reviewer-protocol

Enforce reviewer rejection workflows with strict lockout semantics for AI agents.

3.1k|475|Updated Feb 6, 2026

Search Tags:#quality assurance #code review #orchestration #agent protocol #rejection workflow #lockout semantics

Ready to run

npx skills add https://github.com/bradygaster/squad --skill reviewer-protocol

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: reviewer-protocol
Source: https://github.com/bradygaster/squad/tree/main/.squad/skills/reviewer-protocol
Command: npx skills add https://github.com/bradygaster/squad --skill reviewer-protocol

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill prevents inefficient feedback loops by enforcing strict rules when a reviewer rejects work, ensuring that the original author does not self-revise and that independent review is maintained.

Core Features & Use Cases

Reviewer Rejection Protocol: Defines clear actions (reassign or escalate) for reviewers when rejecting work.
Strict Lockout Semantics: Ensures the original author is locked out of revisions after rejection, mandating a different agent to perform the fix.
Deadlock Handling: Provides a mechanism to escalate to the user if all eligible agents are locked out.
Use Case: When a code review is rejected, this protocol ensures a different developer fixes the issue, rather than the original author making immediate changes, promoting objective code improvement.

Quick Start

When a reviewer rejects work, ensure a different agent is assigned to make the revisions.

Frequently Asked Questions about reviewer-protocol

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

FAQPage Schema

How do I enforce a strict code review rejection workflow where the original author cannot self-revise?▼

To enforce a strict code review rejection workflow with lockout semantics, this protocol prevents the original author from self-revising rejected work and mandates a different agent to perform the fix. It manages reassignment or escalation to maintain objective quality assurance.

What happens during agent orchestration if all eligible agents are locked out after a rejection?▼

If all eligible agents are locked out after a rejection, the protocol provides a deadlock handling mechanism that escalates the rejected work to the user. This prevents inefficient feedback loops when no independent agents are available to perform revisions.

Can I use this rejection protocol to manage quality assurance across multiple AI agents?▼

Yes, you can use this rejection protocol to manage quality assurance across agent teams. It orchestrates reviewer actions by reassigning rejected work to different agents or escalating it, ensuring independent review processes within your AI agent workflows.

What's the best way to handle code review reassignment to prevent agents from reviewing their own fixes?▼

The best way to prevent agents from reviewing their own fixes is applying strict lockout semantics. When a reviewer rejects work, the protocol locks out the original author and automatically orchestrates reassignment of the revision task to a different agent.

Why does an agent orchestration workflow need lockout semantics for rejection workflows?▼

An agent orchestration workflow needs lockout semantics to prevent inefficient feedback loops caused by self-revision. Enforcing that a different agent performs revisions after a code review rejection maintains objective quality assurance and independent oversight.

Does the reviewer-protocol support escalation when no agents are available for reassignment?▼

Yes, the reviewer-protocol supports escalation when no agents are available for reassignment. It includes deadlock handling that escalates the rejected work to the user when all eligible agents are locked out, ensuring the quality assurance process is not stalled.