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.