Automated Code Review

About

Enhance code quality by integrating a second opinion from external AI models like OpenAI Codex and Google Gemini directly into the development workflow. This skill automates the identification of bugs, security risks, and technical debt across newly written or modified files, providing categorized feedback prioritized by severity. By presenting actionable recommendations and offering assisted implementation, it ensures that code remains robust, performant, and maintainable before it ever reaches a pull request.

Key Features

• Automated detection of security vulnerabilities, performance issues, and logic errors.
• Multi-model analysis using OpenAI Codex and Google Gemini for comprehensive feedback.
• 0 GitHub stars
• Categorized reporting of issues by severity, from critical security fixes to minor optimizations.
• Guided implementation process that applies approved recommendations with user oversight.
• Customizable review focuses, including dedicated security-audit and performance-optimization modes.

Use Cases

• Performing automated security audits on authentication modules or sensitive data handling logic.
• Optimizing legacy code for better performance and adherence to modern language-specific idioms.
• Validating new features or bug fixes before committing code to a repository.