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Audit score 90

extract

alirezarezvani/claude-skills

Package recurring patterns and debugging solutions into portable, reusable skills.

What is extract?

The extract skill transforms proven patterns, debugging solutions, and recurring fixes into standalone SKILL.md packages that can be installed across projects. Use it when you've solved a non-obvious problem multiple times or want to preserve a complex solution for future reuse.

  • Converts patterns from project memory or user description into portable skill packages
  • Generates SKILL.md with frontmatter, problem statement, and multiple solution approaches
  • Creates README.md and optional reference documentation with examples
  • Validates skill names against reserved fragments (claude, anthropic) and enforces naming conventions
  • Supports interactive mode, custom naming, custom output directories, and dry-run preview
  • Includes quality gates to ensure solutions are self-contained and copy-pasteable

How to install extract

npx skills add https://github.com/alirezarezvani/claude-skills --skill extract
Claude Code
Cursor
Windsurf
Cline

How to use extract

  1. 1.Run /si:extract with a pattern description (e.g., /si:extract "Docker builds failing on Apple Silicon")
  2. 2.Answer up to 2 clarifying questions about the problem scope and desired examples
  3. 3.Confirm the generated skill name (must avoid reserved fragments like 'claude' or 'anthropic')
  4. 4.Review the generated SKILL.md, README.md, and reference files in the output directory
  5. 5.Install the skill in your project or publish it via clawhub publish

Use cases

Good for
  • Save a Docker build fix that works across multiple projects as a reusable skill
  • Package a complex multi-step debugging workflow into a skill for team reuse
  • Extract a CI/CD pattern or configuration template discovered through trial-and-error
  • Preserve non-obvious API client regeneration or build process steps as portable documentation
  • Convert project-specific memory entries into broadly applicable skills for installation elsewhere
Who it's for
  • Developers who solve the same problems repeatedly across projects
  • Teams wanting to standardize recurring fixes and patterns
  • Anyone building a personal library of reusable debugging solutions
  • Projects using Claude Code or Cursor with skill-based workflows

extract FAQ

When should I extract a pattern into a skill?

Extract when the pattern is recurring (appears in 2+ projects), non-obvious (required real debugging), broadly applicable (not tied to one codebase), complex (multi-step and easy to forget), or explicitly requested by a user.

What naming rules apply to skills?

Use lowercase with hyphens (e.g., docker-m1-fixes). Avoid reserved fragments 'claude' and 'anthropic'. For Claude Code-specific skills, use the cc- prefix (e.g., cc-settings instead of claude-code-settings).

Can I specify a custom output directory?

Yes, use the --output flag: /si:extract <pattern> --output ./skills/

What files does extract create?

It creates SKILL.md (main skill with frontmatter), README.md (human-readable overview), and optionally reference/examples.md (concrete examples and edge cases).

Can I preview the skill before creating files?

Yes, use the --dry-run flag to preview without actually creating files.

Full instructions (SKILL.md)

Source of truth, from alirezarezvani/claude-skills.


name: "extract" description: "Turn a proven pattern or debugging solution into a standalone reusable skill with SKILL.md, reference docs, and examples. Use when the user runs /si:extract or asks to package a recurring solution from memory into a skill."

/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:

CriterionSignal
RecurringSame issue across 2+ projects
Non-obviousRequired real debugging to discover
Broadly applicableNot tied to one specific codebase
Complex solutionMulti-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:

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

Reserved fragments — must NOT appear in the skill name:

  • claude
  • anthropic

For skills about Claude Code itself, use the cc- prefix instead:

  • claude-code-settings → ✅ cc-settings
  • claude-code-maintenance → ✅ cc-maintenance
  • claude-mcp-tools → ✅ cc-mcp-tools
  • claude-plugin-development → ✅ cc-plugin-development

Before writing the skill directory, check the proposed name against this list. If a reserved fragment is present, transform it (drop the fragment or replace the claude*/anthropic* prefix with cc-) and confirm with the user.

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:

---
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)
  • name does NOT contain reserved fragments claude or anthropic (use cc- prefix for Claude Code skills)
  • 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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