Agent skill

extract

Turn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples.

Stars 8,805
Forks 1,070

Install this agent skill to your Project

npx add-skill https://github.com/alirezarezvani/claude-skills/tree/main/engineering-team/self-improving-agent/skills/extract

SKILL.md

/si:extract — Create Skills from Patterns

Transforms a recurring pattern or debugging solution into a standalone, portable skill that can be installed in any project.

Usage

/si:extract <pattern description>                  # Interactive extraction
/si:extract <pattern> --name docker-m1-fixes       # Specify skill name
/si:extract <pattern> --output ./skills/            # Custom output directory
/si:extract <pattern> --dry-run                     # Preview without creating files

When to Extract

A learning qualifies for skill extraction when ANY of these are true:

Criterion Signal
Recurring Same issue across 2+ projects
Non-obvious Required real debugging to discover
Broadly applicable Not tied to one specific codebase
Complex solution Multi-step fix that's easy to forget
User-flagged "Save this as a skill", "I want to reuse this"

Workflow

Step 1: Identify the pattern

Read the user's description. Search auto-memory for related entries:

bash
MEMORY_DIR="$HOME/.claude/projects/$(pwd | sed 's|/|%2F|g; s|%2F|/|; s|^/||')/memory"
grep -rni "<keywords>" "$MEMORY_DIR/"

If found in auto-memory, use those entries as source material. If not, use the user's description directly.

Step 2: Determine skill scope

Ask (max 2 questions):

  • "What problem does this solve?" (if not clear)
  • "Should this include code examples?" (if applicable)

Step 3: Generate skill name

Rules for naming:

  • Lowercase, hyphens between words
  • Descriptive but concise (2-4 words)
  • Examples: docker-m1-fixes, api-timeout-patterns, pnpm-workspace-setup

Step 4: Create the skill files

Spawn the skill-extractor agent for the actual file generation.

The agent creates:

<skill-name>/
├── SKILL.md            # Main skill file with frontmatter
├── README.md           # Human-readable overview
└── reference/          # (optional) Supporting documentation
    └── examples.md     # Concrete examples and edge cases

Step 5: SKILL.md structure

The generated SKILL.md must follow this format:

markdown
---
name: "skill-name"
description: "<one-line description>. Use when: <trigger conditions>."
---

# <Skill Title>

> One-line summary of what this skill solves.

## Quick Reference

| Problem | Solution |
|---------|----------|
| {{problem 1}} | {{solution 1}} |
| {{problem 2}} | {{solution 2}} |

## The Problem

{{2-3 sentences explaining what goes wrong and why it's non-obvious.}}

## Solutions

### Option 1: {{Name}} (Recommended)

{{Step-by-step with code examples.}}

### Option 2: {{Alternative}}

{{For when Option 1 doesn't apply.}}

## Trade-offs

| Approach | Pros | Cons |
|----------|------|------|
| Option 1 | {{pros}} | {{cons}} |
| Option 2 | {{pros}} | {{cons}} |

## Edge Cases

- {{edge case 1 and how to handle it}}
- {{edge case 2 and how to handle it}}

Step 6: Quality gates

Before finalizing, verify:

  • SKILL.md has valid YAML frontmatter with name and description
  • name matches the folder name (lowercase, hyphens)
  • Description includes "Use when:" trigger conditions
  • Solutions are self-contained (no external context needed)
  • Code examples are complete and copy-pasteable
  • No project-specific hardcoded values (paths, URLs, credentials)
  • No unnecessary dependencies

Step 7: Report

✅ Skill extracted: {{skill-name}}

Files created:
  {{path}}/SKILL.md          ({{lines}} lines)
  {{path}}/README.md         ({{lines}} lines)
  {{path}}/reference/examples.md  ({{lines}} lines)

Install: /plugin install (copy to your skills directory)
Publish: clawhub publish {{path}}

Source: MEMORY.md entries at lines {{n, m, ...}} (retained — the skill is portable, the memory is project-specific)

Examples

Extracting a debugging pattern

/si:extract "Fix for Docker builds failing on Apple Silicon with platform mismatch"

Creates docker-m1-fixes/SKILL.md with:

  • The platform mismatch error message
  • Three solutions (build flag, Dockerfile, docker-compose)
  • Trade-offs table
  • Performance note about Rosetta 2 emulation

Extracting a workflow pattern

/si:extract "Always regenerate TypeScript API client after modifying OpenAPI spec"

Creates api-client-regen/SKILL.md with:

  • Why manual regen is needed
  • The exact command sequence
  • CI integration snippet
  • Common failure modes

Tips

  • Extract patterns that would save time in a different project
  • Keep skills focused — one problem per skill
  • Include the error messages people would search for
  • Test the skill by reading it without the original context — does it make sense?

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