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orchestrate-review

Orchestrate multi-pass code reviews with specialized AI agents.

4|2|Updated Feb 21, 2026
Search Tags:#automation#quality assurance#code review#performance#security#ai agents
One-click install
npx skills add https://github.com/agent-sh/next-task --skill orchestrate-review-agent-sh
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: orchestrate-review
Source: https://github.com/agent-sh/next-task/tree/main/skills/orchestrate-review
Command: npx skills add https://github.com/agent-sh/next-task --skill orchestrate-review-agent-sh

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the complex and time-consuming process of code review by orchestrating multiple specialized AI agents to perform thorough, multi-pass checks for quality, security, and performance.

Core Features & Use Cases

  • Multi-Pass Review: Conducts distinct review passes (code quality, security, performance, etc.) in parallel.
  • Signal-Based Specialization: Dynamically selects review specialists based on code changes and project signals.
  • Automated Iteration: Iteratively fixes identified issues and re-reviews until a clean state is achieved or limits are reached.
  • Use Case: When a pull request is opened, this Skill can automatically initiate a comprehensive code review, flagging potential bugs, security vulnerabilities, and performance bottlenecks before human review, significantly speeding up the development cycle.

Quick Start

Use the orchestrate-review skill to deep review the code in the current branch.

Frequently Asked Questions about orchestrate-review

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

FAQPage Schema
How do I automate multi-pass code review for quality, security, and performance?▼

Automated multi-pass code review orchestrates specialized AI agents to conduct distinct parallel checks for code quality, security, performance, and test coverage, flagging potential bugs and vulnerabilities before human review.

How does signal-based specialization work in AI code review?▼

Signal-based specialization dynamically selects review agents by detecting specific code changes and project signals like database usage, API presence, or frontend and backend components to apply targeted analysis.

Can I automatically fix code review findings and re-evaluate the changes?▼

Automated iteration applies fixes to identified issues and re-reviews the code, continuing the cycle until a clean state is achieved or predefined review limits are met.

What is the best way to review pull requests for security vulnerabilities and performance bottlenecks?▼

Reviewing pull requests with specialized AI agents scans code changes in parallel passes, isolating security vulnerabilities and performance bottlenecks to significantly speed up the development cycle.

When do I need automated multi-pass code review instead of manual checks?▼

You need automated multi-pass code review when a pull request requires comprehensive checks across code quality, security, performance, and test coverage simultaneously to reduce manual effort.

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