Skill Reviewer

Skill Reviewer

Purpose

The Skill Reviewer provides comprehensive quality assurance and improvement recommendations for Claude Code skills. It evaluates skills against official Anthropic guidelines, identifies clarity issues, detects missing edge cases, and suggests structural improvements. Use this skill to validate skill quality, identify gaps, and ensure skills meet professional standards before distribution.

When to Use

• Evaluating New Skills: Review skills before adding to project or distributing
• Improving Existing Skills: Identify gaps and enhancement opportunities
• Quality Assurance: Ensure skills meet Anthropic guidelines
• Documentation Audit: Check for clarity, completeness, and accessibility
• Structure Validation: Verify proper organization and naming conventions
• Edge Case Testing: Identify scenarios the skill doesn't handle
• Pre-Release Review: Final validation before skill distribution
• Team Standards: Ensure consistency across skill libraries

Capabilities

• Metadata Validation: Check YAML frontmatter, name conventions, description completeness
• Documentation Audit: Evaluate clarity, completeness, and user accessibility
• Structure Assessment: Verify directory organization, file hierarchy, and naming patterns
• Functionality Coverage: Identify missing capabilities and edge cases
• Instruction Quality: Analyze step-by-step guides, examples, and usage patterns
• Guideline Compliance: Verify adherence to Anthropic skill standards
• Cross-Reference Validation: Check links to related skills and documentation
• Risk Identification: Spot potential issues, confusion points, and improvement areas
• Score Generation: Provide overall skill quality score (0-100) with grade (A-F)
• Improvement Roadmap: Generate prioritized recommendations for enhancements

Evaluation Framework

1. Metadata Quality (20 points)

YAML Frontmatter

• ✅ Valid YAML syntax
• ✅ Required fields present: name, description
• ✅ Consistent naming (kebab-case, lowercase)
• ✅ Description is one concise sentence

Naming Conventions

• ✅ Directory name matches skill name
• ✅ Descriptive verb-based names (not "helper", "tool", "manager")
• ✅ Clear intent without jargon
• ✅ Consistent with project patterns

2. Documentation Quality (25 points)

Structure & Organization

• ✅ Clear heading hierarchy (H1 → H2 → H3)
• ✅ Logical content flow
• ✅ Proper use of formatting (bold, code, lists)
• ✅ Consistent voice and tone

Content Completeness

• ✅ Purpose section present and clear
• ✅ "When to Use" section with scenarios
• ✅ Capabilities listed with specifics
• ✅ Usage examples with code snippets
• ✅ Best practices documented
• ✅ Troubleshooting section for common issues

Clarity & Accessibility

• ✅ Jargon-free or well-explained
• ✅ Active voice preferred
• ✅ Concrete examples over abstract concepts
• ✅ Appropriate detail level for audience

3. Structure & Organization (20 points)

File Organization

• ✅ SKILL.md in root of skill directory
• ✅ scripts/ subdirectory for automation (lowercase, if needed)
• ✅ references/ subdirectory for detailed docs (lowercase, if needed)
• ✅ assets/ subdirectory for templates/​boilerplate (lowercase, if needed)
• ✅ README.md for development notes (excluded from distribution)

Directory Conventions

• ✅ Lowercase directory names
• ✅ No nested subdirectories in references/
• ✅ Single-level organization
• ✅ Consistent naming patterns

File Size Constraints

• ✅ SKILL.md under 500 lines (move excessive detail to references/)
• ✅ Reference files over 100 lines have table of contents
• ✅ Executable scripts have proper permissions (chmod +x)

4. Functionality & Coverage (20 points)

Scope & Capabilities

• ✅ Clear boundaries of what skill does/​doesn't do
• ✅ Realistic capability claims
• ✅ No overpromising functionality
• ✅ Dependencies clearly documented

Edge Cases & Error Handling

• ✅ Anticipated edge cases addressed
• ✅ Error scenarios handled gracefully
• ✅ Fallback strategies documented
• ✅ Limitations explicitly stated

Practical Applicability

• ✅ Real-world usage scenarios covered
• ✅ Examples are realistic and actionable
• ✅ Step-by-step guides are complete
• ✅ Expected outcomes clearly defined

5. Guideline Compliance (15 points)

Anthropic Standards

• ✅ Follows official skill guidelines
• ✅ Proper YAML syntax validation
• ✅ Description includes "when to use" triggers
• ✅ No auxiliary docs mixed with skill content

Project Standards

• ✅ Aligns with project conventions
• ✅ Consistent with similar skills
• ✅ Follows naming patterns
• ✅ Uses established templates

Best Practices

• ✅ Clear value proposition
• ✅ Appropriate scope (not too broad)
• ✅ Progressive content disclosure
• ✅ Links to related resources

Usage

Basic Review

# User: "Review the react-component-scaffolder skill"
# Skill Reviewer will:
# 1. Read the SKILL.md file
# 2. Evaluate against all criteria
# 3. Generate comprehensive review report
# 4. Provide improvement recommendations
# 5. Output skill-reviewer_report.md

Structure Review

# User: "Check the directory structure of the fastapi-endpoint-scaffolder skill"
# Skill Reviewer will:
# 1. Verify SKILL.md location and format
# 2. Check subdirectory organization
# 3. Validate file naming conventions
# 4. Review file permissions and sizes
# 5. Recommend structural improvements

Edge Case Analysis

# User: "Identify missing edge cases in the component-builder skill"
# Skill Reviewer will:
# 1. Analyze described capabilities
# 2. Brainstorm unhandled scenarios
# 3. Test against common failure modes
# 4. List missing functionality
# 5. Recommend coverage improvements

Compliance Check

# User: "Verify that my-new-skill follows Anthropic guidelines"
# Skill Reviewer will:
# 1. Validate YAML frontmatter
# 2. Check naming conventions
# 3. Verify description completeness
# 4. Review against official standards
# 5. Report compliance status

Examples

Example 1: Quality Review Report

Skill Reviewed: jest-test-scaffolder

Review Output:

# Skill Review: jest-test-scaffolder

## Overall Score: 87/​100 (Grade: B+)

### Metadata Quality: 18/​20
✅ Valid YAML frontmatter
✅ Clear, concise description
❌ Description could include mention of "Jest" specifically
⚠️  Consider adding example output reference

### Documentation Quality: 23/​25
✅ Comprehensive "When to Use" section
✅ Clear capabilities list
❌ Missing troubleshooting section
⚠️  One example could show error handling

### Structure & Organization: 19/​20
✅ Proper directory structure
✅ SKILL.md under 500 lines
❌ Reference files lack table of contents
⚠️  Consider adding assets/ directory for templates

### Functionality & Coverage: 19/​20
✅ Real-world scenarios covered
✅ Clear step-by-step guide
⚠️  Missing edge case: TypeScript strict mode configuration
⚠️  No mention of coverage threshold testing

### Guideline Compliance: 14/​15
✅ Follows Anthropic standards
⚠️  Could strengthen "when to use" language

## Recommendations

### Priority 1 (Critical)
1. Add troubleshooting section for common Jest configuration issues
2. Document edge case: TypeScript strict mode with React Testing Library

### Priority 2 (High)
1. Add table of contents to reference files
2. Include example output in capabilities section
3. Add coverage threshold testing to best practices

### Priority 3 (Nice to Have)
1. Create templates/ directory with example test files
2. Add video walkthrough link
3. Document advanced patterns for custom matchers

## Usage Statistics
- User Feedback: 4.2/​5 ⭐
- Effectiveness: High (solving real problems)
- Complexity: Medium

Example 2: Edge Case Analysis

Skill Reviewed: deployment-manager

Edge Cases Identified:

## Missing Edge Case Coverage

### Unhandled Scenarios

1. **Deployment Timeout**: No guidance on stuck deployments
2. **Rollback Failures**: What if rollback fails?
3. **Multi-Region**: Only documents single-region deployment
4. **Authentication Expiry**: No mention of credential refresh during long deployments
5. **Partial Failures**: Handling when some services deploy but others fail
6. **Concurrent Deployments**: What happens if two deployments run simultaneously?
7. **Resource Constraints**: No mention of memory/​disk requirements
8. **Network Interruptions**: Handling transient network failures

### Recommended Additions

- Add deployment timeout configuration section
- Document rollback procedures in detail
- Include multi-region deployment guide
- Add environment variable validation step
- Create contingency/​recovery procedures
- Add resource requirements documentation

Example 3: Structure Recommendations

Skill Reviewed: component-builder

Structure Improvements:

## Current Structure

.claude/​skills/​component-builder/ ├── SKILL.md (620 lines - exceeds 500 limit) └── README.md

## Recommended Structure

.claude/​skills/​component-builder/ ├── SKILL.md (380 lines - main overview) ├── README.md (development notes, not distributed) ├── references/ │ ├── MATERIAL_DESIGN_3_TOKENS.md (detailed token reference) │ ├── COMPONENT_PATTERNS.md (advanced patterns, 150+ lines, includes TOC) │ └── TYPESCRIPT_SETUP.md (TypeScript configuration guide) ├── scripts/ │ ├── generate-component.sh (executable) │ └── validate-m3-tokens.py (executable) └── assets/ ├── component.tsx.template ├── component.test.tsx.template └── component.stories.tsx.template

## Benefits
- SKILL.md within 500-line limit (progressive disclosure)
- Reference files organized by topic
- Reusable templates in assets/
- Automation scripts clearly separated
- Better content navigation

Best Practices

For Skill Developers

1. Self-Review First: Use this skill before distributing
2. Iterate Based on Feedback: Implement recommendations progressively
3. Test Your Examples: Verify all code snippets work
4. Get Peer Review: Have teammates review critical skills
5. Version Your Skills: Track changes and improvements

For Skill Maintenance

1. Regular Audits: Review skills quarterly
2. User Feedback: Incorporate reports and suggestions
3. Update Examples: Keep code samples current
4. Expand Coverage: Add edge cases as they're discovered
5. Archive Old Skills: Retire obsolete skills clearly

For Skill Distribution

1. Pre-Release Review: Score ≥80 before distribution
2. Document Dependencies: List required tools/​knowledge
3. Provide Feedback Mechanism: How users report issues
4. Create Support Resources: Links to help and troubleshooting
5. Plan Updates: Version numbering and upgrade path

Scoring Guidelines

Grade Scale

• A (90-100): Exceptional - Ready for distribution, exemplary quality
• B (80-89): Good - Ready for distribution, minor improvements suggested
• C (70-79): Satisfactory - Usable but needs improvements before wider sharing
• D (60-69): Poor - Needs significant work before distribution
• F (Below 60): Inadequate - Not ready for release, major rework required

Minimum Distribution Standards

• ✅ Score ≥ 80 (Grade B or higher)
• ✅ All Priority 1 recommendations addressed
• ✅ Comprehensive documentation
• ✅ Tested examples and workflows
• ✅ Clear scope and limitations

Troubleshooting

Issue: Score Below 80

Solution:

1. Address all Priority 1 recommendations first
2. Add missing sections (troubleshooting, edge cases)
3. Improve documentation clarity
4. Get peer review for feedback
5. Iterate and re-review

Issue: Unclear Recommendations

Solution:

1. Request specific examples
2. Ask for comparison with high-scoring skill
3. Discuss recommendations with team
4. Review Anthropic guidelines for clarification
5. Request follow-up review after changes

Issue: Scope Too Broad

Solution:

1. Break into smaller, focused skills
2. Move advanced topics to references/
3. Focus on core use case
4. Create related skills for extensions
5. Use "Related Skills" to connect them

Related Skills

• skill-creator - Create new Claude Code skills
• task-delegator - Delegate review tasks to specialized agents
• code-reviewer - Review code quality and structure
• project-health-checker - Comprehensive project validation
• audit-agent - Security and quality audits

Related Documentation

• Anthropic Skill Guidelines
• SKILL_GUIDELINES_AUDIT.md - Project skill audit
• Skill Development Best Practices

Summary

The Skill Reviewer provides systematic, objective evaluation of Claude Code skills across five key dimensions: metadata, documentation, structure, functionality, and guideline compliance. Use it to ensure skills meet professional standards, identify improvement opportunities, and maintain consistent quality across skill libraries.

Quick Checklist for High-Quality Skills:

• ✅ Score ≥ 80/​100 (Grade B or higher)
• ✅ Clear, concise description with "when to use"
• ✅ Comprehensive documentation with examples
• ✅ Proper directory structure and naming
• ✅ Addressed Priority 1 recommendations
• ✅ All claims tested and verified
• ✅ Edge cases documented
• ✅ Related skills and references linked