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code-reviewer

Identify defects, security gaps, and maintainability risks in codebases.

10|Updated May 20, 2026
Search Tags:#automation#security#maintainability#static-analysis#code-review#ai-review
One-click install
npx skills add https://github.com/AI-Safeter/antigravity-cli-plugin --skill code-reviewer-ai-safeter
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-reviewer
Source: https://github.com/AI-Safeter/antigravity-cli-plugin/tree/main/plugins/code-reviewer
Command: npx skills add https://github.com/AI-Safeter/antigravity-cli-plugin --skill code-reviewer-ai-safeter

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Automates and elevates code reviews by combining AI-powered analysis, static analysis tools, and security guidance to catch defects, vulnerabilities, and maintainability issues early in development.

Core Features & Use Cases

  • AI-powered multi-language code analysis with actionable recommendations
  • Integration with industry tools (SonarQube, CodeQL, Semgrep) for comprehensive scans
  • Security-focused review workflow covering vulnerabilities, input validation, and dependency risks
  • Automation of pull request reviews and template-driven remediation guidance
  • End-to-end assessment for performance, reliability, and maintainability

Quick Start

Provide a comprehensive codebase and request an expert review focused on security, performance, and maintainability.

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 reviews for security and maintainability?▼

You can automate pull request reviews by applying AI-powered analysis to identify defects, security gaps, and maintainability risks, generating template-driven remediation guidance for your codebase.

Can I integrate static analysis tools like SonarQube and CodeQL with AI code review?▼

Yes, AI code review supports integration with industry static analysis tools like SonarQube, CodeQL, and Semgrep to perform comprehensive scans and combine results with AI-assisted analysis.

What is the best way to perform a production readiness check across a multi-language codebase?▼

The best way to perform a production readiness check is to conduct an end-to-end AI-assisted assessment that evaluates performance, reliability, and maintainability risks across multi-language codebases.

How does AI-assisted analysis identify security vulnerabilities and dependency risks?▼

AI-assisted analysis identifies security vulnerabilities and dependency risks by applying a security-focused review workflow that checks for input validation issues and evaluates dependencies for potential threats.

Does automated code review provide actionable steps for fixing defects?▼

Yes, automated code review provides guided remediation with actionable steps, offering template-driven recommendations to resolve identified defects, vulnerabilities, and maintainability issues.

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