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chicanoandres702
chicanoandres702COMMUNITY
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code-reviewer

Automate code reviews to identify security, performance, and reliability issues.

Updated Feb 24, 2026
Search Tags:#ci/cd#static analysis#code review#performance#security#ai-assisted#production reliability
One-click install
npx skills add https://github.com/chicanoandres702/SentientAIBrowser --skill code-reviewer-chicanoandres702
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-reviewer
Source: https://github.com/chicanoandres702/SentientAIBrowser/tree/main/.agents/workflows/code-reviewer
Command: npx skills add https://github.com/chicanoandres702/SentientAIBrowser --skill code-reviewer-chicanoandres702

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Code review is time-consuming and inconsistent. This Skill provides AI-assisted, comprehensive code analysis to uncover security vulnerabilities, performance bottlenecks, and maintainability concerns across modern codebases.

Core Features & Use Cases

  • AI-powered code analysis across multiple languages with context-aware recommendations.
  • Static analysis tooling integration (SonarQube, CodeQL, Semgrep) and security scanners (Snyk, Bandit, OWASP).
  • Automated pull request analysis, detailed feedback templates, and guidance for remediation.

Quick Start

Provide an AI-assisted code review for the latest pull request to surface critical issues and recommended fixes.

Frequently Asked Questions about code-reviewer

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate pull request analysis for security and performance issues?▼

Automated pull request analysis detects security vulnerabilities and performance bottlenecks using AI-assisted code review. It integrates static analysis tools like SonarQube and Semgrep to provide structured, actionable remediation feedback.

What is AI-assisted code review and how does it find vulnerabilities?▼

AI-assisted code review applies context-aware analysis across multi-language codebases to uncover security vulnerabilities and maintainability concerns. It leverages security scanners like Snyk, Bandit, and OWASP to detect issues and enforce production reliability.

Can I use static analysis tools like CodeQL and SonarQube for multi-language codebases?▼

Static analysis tools like CodeQL and SonarQube can be integrated for multi-language codebases. This Skill applies automated code review across JavaScript, Python, Java, and Go to surface critical issues and provide context-aware recommendations.

Does automated code review work with Python and JavaScript security scanners?▼

Automated code review works with Python and JavaScript security scanners like Bandit, Snyk, and OWASP. It analyzes multi-language projects to identify security vulnerabilities and performance bottlenecks, outputting structured feedback.

What's the best way to audit production code for reliability and maintainability?▼

Auditing production code for reliability involves integrating AI-assisted analysis with static analysis tooling like Semgrep. This approach identifies security vulnerabilities, performance bottlenecks, and maintainability concerns while providing actionable remediation guidance.

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