review

Name: review
Availability: InStock
Author: VitaDynamics

Analyze code with multi-agent review across architecture, security, and performance.

Updated Jan 8, 2026

Search Tags:#architecture #quality assurance #code review #performance #security #multi-agent

Ready to run

npx skills add https://github.com/VitaDynamics/vita-cc-market --skill review-vitadynamics

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: review
Source: https://github.com/VitaDynamics/vita-cc-market/tree/main/plugins/Vengineer/skills/review
Command: npx skills add https://github.com/VitaDynamics/vita-cc-market --skill review-vitadynamics

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the process of conducting thorough code reviews by leveraging a diverse team of specialized AI agents, ensuring comprehensive analysis and identification of potential issues.

Core Features & Use Cases

Multi-Agent Analysis: Employs over 13 specialized reviewer agents (e.g., Architecture, Security, Performance, Language-Specific) to cover all aspects of code quality.
Structured Feedback: Delivers categorized findings with priority classifications (P1-P3) and actionable recommendations.
Use Case: Before merging a critical feature branch, use this Skill to get a detailed, multi-faceted review that catches potential bugs, security flaws, and performance bottlenecks that a single human reviewer might miss.

Quick Start

Use the review skill to analyze the current pull request.

Frequently Asked Questions about review

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

FAQPage Schema

How do I perform an exhaustive code review across multiple specialized domains like architecture and security?▼

Exhaustive code review is performed using multi-agent analysis, deploying over 13 specialized reviewer agents to identify issues across domains like architecture, security, performance, and API design. This delivers structured review documents with priority classifications and actionable recommendations.

What is the best way to automate catching performance bottlenecks and security flaws before merging a feature branch?▼

Automated multi-agent code review is the best way to catch performance bottlenecks and security flaws before merging, utilizing specialized AI agents to provide comprehensive analysis that identifies potential bugs a single human reviewer might miss.

How does multi-agent code review identify issues related to domain modeling and framework usage?▼

Multi-agent code review identifies domain modeling and framework usage issues by deploying specialized reviewer agents that analyze specific aspects of code quality, categorizing findings with priority classifications from P1 to P3 to highlight actionable recommendations.

Can I get structured feedback with priority classifications for database and DevOps integration issues?▼

Yes, you can get structured feedback for database and DevOps integration issues because the review process categorizes all findings with priority classifications and provides actionable recommendations for immediate remediation.

Does automated code analysis work for evaluating language idioms and UI/UX implementation?▼

Automated code analysis works for evaluating language idioms and UI/UX implementation by leveraging language-specific reviewer agents within its multi-agent framework to ensure comprehensive coverage of all code quality aspects.

When do I need to use a multi-agent code review process instead of a standard single review?▼

You need a multi-agent code review process when merging critical feature branches that require comprehensive analysis across architecture, security, and performance, ensuring specialized agents catch potential flaws that standard single reviews might miss.