4meta5

engram-summarize

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# Install this skill:
npx skills add 4meta5/skills --skill "engram-summarize"

Install specific skill from multi-skill repository

# Description

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# SKILL.md


name: engram-summarize
description: |
Summarize coding sessions into structured learnings using LLM extraction.
Use when: (1) distilling lessons from recent work, (2) creating reusable knowledge,
(3) building a project knowledge base, (4) onboarding others to a codebase.
category: memory
disable-model-invocation: false
user-invocable: true
allowed-tools: Read, Bash, Write, Edit, Glob


Engram Summarize

Extract structured learnings from Claude Code and OpenClaw session history using LLM-based summarization.

When to Use

  • After completing significant work on a project
  • Before onboarding someone new to a codebase
  • Periodically to capture accumulated knowledge
  • When you want to distill decisions and patterns

What It Extracts

Category Description Example
decision Architectural and design choices "Chose SQLite over PostgreSQL for local CLI"
pattern Code patterns and idioms "Uses Result for error handling"
gotcha Things that went wrong and fixes "index.json must sync with posts/"
convention Project-specific norms "Tests colocated with source files"
context Background knowledge "This is a Rust 2021 edition project"

Workflow

Step 1: Set up API key

export ANTHROPIC_API_KEY=your-key

Step 2: Summarize sessions

# Summarize last 30 days for current workspace
npx engram summarize --workspace . --days 30

# Save to file
npx engram summarize --workspace . -o learnings.json

# Higher confidence threshold
npx engram summarize --workspace . --min-confidence 0.7

Step 3: Review learnings

The output includes:
- Session count processed
- Learnings by category
- Top learnings ranked by confidence

Example output:

📊 Summary:
  Sessions: 12
  Learnings: 23

  By category:
    Decisions:   5
    Patterns:    8
    Gotchas:     4
    Conventions: 3
    Context:     3

📝 Top learnings:
  [gotcha] Blog index.json must be updated when posts are renamed
  [pattern] All exports go through index.ts barrel files
  [decision] Used vitest over jest for faster test execution

Step 4: Integrate with skill generation

Use summarized learnings to enhance generated skills:

# Generate skill with richer context
npx engram generate-skill --workspace . --days 30

CLI Options

Option Description Default
-w, --workspace <path> Workspace to filter sessions .
-d, --days <number> Days of history to analyze 30
--no-openclaw Exclude OpenClaw sessions include
-a, --agent <id> OpenClaw agent ID filter all
-c, --min-confidence <n> Confidence threshold (0-1) 0.5
-o, --output <path> Save learnings to JSON file stdout
--json Output as JSON pretty print

Integration with Other Skills

Skill When to Combine
engram-generate Summarize before generating for richer skills
engram-recall Recall + summarize for full context
describe-codebase Add summarized learnings to codebase description

Comparison: Generate vs Summarize

Aspect engram-generate engram-summarize
Method Pattern matching LLM extraction
Output Structural patterns Semantic learnings
Cost Free (local) API tokens
Depth File co-edits, commands Decisions, rationale

Use both together for best results:
1. summarize extracts the meaning
2. generate captures the structure

Example Learnings

{
  "learnings": [
    {
      "category": "gotcha",
      "summary": "Blog index.json must be updated when posts are renamed",
      "detail": "The blog uses a static index.json. Renaming a post without updating causes 404 errors.",
      "files": ["index.json", "posts/*.md"],
      "confidence": 0.95
    },
    {
      "category": "decision", 
      "summary": "Chose TypeScript for type safety",
      "confidence": 0.85
    }
  ]
}

Important

  • Requires ANTHROPIC_API_KEY environment variable
  • Uses Claude Sonnet for extraction (cost-effective)
  • Review learnings before sharing (may contain sensitive info)
  • Higher confidence threshold reduces noise but may miss insights

# Supported AI Coding Agents

This skill is compatible with the SKILL.md standard and works with all major AI coding agents:

Learn more about the SKILL.md standard and how to use these skills with your preferred AI coding agent.