Chenycl Claude Skills Collection Skill Creator

Skill Creator Guide

Create effective skills that extend Claude's capabilities with specialized knowledge, workflows, or tool integrations.

Skill Structure

skill-name/
├── SKILL.md           # Core instructions (required)
├── scripts/           # Executable code (optional)
│   └── main.py
├── references/        # Extended documentation (optional)
│   └── details.md
└── assets/            # Templates, images, etc. (optional)
    └── template.txt

SKILL.md Template

---
name: skill-name
description: >
  Clear, concise description of what this skill does.
  Include trigger phrases that should activate this skill.
  Mention specific use cases: (1) first use case, (2) second use case.
  Triggers: "keyword1", "keyword2", "phrase that triggers".
---

# Skill Name

Brief overview of the skill's purpose and capabilities.

## Quick Start

### Basic Usage
```bash
# Example command or workflow
skill-command --option value

Workflow

1. Step One - Description of first step
2. Step Two - Description of second step
3. Step Three - Description of third step

Reference

Examples

Example 1: Common Use Case

Detailed example showing skill in action

Notes

• Important consideration
• Another important note

References

See references/details.md for extended documentation.

## Best Practices

### YAML Frontmatter

```yaml
---
name: lowercase-hyphenated
description: >
  CRITICAL: The description is how Claude decides when to use your skill.

  1. Start with WHAT the skill does
  2. List specific USE CASES with numbers: (1) case one, (2) case two
  3. Include TRIGGER PHRASES: "exact phrases", "keywords"
  4. Keep under 500 characters for the description
---

Good vs Bad Descriptions

Good:

description: >
  Generate professional code reviews following industry standards.
  Use when: (1) reviewing pull requests, (2) analyzing code quality,
  (3) finding bugs and security issues.
  Triggers: "review code", "check my PR", "code review", "find bugs".

Bad:

description: A skill for doing code stuff.

Skill Body Guidelines

1. Keep it under 500 lines - Split into references/ if longer
2. Use clear headings - Quick Start, Workflow, Reference, Examples
3. Include examples - Show real usage patterns
4. Be specific - Concrete steps, not vague instructions
5. Link references - Point to references/ for deep dives

Scripts

#!/usr/bin/env python3
"""
Script description.

Usage:
    python script.py <arg1> [--option value]
"""

import sys
import argparse
from pathlib import Path

def main():
    parser = argparse.ArgumentParser(description="Script description")
    parser.add_argument("input", help="Input file or value")
    parser.add_argument("--option", default="default", help="Optional parameter")
    args = parser.parse_args()

    # Main logic here
    print(f"Processing: {args.input}")

if __name__ == "__main__":
    main()

Script Best Practices:

• Use only Python stdlib when possible
• Document any pip dependencies
• Include --help support
• Make scripts executable (chmod +x)
• Use argparse for CLI interface

References Directory

Use references/ for:

• Detailed API documentation
• Extended examples
• Configuration options
• Troubleshooting guides

Keep main SKILL.md focused on quick start and common workflows.

Skill Types

Knowledge Skills

Provide domain expertise and best practices.

• Code style guides
• Industry standards
• Reference documentation

Workflow Skills

Guide through multi-step processes.

• Document generation
• Analysis pipelines
• Review checklists

Tool Skills

Integrate with external tools and APIs.

• Scripts for automation
• API integrations
• File processing

Template Skills

Provide templates and boilerplate.

• Project scaffolding
• Document templates
• Code generators

Testing Your Skill

1. Upload to Claude.ai

   cd skills/my-skill
   zip -r ../../my-skill.skill .
   

   Upload the .skill file in Settings → Capabilities → Skills

2. Test triggers - Try phrases from your description

3. Test edge cases - What happens with unusual inputs?

4. Iterate - Refine based on testing

Common Mistakes

1. Vague descriptions - Be specific about triggers
2. Too long - Split into references if > 500 lines
3. No examples - Always include usage examples
4. Missing triggers - Add common phrases users might say
5. Complex scripts - Keep dependencies minimal

Skill Naming

• Use lowercase
• Hyphen-separated words
• Descriptive but concise
• Examples: code-review, git-commit, api-docs

Converted and distributed by TomeVault — claim your Tome and manage your conversions.