code-quality-check
Automated code quality verification checklist
When & Why to Use This Skill
This Claude skill provides an automated, comprehensive code quality verification checklist designed to streamline the software development lifecycle. It systematically evaluates code against SOLID principles, clean code standards, security protocols, and performance benchmarks, ensuring high maintainability and robust error handling before deployment. By integrating these best practices, developers can significantly reduce technical debt and improve overall system reliability.
Use Cases
- Pre-commit Validation: Use the checklist as a final gate to catch 'TODO' tags, debug logs, and hardcoded credentials before pushing code to the repository.
- Automated Peer Reviews: Standardize the code review process by applying a consistent set of rules for SOLID principles and clean code across the engineering team.
- Security & Performance Auditing: Identify potential vulnerabilities such as SQL injection and XSS, as well as performance bottlenecks like N+1 queries during the development phase.
- Technical Debt Reduction: Systematically refactor legacy code by checking against modern standards for function length, parameter counts, and DRY (Don't Repeat Yourself) principles.
| name | code-quality-check |
|---|---|
| description | Automated code quality verification checklist |
| trigger | auto |
Code Quality Check
Run this checklist before committing code:
1. SOLID Principles
[S] Single Responsibility - Each class/function does ONE thing
[O] Open/Closed - Extend without modifying
[L] Liskov Substitution - Subtypes are substitutable
[I] Interface Segregation - Small, focused interfaces
[D] Dependency Inversion - Depend on abstractions
2. Clean Code Rules
✓ Names reveal intent
✓ Functions < 20 lines
✓ Max 3 parameters (use objects if more)
✓ No magic numbers/strings
✓ DRY - No duplication
✓ Comments explain WHY not WHAT
3. Error Handling
✓ All errors caught and handled
✓ No silent failures
✓ Meaningful error messages
✓ Proper logging
✓ Cleanup in finally blocks
4. Performance
✓ No N+1 queries
✓ Proper indexing
✓ Caching where appropriate
✓ Lazy loading for heavy ops
✓ No memory leaks
5. Security
✓ Input validated
✓ Output sanitized
✓ No SQL injection vectors
✓ No XSS vulnerabilities
✓ Secrets in env vars
✓ Dependencies updated
6. Testing
✓ Unit tests written
✓ Edge cases covered
✓ Mocks used for external deps
✓ Tests are fast (< 1s each)
✓ Coverage > 80%
7. Documentation
✓ Public APIs documented
✓ Complex logic explained
✓ README updated
✓ Examples provided
Quick Scan (30 seconds)
# Run before commit:
1. grep -r "TODO\|FIXME\|XXX\|HACK" .
2. Check for console.log / print statements
3. Verify no commented-out code blocks
4. Check for hardcoded credentials
5. Run linter
6. Run tests
Token-Efficient Usage
- Use as final validation, not during writing
- Catch issues before review (saves back-and-forth)
- Automate what you can (linters, formatters)