Converts patterns and debugging solutions into standalone, shareable skills. Ideal for standardizing fixes across multiple projects.
Install
mkdir -p .claude/skills/extract && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/6265" && unzip -o skill.zip -d .claude/skills/extract && rm skill.zipInstalls to .claude/skills/extract
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
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.Key capabilities
- →Formalize recurring debugging solutions into docs
- →Create modular SKILL.md files
- →Search memory for existing patterns
- →Standardize naming and formatting for new skills
How it works
Looks through existing project memory for historical solutions, then packages them into a portable format with documentation.
Inputs & outputs
When to use extract
- →Package a repeated bug fix
- →Turn a complex setup into a reusable skill
- →Save a debugging pattern for future use
About this 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:
| 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:
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:
claudeanthropic
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
nameanddescription -
namematches the folder name (lowercase, hyphens) -
namedoes NOT contain reserved fragmentsclaudeoranthropic(usecc-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?
When not to use it
- →For one-off fixes that won't be repeated
- →Without confirming the pattern is reproducible
Prerequisites
Limitations
- →Quality depends entirely on the clarity of the source solution
- →Requires user input to define scope
How it compares
Automates the documentation of tribal knowledge into reusable, AI-executable skills.
Compared to similar skills
extract side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| extract (this skill) | 1 | 2mo | Review | Intermediate |
| command-development | 16 | 9mo | Review | Intermediate |
| skill-forge | 11 | 9mo | Review | Intermediate |
| codex-skill | 12 | 5mo | Review | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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