Code Reviewer

---
name: code-reviewer
description: Default code-quality route for broad code review, PR review, maintainability, correctness, and regression-risk checks. Do not use as the primary route for dedicated OWASP/security audits, review-feedback handling, completion verification, AI-code cleanup, or TDD/test-first work.
---

# Code Reviewer

Complete toolkit for code reviewer with modern tools and best practices.

## Routing Boundary

Use `code-reviewer` when the user asks for a fresh review of code or a PR:
- correctness and likely bugs
- maintainability and readability
- regression risk
- test coverage gaps from a reviewer's point of view

Do not let this skill own narrower problems:
- `security-reviewer` owns OWASP, secret leak, auth bypass, injection, and dedicated security audit prompts.
- `receiving-code-review` owns existing CodeRabbit/GitHub/human review comments.
- `verification-before-completion` owns final evidence before claiming work is done.
- `deslop` owns cleanup of AI-generated comments, redundant guards, and boilerplate.
- `tdd-guide` owns test-first or RED -> GREEN -> REFACTOR development.

## Migrated Legacy Assets

The legacy review wrapper has been absorbed into this direct route owner.

- `references/python-style-guide.md` contains the retained Python naming, import, documentation, error-handling, and secret-handling guidance.
- `scripts/check_style.py` is a lightweight stdin/string style checker for quick local review support.

Use these assets as supporting material inside `code-reviewer`; do not route to the deleted wrapper skill.

## Quick Start

### Main Capabilities

This skill provides three core capabilities through automated scripts:

```bash
# 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 analyzer tasks.

**Features:**
- Automated scaffolding
- Best practices built-in
- Configurable templates
- Quality checks

**Usage:**
```bash
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:**
```bash
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:**
```bash
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

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

# Configure environment
cp .env.example .env
```

### 2. Run Quality Checks

```bash
# 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:
- `references/code_review_checklist.md`
- `references/coding_standards.md`
- `references/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
- Flag obvious security risks during a general review.
- Route dedicated OWASP, auth, secret, injection, or threat-model requests to `security-reviewer`.

### Maintainability
- Write clear code
- Use consistent naming
- Add helpful comments
- Keep it simple

## Common Commands

```bash
# 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 `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