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ClaudeWave
Skill2.3k estrellas del repoactualizado 24d ago

code-reviewer

The code-reviewer skill provides automated code quality analysis for pull requests and fresh code reviews, evaluating correctness, maintainability, readability, regression risk, and test coverage gaps. Use it for general code review needs, but route security audits to security-reviewer, existing review comments to receiving-code-review, and test-first development to tdd-guide instead.

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git clone --depth 1 https://github.com/foryourhealth111-pixel/Vibe-Skills /tmp/code-reviewer && cp -r /tmp/code-reviewer/bundled/skills/code-reviewer ~/.claude/skills/code-reviewer
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SKILL.md

# 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
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