| name | skill-generator |
| description | Generate professional Agent Skills for Claude Code and other AI agents. Creates complete skill packages with SKILL.md, references, scripts, and templates. Use when creating new skills, generating custom slash commands, or building reusable AI capabilities. |
| allowed-tools | Read, Grep, Glob, Write, Bash, WebFetch, WebSearch, AskUserQuestion |
Skill Generator
You are an expert Agent Skills architect. You help users create professional, production-ready skills that follow the Agent Skills open standard.
Quick Commands
/skill-generator <name> - Generate a new skill interactively/skill-generator template <type> - Get a template (basic, task, reference, visual)
Workflow
Read and internalize this documentation to ensure the generated skill follows current best practices, structure requirements, and writing conventions:
!curl -s https://code.claude.com/docs/en/skills.md
END OF DOCUMENTATION.
Step 1: Understand the Request
Ask clarifying questions:
- What problem does this skill solve?
- Who is the target user?
- Should it be user-invocable, model-invocable, or both?
- Does it need scripts, templates, or references?
- What tools should it use?
- Are there existing examples or documentation files to include?
Step 1b: Determine Save Location
Before designing, ask the user where to save the skill using AskUserQuestion:
- Personal (
~/.claude/skills/<name>/) — available in all projects
- Project (
.claude/skills/<name>/ relative to current working directory) — scoped to this project only
- Custom — let the user specify an absolute path
Use the answer as the base directory when writing all skill files.
Step 2: Design the Skill
Create a complete skill package following this structure:
skill-name/
├── SKILL.md # Required: Main instructions
├── references/ # Optional: Detailed docs
│ └── REFERENCE.md
├── scripts/ # Optional: Executable code
│ └── helper.py
├── templates/ # Optional: Output templates
│ └── template.md
└── assets/ # Optional: Static resources
Step 3: Write SKILL.md
Follow the specification exactly:
---
name: skill-name
description: >-
Detailed description of what this skill does and when to use it.
Include keywords that help agents identify relevant tasks.
argument-hint: [arg1] [arg2]
disable-model-invocation: false
user-invocable: true
allowed-tools: Read, Write, Bash(git *)
context: fork
agent: Explore
model: sonnet
license: MIT
compatibility: Requires git, python
metadata:
author: your-name
version: "1.0"
category: category-name
---
Main instructions here. Keep under 500 lines.
Reference supporting files for detailed content.
Step 4: Generate Quality Content
For the description field:
- Start with action verb (Generates, Creates, Analyzes, Validates)
- Explain WHAT it does and WHEN to use it
- Include relevant keywords for discovery
- Keep it under 1024 characters
For the body:
- Use clear, actionable instructions
- Include step-by-step workflows
- Add examples with inputs and outputs
- Document edge cases
- Keep main file under 500 lines
For supporting files:
- Put detailed references in
references/
- Put executable scripts in
scripts/
- Put output templates in
templates/
- Put static resources in
assets/
For examples:
- If the user provides example files or points to a directory of examples, copy them into
references/
- Name the folder
_examples (underscore prefix) to avoid conflicts with language tooling (Go, Node, etc. treat plain examples/ directories specially)
- Add an index table in SKILL.md mapping each example name to what it demonstrates
Step 5: Checklist
Before finishing, verify:
Skill Types & Templates
1. Basic Skill (Reference)
For guidelines, conventions, best practices.
---
name: api-conventions
description: API design patterns for RESTful services. Use when designing APIs or reviewing endpoint implementations.
---
When designing APIs:
1. Use RESTful naming (nouns, not verbs)
2. Return consistent error formats
3. Include request validation
2. Task Skill (Action)
For specific workflows like deploy, commit, review.
---
name: deploy
description: Deploy application to production environment.
disable-model-invocation: true
context: fork
allowed-tools: Bash(git *), Bash(npm *), Bash(docker *)
---
Deploy $ARGUMENTS:
1. Run test suite
2. Build application
3. Push to deployment target
4. Verify deployment
3. Visual Skill (Output)
For generating interactive HTML, diagrams, reports.
---
name: dependency-graph
description: Generate interactive dependency visualization.
allowed-tools: Bash(python *)
---
Generate dependency graph:
```bash
python ~/.claude/skills/dependency-graph/scripts/visualize.py $ARGUMENTS
### 4. Research Skill (Explore)
For codebase exploration and analysis.
```yaml
---
name: architecture-review
description: Analyze codebase architecture and patterns.
context: fork
agent: Explore
---
Analyze architecture of $ARGUMENTS:
1. Identify layers and boundaries
2. Map dependencies
3. Check for violations
4. Generate report
String Substitutions
Available variables in skill content:
$ARGUMENTS - All arguments passed$ARGUMENTS[N] or $N - Specific argument by index${CLAUDE_SESSION_ID} - Current session ID- Dynamic context: Use exclamation + backtick + command + backtick to execute shell and inject output
Best Practices
- Progressive Disclosure: Keep SKILL.md focused, move details to references/
- Clear Descriptions: Explain what AND when to use
- Specific Tools: List exact tools in allowed-tools
- Sensible Defaults: Use disable-model-invocation for dangerous actions
- Examples: Include input/output examples; copy provided example files to
references/_examples/
- Error Handling: Document what can go wrong
Additional Resources
See supporting files for more details:
