Skill Validator
Overview
skill-validator ensures Claude Code skills meet established quality standards through systematic validation operations. Unlike review-multi (which scores 1-5), skill-validator provides pass/fail validation against minimum standards for production deployment.
Purpose: Quality gate for skill deployment - ensure minimum standards met
The 4 Validation Operations:
- •Validate Structure - YAML, files, naming must pass minimum standards
- •Validate Content - Essential sections and examples must be present
- •Validate Pattern - Architecture pattern correctly implemented
- •Validate Production Readiness - All critical criteria met for deployment
Difference from review-multi:
- •review-multi: Scores 1-5, identifies improvements, comprehensive assessment
- •skill-validator: Pass/fail, minimum standards, deployment gating
Use Together: review-multi for comprehensive assessment, skill-validator for go/no-go decisions
When to Use
Use skill-validator when:
- •Pre-Deployment Gating - Validate skill ready for production before releasing
- •Quality Standards Enforcement - Ensure all skills meet minimum bar
- •Continuous Integration - Automated validation in build/deploy pipelines
- •Certification - Certify skills meet ecosystem standards
- •Post-Update Validation - Ensure changes didn't break compliance
- •Ecosystem Consistency - Maintain quality across all skills
- •Binary Decision Needed - Ship or don't ship (not "what's the score")
Operations
Operation 1: Validate Structure
Purpose: Ensure skill structure meets minimum standards for deployment
Pass Criteria (All must pass):
- •✅ YAML frontmatter valid with required fields (name, description)
- •✅
namein kebab-case format - •✅
descriptionincludes 3+ trigger keywords minimum - •✅ SKILL.md exists
- •✅ File naming follows conventions
- •✅ No critical structure violations
Process:
- •Run automated validation:
python3 review-multi/scripts/validate-structure.py <skill> - •Check score: Must be ≥4 to pass
- •Verify no critical issues
- •Document pass/fail
Validation: PASS if structure score ≥4, FAIL if <4
Time: 5-10 minutes (automated)
Operation 2: Validate Content
Purpose: Ensure essential content sections and examples present
Pass Criteria (All must pass):
- •✅ Overview/Introduction section present
- •✅ When to Use section with 3+ scenarios minimum
- •✅ Main content present (workflow steps OR operations OR reference)
- •✅ At least 3 examples present (code/command)
- •✅ Some form of best practices or guidance
Process:
- •Check for Overview section (## Overview or ## Introduction)
- •Check for When to Use section with scenarios
- •Verify main content exists (steps, operations, or reference material)
- •Count examples (look for ``` code blocks, minimum 3)
- •Check for Best Practices, Common Mistakes, or guidance section
Validation: PASS if all 5 criteria met, FAIL if any missing
Time: 10-15 minutes (manual check)
Operation 3: Validate Pattern
Purpose: Ensure architecture pattern correctly implemented
Pass Criteria (Pattern-specific):
For Workflow Skills:
- •✅ Sequential steps present
- •✅ Steps have consistent structure
- •✅ Prerequisites or Post-Workflow section exists
For Task Skills:
- •✅ Operations section present
- •✅ Operations have consistent structure
- •✅ Operations are independent (no forced sequence)
For Reference Skills:
- •✅ Topic-based organization
- •✅ Quick Reference present
Process:
- •Identify pattern type (workflow/task/reference)
- •Check pattern-specific criteria
- •Verify pattern consistency throughout
- •Document compliance
Validation: PASS if pattern correctly implemented, FAIL if pattern violated
Time: 10-20 minutes (manual check)
Operation 4: Validate Production Readiness
Purpose: Comprehensive pass/fail check for deployment readiness
Pass Criteria (All must pass):
- •✅ Structure validation passes (Operation 1)
- •✅ Content validation passes (Operation 2)
- •✅ Pattern validation passes (Operation 3)
- •✅ No critical anti-patterns (from review-multi if available)
- •✅ SKILL.md completeness (not stub or incomplete)
- •✅ Examples are concrete (not all placeholders)
Process:
- •Run Operations 1-3
- •Check for critical anti-patterns:
- •Monolithic SKILL.md (>2,000 lines, no references)
- •All examples are placeholders
- •Major sections missing
- •Assess overall completeness
- •Make deployment decision
Validation: PASS if all criteria met (ready to deploy), FAIL if any critical issue
Time: 30-45 minutes (combines all operations)
Output: DEPLOY or HOLD decision
Validation Report Format
# Skill Validation Report: [Skill Name] **Validation Date**: [Date] **Validator**: [Name] ## Validation Results Operation 1: Structure Validation Status: ✅ PASS | ❌ FAIL - YAML: [Pass/Fail] - Files: [Pass/Fail] - Naming: [Pass/Fail] - Structure Score: [X]/5 Operation 2: Content Validation Status: ✅ PASS | ❌ FAIL - Overview: [Present/Missing] - When to Use: [X scenarios - Pass if ≥3] - Main Content: [Present/Missing] - Examples: [X examples - Pass if ≥3] - Guidance: [Present/Missing] Operation 3: Pattern Validation Status: ✅ PASS | ❌ FAIL - Pattern: [Workflow/Task/Reference] - Implementation: [Correct/Incorrect] - Consistency: [Yes/No] Operation 4: Production Readiness Status: ✅ READY TO DEPLOY | ❌ HOLD Critical Issues: [List if any] ## Deployment Decision ✅ DEPLOY - All validations passed, ready for production OR ❌ HOLD - Critical issues must be fixed: 1. [Issue 1 with fix] 2. [Issue 2 with fix]
Best Practices
1. Validate Before Deploy
Practice: Run skill-validator on all skills before production deployment
Rationale: Catches critical issues, prevents shipping broken skills
Application: Make validation part of deployment checklist
2. Use as Quality Gate
Practice: Skills must pass validation to be deployed
Rationale: Maintains ecosystem quality baseline
Application: No exceptions - PASS required for deployment
3. Automate Where Possible
Practice: Use review-multi automation for structure validation
Rationale: 95% automated, fast, consistent
Application: Run validate-structure.py as first check
4. Document Failures Clearly
Practice: When skill fails, specify exactly what to fix
Rationale: Actionable feedback enables quick fixes
Application: List specific issues with remediation steps
5. Re-Validate After Fixes
Practice: After fixing issues, run validation again to confirm
Rationale: Ensures fixes actually resolve issues
Application: Validate → Fix → Re-validate cycle
Quick Reference
The 4 Validations
| Operation | Focus | Pass Criteria | Time | Automation |
|---|---|---|---|---|
| Structure | YAML, files, naming | Score ≥4 | 5-10m | 95% (use review-multi) |
| Content | Sections, examples | 5 criteria all met | 10-15m | 40% |
| Pattern | Architecture compliance | Pattern correct | 10-20m | 50% |
| Production Readiness | Overall deployment decision | All validations pass | 30-45m | Combined |
Minimum Standards
Structure:
- •Valid YAML with name + description
- •name in kebab-case
- •3+ trigger keywords
- •SKILL.md exists
- •Basic file structure
Content:
- •Overview present
- •3+ When to Use scenarios
- •Main content present
- •3+ examples
- •Some guidance/best practices
Pattern:
- •Correct pattern implementation
- •Consistent structure
- •Pattern-specific requirements met
Production:
- •All validations pass
- •No critical anti-patterns
- •Completeness (not stub)
- •Examples concrete
Deployment Decision Tree
Run validation operations 1-4
↓
All PASS?
├─ Yes → ✅ DEPLOY (production ready)
└─ No → Which failed?
├─ Structure → Fix YAML/files (critical)
├─ Content → Add missing sections (critical)
├─ Pattern → Fix implementation (critical)
└─ After fixes → Re-validate → Deploy if pass
Integration with review-multi
Use Both:
- •skill-validator: Pass/fail, deployment gating
- •review-multi: 1-5 scoring, comprehensive assessment, improvements
Workflow:
Build skill → skill-validator (PASS?) → review-multi (score?) → Deploy (if PASS) + Note improvements (from review-multi)
skill-validator provides quality gating for skill deployment, ensuring minimum standards met before production release.