team

Spawns and coordinates an agent team for parallel work from a task description or task graph.

Updated Mar 9, 2026
One-click install
npx skills add https://github.com/justinpbarnett/claude --skill team-justinpbarnett
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: team
Source: https://github.com/justinpbarnett/claude/tree/main/skills/team
Command: npx skills add https://github.com/justinpbarnett/claude --skill team-justinpbarnett

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill tackles complex tasks by orchestrating multiple AI agents working in parallel, significantly speeding up development and problem-solving.

Core Features & Use Cases

  • Parallel Task Execution: Breaks down large tasks into sub-tasks that can be handled concurrently by different agents.
  • Role Assignment: Assigns specific roles and file ownership to each agent for clear responsibilities.
  • Team Coordination: Monitors progress, handles failures, and integrates the work of all team members.
  • Use Case: Refactoring multiple microservices simultaneously, where each service can be handled by a dedicated agent.

Quick Start

Use the team skill to refactor the auth and payments modules in parallel.

Frequently Asked Questions about team

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

FAQPage Schema
How do I coordinate multiple AI agents for parallel task execution?

To coordinate parallel task execution, you provide a task description, spec file path, or decomposed task graph. The system then determines optimal team composition, assigns roles with file ownership, and monitors execution to handle complex distributed workflows.

What is the best way to refactor multiple microservices simultaneously?

Refactoring multiple microservices simultaneously is handled by spawning an agent team where each agent takes ownership of a specific service. This allows independent work streams to be processed concurrently for faster development.

When do I need to use distributed agents for workflow automation?

Distributed agents are needed for workflow automation when a complex task requires at least three independent work streams. This allows the workload to be decomposed and processed concurrently rather than sequentially.

How does task decomposition work for agent coordination?

Task decomposition for agent coordination involves accepting a task graph and breaking it into sub-tasks. The system then assigns specific roles and file ownership to each agent to ensure clear responsibilities during parallel processing.

Can I use a spec file path to initiate parallel processing?

Yes, you can initiate parallel processing by providing a spec file path. The system reads the specification to determine the optimal team composition, assigns roles, and monitors the distributed agents during execution.

How are failures handled during team coordination of independent work streams?

During team coordination, failures are handled by the monitoring system which tracks execution progress. It manages the integration of all team members and addresses issues to maintain efficient parallel processing across independent work streams.