| name | code-reviewer |
| description | Comprehensive code review skill for TypeScript, JavaScript, Python, Swift, Kotlin, Go. Includes automated code analysis, best practice checking, security scanning, and review checklist generation. Use when reviewing pull requests, providing code feedback, identifying issues, or ensuring code quality standards. |
Code Reviewer
Complete toolkit for code reviewer with modern tools and best practices.
Quick Start
Main Capabilities
This skill provides three core capabilities through automated scripts:
python scripts/pr_analyzer.py [options]
python scripts/code_quality_checker.py [options]
python scripts/review_report_generator.py [options]
Core Capabilities
1. Pr Analyzer
Automated tool for pr analyzer tasks.
Features:
- Automated scaffolding
- Best practices built-in
- Configurable templates
- Quality checks
Usage:
python scripts/pr_analyzer.py <project-path> [options]
2. Code Quality Checker
Comprehensive analysis and optimization tool.
Features:
- Deep analysis
- Performance metrics
- Recommendations
- Automated fixes
Usage:
python scripts/code_quality_checker.py <target-path> [--verbose]
3. Review Report Generator
Advanced tooling for specialized tasks.
Features:
- Expert-level automation
- Custom configurations
- Integration ready
- Production-grade output
Usage:
python scripts/review_report_generator.py [arguments] [options]
Reference Documentation
Code Review Checklist
Comprehensive guide available in references/code_review_checklist.md:
- Detailed patterns and practices
- Code examples
- Best practices
- Anti-patterns to avoid
- Real-world scenarios
Coding Standards
Complete workflow documentation in references/coding_standards.md:
- Step-by-step processes
- Optimization strategies
- Tool integrations
- Performance tuning
- Troubleshooting guide
Common Antipatterns
Technical reference guide in references/common_antipatterns.md:
- Technology stack details
- Configuration examples
- Integration patterns
- Security considerations
- Scalability guidelines
Tech Stack
Languages: TypeScript, JavaScript, Python, Go, Swift, Kotlin
Frontend: React, Next.js, React Native, Flutter
Backend: Node.js, Express, GraphQL, REST APIs
Database: PostgreSQL, Prisma, NeonDB, Supabase
DevOps: Docker, Kubernetes, Terraform, GitHub Actions, CircleCI
Cloud: AWS, GCP, Azure
Development Workflow
1. Setup and Configuration
npm install
pip install -r requirements.txt
cp .env.example .env
2. Run Quality Checks
python scripts/code_quality_checker.py .
3. Implement Best Practices
Follow the patterns and practices documented in:
references/code_review_checklist.mdreferences/coding_standards.mdreferences/common_antipatterns.md
Best Practices Summary
Code Quality
- Follow established patterns
- Write comprehensive tests
- Document decisions
- Review regularly
Performance
- Measure before optimizing
- Use appropriate caching
- Optimize critical paths
- Monitor in production
Security
- Validate all inputs
- Use parameterized queries
- Implement proper authentication
- Keep dependencies updated
Maintainability
- Write clear code
- Use consistent naming
- Add helpful comments
- Keep it simple
Common Commands
npm run dev
npm run build
npm run test
npm run lint
python scripts/code_quality_checker.py .
python scripts/review_report_generator.py --analyze
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/
Troubleshooting
Common Issues
Check the comprehensive troubleshooting section in references/common_antipatterns.md.
Getting Help
- Review reference documentation
- Check script output messages
- Consult tech stack documentation
- Review error logs
Resources
- Pattern Reference:
references/code_review_checklist.md
- Workflow Guide:
references/coding_standards.md
- Technical Guide:
references/common_antipatterns.md
- Tool Scripts:
scripts/ directory
