Claude-skill-registry extract
Extract decisions and learnings from Claude session transcripts. Triggers: "extract learnings", "process pending", SessionStart hook.
install
source · Clone the upstream repo
git clone https://github.com/majiayu000/claude-skill-registry
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/extract" ~/.claude/skills/majiayu000-claude-skill-registry-extract && rm -rf "$T"
manifest:
skills/data/extract/SKILL.mdsource content
Extract Skill
Typically runs automatically via SessionStart hook.
Process pending learning extractions from previous sessions.
How It Works
The SessionStart hook runs:
ao extract
This checks for queued extractions and outputs prompts for Claude to process.
Manual Execution
Given
/extract:
Step 1: Check for Pending Extractions
ao extract 2>/dev/null
Or check the pending queue:
cat .agents/ao/pending.jsonl 2>/dev/null | head -5
Step 2: Process Each Pending Item
For each queued session:
- Read the session summary
- Extract actionable learnings
- Write to
.agents/learnings/
Step 3: Write Learnings
Write to:
.agents/learnings/YYYY-MM-DD-<session-id>.md
# Learning: <Short Title> **ID**: L1 **Category**: <debugging|architecture|process|testing|security> **Confidence**: <high|medium|low> ## What We Learned <1-2 sentences describing the insight> ## Why It Matters <1 sentence on impact/value> ## Source Session: <session-id>
Step 4: Clear the Queue
ao extract --clear 2>/dev/null
Step 5: Report Completion
Tell the user:
- Number of learnings extracted
- Key insights
- Location of learning files
The Knowledge Loop
Session N ends: → ao forge --last-session --queue → Session queued in pending.jsonl Session N+1 starts: → ao extract (this skill) → Claude processes the queue → Writes to .agents/learnings/ → Loop closed
Key Rules
- Runs automatically - usually via hook
- Process the queue - don't leave extractions pending
- Be specific - actionable learnings, not vague observations
- Close the loop - extraction completes the knowledge cycle