extract

Original：🇺🇸 English
Translated

Extract decisions and learnings from Claude session transcripts. Triggers: "extract learnings", "process pending", SessionStart hook.

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Sourceboshu2/agentops
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NPX Install

npx skill4agent add boshu2/agentops extract

Tags

Translated version includes tags in frontmatter
claude-sessionslearning-extractionsession-hooksai-workflowknowledge-management

SKILL.md Content

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Extract Skill

Typically runs automatically via SessionStart hook.
Process pending learning extractions from previous sessions.

How It Works

The SessionStart hook runs:
bash
ao extract
This checks for queued extractions and outputs prompts for Claude to process.

Manual Execution

Given 
/extract
:

Step 1: Check for Pending Extractions

bash
ao extract 2>/dev/null
Or check the pending queue:
bash
cat .agents/ao/pending.jsonl 2>/dev/null | head -5

Step 2: Process Each Pending Item

For each queued session:
  1. Read the session summary
  2. Extract actionable learnings
  3. Write to 
    .agents/learnings/

Step 3: Write Learnings

Write to: 
.agents/learnings/YYYY-MM-DD-<session-id>.md
markdown
# 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 3.5: Validate Learnings

After writing learning files, validate each has required fields:
  1. Scan newly written files:
bash
ls -t .agents/learnings/YYYY-MM-DD-*.md 2>/dev/null | head -5
  1. For each file, check required fields:
    • Heading: File must start with 
      # Learning: <title>
      (non-empty title)
    • Category: Must contain 
      **Category**: <value>
      where value is one of: 
      debugging
      , 
      architecture
      , 
      process
      , 
      testing
      , 
      security
    • Confidence: Must contain 
      **Confidence**: <value>
      where value is one of: 
      high
      , 
      medium
      , 
      low
    • Content: Must contain a 
      ## What We Learned
      section with at least one non-empty line after the heading
  2. Report validation results:
    • For each valid learning: "✓ <filename>: valid"
    • For each invalid learning: "⚠ <filename>: missing <field>" (list each missing field)
  3. Do NOT delete or retry invalid learnings. Log the warning and proceed. Invalid learnings are still better than no learnings — the warning helps identify extraction quality issues over time.

Step 4: Clear the Queue

bash
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/
  → Validates required fields
  → 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