code-reviewer

Analyze code and generate structured review feedback for pull requests.

Updated Mar 21, 2026
One-click install
npx skills add https://github.com/d0whc3r/hackaton-cubepath --skill code-reviewer-d0whc3r
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-reviewer
Source: https://github.com/d0whc3r/hackaton-cubepath/tree/main/.agents/skills/code-reviewer
Command: npx skills add https://github.com/d0whc3r/hackaton-cubepath --skill code-reviewer-d0whc3r

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill provides expert code review guidance powered by AI to improve code quality, security, and maintainability across projects.

Core Features & Use Cases

  • AI-powered code analysis and comment generation to identify defects, security risks, and maintainability improvements
  • Integration with static analysis tools (e.g., SonarQube, CodeQL) and CI/CD workflows for automated reviews
  • PR-level feedback, remediation plans, and governance checklists to accelerate code reviews and reduce production incidents

Quick Start

Provide the codebase or PR to review and I will generate a detailed, actionable code review focused on quality, security, 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 AI-assisted code reviews for my pull requests?▼

You can automate code review by applying AI prompts and static analysis tools within CI/CD pipelines to automatically generate PR-level feedback, governance checklists, and remediation steps.

What is static analysis for code security and maintainability?▼

Static analysis tools scan source code without executing it to identify security vulnerabilities and maintainability issues, which AI-assisted reviews then translate into structured feedback and remediation plans.

Does AI code review work with existing CI/CD pipelines and static analysis tools?▼

Yes, AI code review integrates with common CI/CD workflows and static analysis tools like SonarQube or CodeQL to merge automated tool outputs with AI prompts for comprehensive PR-level feedback.

Can I use AI code review across different programming languages and frameworks?▼

Yes, AI code review applies to workflows across languages, frameworks, and PR sizes, analyzing your specific codebase to deliver targeted quality, security, and maintainability assessments.

What is the best way to perform a security audit on a large codebase?▼

The best way to perform a security audit is combining static analysis tools with AI prompts to systematically scan large codebases, producing structured feedback and remediation steps for identified risks.

How do I generate actionable remediation plans from code review findings?▼

You can generate actionable remediation plans by feeding codebase or PR diffs into an AI-assisted review, which outputs structured feedback, governance checklists, and specific remediation steps.