consensus

Coordinate multiple AI agents to review code changes and confirm consensus before implementation.

2|Updated Jan 7, 2026
One-click install
npx skills add https://github.com/Integralist/agent-skills --skill consensus-integralist
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: consensus
Source: https://github.com/Integralist/agent-skills/tree/main/.agents/skills/consensus
Command: npx skills add https://github.com/Integralist/agent-skills --skill consensus-integralist

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill helps in making complex decisions by enabling collaborative reviews among multiple AI agents, ensuring thorough discussion and consensus before implementation.

Core Features & Use Cases

  • Multi-Agent Review: Invokes and coordinates multiple AI agents for code review and assessment.
  • User-Driven Approval: Only proceeds with implementation after user confirms the consensus.
  • Use Case: Ideal for architectural changes, multi-file features, and investigations where a broad consensus is necessary before proceeding.

Quick Start

Run the consensus skill to review and agree upon changes to your codebase.

Frequently Asked Questions about consensus

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

FAQPage Schema
How do I use multi-agent review for complex architectural code changes?

Multi-agent review coordinates several AI agents to assess architectural code changes, fostering thorough discussion. It ensures comprehensive evaluation and user-confirmed consensus before any implementation proceeds on non-trivial features.

What is consensus building in collaborative code review?

Consensus building in code review is a process where multiple AI agents evaluate changes together. It requires user validation to confirm agreements, ensuring that complex decisions and multi-file developments are thoroughly vetted before implementation.

When do I need multiple AI agents for decision-making in software engineering?

You need multiple AI agents for decision-making when handling architectural changes, multi-file feature developments, or investigations. This collaborative assessment ensures broad consensus is reached and user-validated before complex code modifications are applied.

Does collaborative AI code review require user validation before implementing changes?

Yes, collaborative AI code review requires user validation before implementing changes. The process mandates user-driven approval to confirm the consensus reached by the multiple AI agents, ensuring you retain control over modifications.

Can I use multi-agent review for investigating non-trivial code changes across multiple files?

Yes, you can use multi-agent review for investigating non-trivial code changes across multiple files. It is specifically designed to coordinate multiple AI agents for comprehensive assessments, ensuring thorough discussion and consensus for complex feature developments.