Filename Convention

• Kebab-case from the short title: hook-stderr-windows.md, parallel-bash-calls.md
• No numbering, no date prefixes
• Descriptive enough to guess content without opening

---

Mode: review

Analyzes the last commit specifically.

Procedure

1. Read git log -1 --stat (last commit)
2. Read git diff HEAD~1..HEAD
3. Analyze commit message (what was the goal?)
4. Compare changes against goal
5. Extract learning if relevant
6. Create memory file (same as auto, step 6)

---

Mode: session

Retrospective on the entire session. For use at session end.

Procedure

1. Read git log --since="3 hours ago" --stat
2. Summarize all commits from the session
3. Identify overarching patterns:
   • Recurring error categories
   • Tools/workarounds that helped
   • Architecture decisions that were made
4. Formulate 1-2 overarching lessons
5. Create memory files (same as auto, step 6)

---

Rules

1. Max 2 lessons per invocation — Quality over quantity
2. Always anchored to real files — No abstract wisdom
3. No duplicates — Read memory directory and MEMORY.md index first
4. No noise — Only insights that will concretely save time in the future
5. Project-specific vs. global:
   • Project-specific learning -> project-specific memory directory
   • General learning -> global memory directory or CLAUDE.md
6. Update existing memory files instead of creating new ones when the topic already exists
7. Frontmatter required — Every memory file needs name, description, and type (feedback)
8. Maintain MEMORY.md index — Update the index after every new memory file

When to Recommend

• After a bug-fixing session with >3 fixes
• After a debugging process that took >20 minutes
• After an architecture decision
• At the end of a major work phase
• When the same error type occurs for the second time

Files

lesson-learned/
└── SKILL.md    <- This file