agent-collaboration

Coordinate multi-agent collaboration with uniform worktree awareness and decision recording.

Updated Apr 6, 2026
One-click install
npx skills add https://github.com/jperezdelreal/GymBro --skill agent-collaboration-jperezdelreal
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: agent-collaboration
Source: https://github.com/jperezdelreal/GymBro/tree/main/.copilot/skills/agent-collaboration
Command: npx skills add https://github.com/jperezdelreal/GymBro --skill agent-collaboration-jperezdelreal

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Squad-level AI agents often operate without consistent collaboration patterns, causing miscommunication and inconsistent decisions. This skill centralizes worktree awareness, decision recording, and cross-agent communication into a single, repeatable protocol the squad can follow.

Core Features & Use Cases

  • Unified collaboration patterns: Standardized guidelines for worktree awareness, decision logging, and inter-agent messaging.
  • Traceability & accountability: Centralized decisions inbox and history references to track decisions over time.
  • Scalability: Works for any squad size and agent type, reducing duplication across charters and speeding on-boarding.

Quick Start

Provide a ready-to-use standard collaboration pattern for all squad agents, covering worktree awareness, decisions, and cross-agent communication.

Frequently Asked Questions about agent-collaboration

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

FAQPage Schema
How do I standardize multi-agent collaboration protocols for a development squad?

Standardize multi-agent collaboration by applying uniform worktree awareness, decision logging, and cross-agent communication guidelines. This enforces consistency by routing decisions to a centralized inbox and referencing shared history files, ensuring all squad agents operate under a repeatable protocol.

What is the best way to log cross-agent decisions for traceability?

Log cross-agent decisions for traceability by recording them to a centralized inbox and reading from decisions.md and history.md. This centralized approach maintains accountability over time and prevents agents from editing each other's artifacts.

How do I prevent AI agents from overwriting each other's worktree artifacts?

Prevent agents from overwriting artifacts by enforcing strict worktree awareness and a protocol that avoids edits to other agents' artifacts. Agents must read shared history files and log decisions centrally instead of modifying files directly.

Can I scale a standardized collaboration pattern to any squad size and agent type?

Yes, you can scale this collaboration pattern to any squad size and agent type. It reduces duplication across charters and speeds onboarding by providing a single repeatable protocol for worktree awareness and inter-agent messaging.

Why does my squad of AI agents have inconsistent decisions and miscommunication?

Squad agents have inconsistent decisions and miscommunication when they operate without consistent collaboration patterns. Centralizing worktree awareness and decision recording into a single protocol eliminates these issues and maintains traceability.