AI Skill Report Card
Building Claude Skills
Creates and manages Claude MCP skills following best practices from the awesome-claude-skills repository. Use when developing MCP tools, creating skill repositories, or contributing to Claude ecosystems.
Quick Start15 / 15
Bash# Clone skill repository template git clone https://github.com/your-username/claude-skills cd claude-skills # Create new skill file touch skills/analyzing-data.md # Add YAML frontmatter and content echo '--- name: analyzing-data description: Analyzes datasets and generates insights with visualizations. Use when exploring data patterns or creating reports. ---' > skills/analyzing-data.md
Recommendation▾
Reduce verbosity in the Best Practices section - Claude already understands naming conventions and file organization basics
Workflow15 / 15
Progress:
- Research existing skills - Check awesome-claude-skills for similar tools
- Define skill scope - Single responsibility, clear trigger phrases
- Create YAML frontmatter - Gerund name, third-person description
- Write quick start - Immediate actionable example
- Document workflow - Step-by-step process with checkboxes
- Add concrete examples - Input/output pairs
- List best practices - Guidelines and tips
- Note common pitfalls - What to avoid
- Test skill - Verify with Claude MCP server
- Submit to repository - Create PR with proper documentation
Recommendation▾
Consolidate the multiple checklists (Progress, Quality Checklist) into one comprehensive workflow checklist
Examples18 / 20
Example 1: Data Analysis Skill
YAML--- name: analyzing-sales-data description: Processes sales datasets to identify trends, seasonal patterns, and revenue insights. Use when examining business performance or forecasting. ---
Example 2: Code Review Skill
YAML--- name: reviewing-python-code description: Conducts thorough Python code reviews focusing on performance, security, and maintainability. Use when auditing codebases or mentoring developers. ---
Example 3: Content Creation Skill
YAML--- name: writing-technical-docs description: Creates comprehensive technical documentation with proper structure and examples. Use when documenting APIs, software architecture, or user guides. ---
Recommendation▾
Add more concrete input/output examples showing the actual skill content structure, not just YAML frontmatter
Best Practices
Naming Convention:
- Use gerund form:
processing-images,managing-databases - Kebab-case only: lowercase, hyphens, no spaces
- Be specific:
analyzing-financial-datavsanalyzing-data
Description Guidelines:
- Start with action verb in third person
- Include specific use cases and trigger phrases
- Keep under 1024 characters
- Mention domain/context when relevant
Content Structure:
- Lead with executable code or immediate steps
- Use progress checklists for complex workflows
- Provide concrete input/output examples
- Include error handling and edge cases
Repository Organization:
skills/
├── data-analysis/
│ ├── analyzing-datasets.md
│ └── visualizing-metrics.md
├── development/
│ ├── reviewing-code.md
│ └── debugging-applications.md
└── content/
├── writing-documentation.md
└── creating-presentations.md
Common Pitfalls
Avoid These Mistakes:
- Generic names:
helper-toolvsparsing-json-apis - First/second person: "I analyze" or "You can" vs "Analyzes"
- Missing triggers: Description without use cases
- Over-explanation: Defining basic concepts Claude knows
- Multiple responsibilities: One skill = one clear purpose
- Vague examples: Abstract descriptions vs concrete input/output
- No error handling: Ignoring edge cases and failures
Quality Checklist:
- Name follows gerund kebab-case format
- Description is third-person with clear triggers
- Quick start provides immediate value
- Examples show concrete input/output
- Workflow has actionable steps
- Best practices are specific and useful
- Common pitfalls prevent real mistakes
Integration Tips:
- Test skills with Claude MCP server before submitting
- Follow repository contribution guidelines
- Include proper README and documentation
- Tag skills appropriately for discoverability
- Consider skill dependencies and prerequisites