Skill 详情
extract
Agent knowledge management specialty.
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SKILL.md
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---
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:
| 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`
**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:
```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)
- [ ] `name` does NOT contain reserved fragments `c在 GitHub 阅读完整来源 (打开外部页面)