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agent-cross-review

Coordinate structured cross-review protocols between specialized AI agents with priority tiers.

2|1|Updated Dec 26, 2025
Search Tags:#quality assurance#code review#feedback#protocol#handoff#agent collaboration
One-click install
npx skills add https://github.com/1ambda/dataops-platform --skill agent-cross-review
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: agent-cross-review
Source: https://github.com/1ambda/dataops-platform/tree/main/.copilot/skills/agent-cross-review
Command: npx skills add https://github.com/1ambda/dataops-platform --skill agent-cross-review

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides a structured protocol for agents to review each other's work, ensuring alignment on scope, calibration of priorities, and domain-aware feedback, preventing miscommunication and improving overall output quality.

Core Features & Use Cases

  • Structured Review Protocol: Defines clear steps for identifying scope, checking domain relevance, and providing calibrated feedback using priority tiers (CRITICAL, MAJOR, MINOR, DEFER).
  • Role-Specific Guidance: Offers tailored review focus areas and deferral points for different agent types (e.g., Feature Agent, Expert Agent, Architecture).
  • Handoff & Conflict Resolution: Facilitates smooth transitions between agents and provides a framework for resolving disagreements.
  • Use Case: When a feature-interface-cli agent completes a new command implementation, it can use this skill to initiate a cross-review with an expert-python agent to ensure code quality and adherence to Python best practices, while the expert-python agent defers on CLI-specific structural decisions.

Quick Start

Initiate a cross-review for the 'basecamp-server' artifact, with the reviewer being 'agent-cross-review' and the author being 'basecamp-server'.

Frequently Asked Questions about agent-cross-review

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

FAQPage Schema
How do I set up an agent-to-agent code review protocol?▼

To set up an agent-to-agent code review protocol, define the reviewer and author roles, establish artifact context, and apply priority tiers like CRITICAL, MAJOR, MINOR, and DEFER for calibrated feedback.

What is structured cross-review for AI agents?▼

Structured cross-review is a protocol for specialized AI agents to validate work, ensuring scope alignment, priority calibration, and domain-aware feedback during handoffs and cross-cutting concern checks.

How do I handle task handoffs between specialized AI agents?▼

Handle task handoffs between specialized AI agents by using a structured cross-review protocol that defines role-specific guidance, deferral points for different agent types, and a framework for conflict resolution.

Can I use this protocol for agents with different domain expertise?▼

Yes, you can use this protocol for agents with different domain expertise by providing role-specific guidance and deferral points, allowing an expert agent to focus on domain rules while deferring structural decisions.

What are the limitations of automated code review between agents?▼

A limitation of automated code review between agents is the requirement for clear definition of reviewer and author roles, artifact context, and feedback tiers, without which effective collaboration and scope alignment cannot be achieved.

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