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Contributing to Claude Skills Marketplace

Thank you for your interest in contributing! This guide will help you create high-quality Skills that work reliably across different Claude models.

Skill Structure

A basic Skill consists of:

skill-name/
├── SKILL.md          # Required: Main skill file
├── reference.md      # Optional: Detailed reference material
├── examples/         # Optional: Example files or templates
└── scripts/          # Optional: Executable scripts

SKILL.md Format

---
name: skill-name
description: What it does and when to use it. Include activation triggers.
model: sonnet              # Optional: Preferred model (sonnet, opus, haiku)
---

# Skill Title

Brief overview (1-2 sentences).

## When to Use

Specific activation scenarios:
- User says "X"
- Context includes Y
- Task involves Z

## Instructions

Step-by-step instructions for Claude...

Best Practices

1. Write Clear Descriptions

Good:

description: Analyze vendorlist extraction performance and F1-scores. Use when user mentions vendorlist evaluation, low F1-scores, extraction accuracy issues, or asks to analyze vendorlist performance.

Bad:

description: Helps with vendorlists

The description should answer:

  • What does this skill do?
  • When should it activate?
  • Why would someone use it?

2. Use Gerund Names

Good: git-pushing, test-fixing, review-implementing

Bad: git-push, fix-test, implement-review

Gerund forms (-ing) indicate ongoing processes and match natural language patterns.

3. Keep Skills Focused

Each Skill should do ONE thing well. If you find yourself writing "and also" in the description, consider splitting into separate Skills.

4. Structure for Progressive Disclosure

Keep SKILL.md under 500 lines:

  • Core instructions in SKILL.md
  • Detailed reference material in reference.md
  • Examples in separate files

This allows Claude to load only what's needed.

5. Assume Claude's Knowledge

Don't explain basic concepts. Claude already knows Python, git, testing frameworks, etc.

Good:

Run `pytest -k "pattern"` to test specific cases.

Bad:

Pytest is a testing framework for Python. The -k flag filters tests by pattern. You should use this command: `pytest -k "pattern"` to run tests that match the pattern.

6. Match Specificity to Risk

High-risk operations (database migrations, deployments):

  • Provide step-by-step instructions
  • Include validation checks
  • Require confirmation

Low-risk operations (code formatting, documentation):

  • Give general guidance
  • Allow flexibility

7. Use Platform-Agnostic Paths

Good: backend/src/utils/helper.py

Bad: backend\src\utils\helper.py

Always use forward slashes for file paths.

8. Test Across Models

Test your Skill with:

  • Claude Sonnet (balanced)
  • Claude Opus (most capable)
  • Claude Haiku (fastest)

Some models may need more detail than others.

Submission Process

  1. Fork this repository

  2. Create your skill:

    mkdir my-skill
    cd my-skill
    # Create SKILL.md following the template
  3. Test thoroughly:

    • Test with different phrasings
    • Verify activation triggers work
    • Check across multiple models if possible
  4. Update README.md:

    • Add your skill to the "Available Skills" section
    • Include activation examples
    • Describe what it does
  5. Submit Pull Request:

    • Title: "Add [skill-name] skill"
    • Description: Explain what the skill does and why it's useful
    • Include example usage

Skill Categories

Organize your skill into one of these categories:

  • Git & Version Control: Git workflows, commits, branches
  • Testing & Quality: Test running, fixing, coverage
  • Code Review: Review feedback, PR management
  • Documentation: Docs generation, README updates
  • DevOps: CI/CD, deployment, infrastructure
  • Data Processing: ETL, analysis, transformation
  • Development Tools: Linting, formatting, refactoring

Examples of Good Skills

Look at existing skills in this repository for inspiration:

  • git-pushing: Clear activation triggers, conventional commits
  • test-fixing: Smart grouping strategy, systematic approach
  • review-implementing: Todo tracking, systematic workflow

Quality Checklist

Before submitting, verify:

  • YAML frontmatter is valid
  • Description includes activation triggers
  • Instructions are concise (no unnecessary explanations)
  • File paths use forward slashes
  • Skill is under 500 lines (or uses reference files)
  • Examples demonstrate activation
  • README.md updated with new skill
  • Tested with actual use cases
  • No hard-coded paths or environment-specific details

Getting Help

Questions or need guidance?

License

By contributing, you agree that your contributions will be licensed under the Apache 2.0 License.