code-reviewer

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:

# Script 1: PR Analyzer
python scripts/pr_analyzer.py [options]

# Script 2: Code Quality Checker
python scripts/code_quality_checker.py [options]

# Script 3: Review Report Generator
python scripts/review_report_generator.py [options]

Core Capabilities

1. PR Analyzer

Automated tool for PR analysis 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 covering:

• Detailed patterns and practices
• Code examples
• Best practices
• Anti-patterns to avoid
• Real-world scenarios

See documentation for details.

Coding Standards

Complete workflow documentation:

• Step-by-step processes
• Optimization strategies
• Tool integrations
• Performance tuning
• Troubleshooting guide

See documentation for details.

Common Antipatterns

Technical reference guide:

• Technology stack details
• Configuration examples
• Integration patterns
• Security considerations
• Scalability guidelines

See documentation for details.

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

# Install dependencies
npm install
# or
pip install -r requirements.txt

# Configure environment
cp .env.example .env

2. Run Quality Checks

# Use the analyzer script
python scripts/code_quality_checker.py .

# Review recommendations
# Apply fixes

3. Implement Best Practices

Follow the patterns and practices documented in:

• Code review checklist
• Coding standards reference
• Common antipatterns reference

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

# Development
npm run dev
npm run build
npm run test
npm run lint

# Analysis
python scripts/code_quality_checker.py .
python scripts/review_report_generator.py --analyze

# Deployment
docker build -t app:latest .
docker-compose up -d
kubectl apply -f k8s/

Troubleshooting

Common Issues

Check the comprehensive troubleshooting section in common antipatterns documentation.

Getting Help

• Review reference documentation
• Check script output messages
• Consult tech stack documentation
• Review error logs