team-collaboration

Coordinate multiple AI agents using sequential handoff, fan-out, and synthesis patterns.

Updated Feb 16, 2026
One-click install
npx skills add https://github.com/michaeljabbour/amplifier-bundle-letsgo --skill team-collaboration-michaeljabbour
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: team-collaboration
Source: https://github.com/michaeljabbour/amplifier-bundle-letsgo/tree/main/skills/team-collaboration
Command: npx skills add https://github.com/michaeljabbour/amplifier-bundle-letsgo --skill team-collaboration-michaeljabbour

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides structured patterns for coordinating multiple AI agents to work together on complex tasks, ensuring efficient delegation, context management, and convergence.

Core Features & Use Cases

  • Multi-Agent Coordination: Implements patterns like sequential handoff, fan-out, and synthesis for complex problem-solving.
  • Context Management: Controls how information is passed between agents using delegate() parameters.
  • Use Case: Automate a code review process where one agent designs, another implements, and a third reviews, with the coordinator synthesizing feedback.

Quick Start

Use the team-collaboration skill to orchestrate a sequential handoff between an architect agent and a builder agent.

Frequently Asked Questions about team-collaboration

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

FAQPage Schema
How do I coordinate multiple AI agents to work together on complex tasks?

Multi-agent coordination is achieved using the actor model and explicit delegation, employing patterns like sequential handoff, fan-out, and synthesis to ensure efficient task decomposition and convergence.

What is the best way to automate a multi-step code review process across different agents?

Automating a code review process involves orchestrating a sequential handoff where one agent designs, another implements, and a third reviews, with the coordinator synthesizing the final feedback.

How does context management work when passing information between agents in a workflow?

Context management between agents is handled using configurable scope and depth parameters within the delegate() function, controlling exactly what information is passed during inter-agent communication.

When should I use fan-out and synthesis patterns for task decomposition?

Fan-out and synthesis patterns are used for complex problem-solving when a task must be decomposed into parallel sub-tasks, requiring a coordinator to synthesize the individual agent outputs back into a unified result.

Can I use multi-agent orchestration without any external dependencies?

Yes, multi-agent orchestration operates entirely within the Amplifier framework using internal references, requiring no external dependencies to manage sequential handoffs or fan-out workflows.

What are the limitations of using explicit delegation for inter-agent communication?

Explicit delegation requires careful configuration of scope and depth parameters to manage context, meaning poorly configured delegate() calls can lead to insufficient information passing between the architect and builder agents.