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ai-code-reviewer

Review AI-generated code for correctness, security, performance, and maintainability issues.

5|1|Updated Feb 4, 2026
Search Tags:#quality assurance#code review#performance#security#maintainability#ai code
One-click install
npx skills add https://github.com/latestaiagents/agent-skills --skill ai-code-reviewer-latestaiagents
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: ai-code-reviewer
Source: https://github.com/latestaiagents/agent-skills/tree/main/plugins/developer-toolkit/skills/code-intelligence/ai-code-reviewer
Command: npx skills add https://github.com/latestaiagents/agent-skills --skill ai-code-reviewer-latestaiagents

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This skill addresses the risk of deploying buggy, insecure, or inefficient code generated by AI assistants by providing a systematic review process.

Core Features & Use Cases

  • Catch Common AI Mistakes: Identifies issues like hallucinated APIs, incorrect library versions, off-by-one errors, and null/undefined handling.
  • Security Vulnerability Detection: Checks for SQL injection, XSS, exposed secrets, and missing input validation.
  • Performance Optimization: Flags potential N+1 queries, unnecessary re-renders, memory leaks, and blocking operations.
  • Maintainability Checks: Ensures consistent patterns, proper typing, and avoids dead code.
  • Integration Verification: Verifies adherence to project conventions, naming, and error handling.
  • Use Case: After an AI generates a new API endpoint, use this skill to systematically review the code for correctness, security, performance, and adherence to project standards before merging it into the main branch.

Quick Start

Use the ai-code-reviewer skill to review the AI-generated code in the current file.

Frequently Asked Questions about ai-code-reviewer

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

FAQPage Schema
How do I check AI-generated code for security vulnerabilities and API hallucinations?▼

Review AI-generated code using a structured checklist to detect security vulnerabilities like SQL injection and XSS, along with hallucinated APIs and incorrect library versions. This process ensures correctness and security before merging.

What is the best way to review AI code for performance and maintainability issues?▼

The best way to review AI code for performance and maintainability is to flag N+1 queries, memory leaks, and blocking operations. Maintainability is ensured by checking for consistent patterns, proper typing, and removing dead code.

Can I use a systematic code review process for any programming language and framework?▼

Yes, you can apply this systematic code review process across all programming languages and frameworks where AI code generation is employed. It ensures adherence to best practices and project-specific standards regardless of the stack.

How do I verify AI-generated API endpoints adhere to project conventions before merging?▼

Verify AI-generated API endpoints by checking integration adherence to project conventions, naming, and error handling. This systematic review ensures the generated code meets project standards before merging into the main branch.

What common AI mistakes should I look for when reviewing generated code?▼

Common AI mistakes to look for when reviewing generated code include hallucinated APIs, incorrect library versions, off-by-one errors, and improper null or undefined handling. Identifying these issues prevents bugs and integration failures.

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