team

Manage long-lived provider LLM teammates within Claude Code workflows.

201|27|Updated May 30, 2026

Search Tags:#Claude Code #LLM integration #provider orchestration #long-lived collaboration #sustained work

Ready to run

npx skills add https://github.com/ethanhq/cc-fleet --skill team-ethanhq

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: team
Source: https://github.com/ethanhq/cc-fleet/tree/main/skills/team
Command: npx skills add https://github.com/ethanhq/cc-fleet --skill team-ethanhq

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill addresses the challenge of managing long-term collaboration with third-party LLM providers, enabling seamless integration into Claude Code's agent teams.

Core Features & Use Cases

Long-Lived Collaboration: Spawn LLM teammates that persist across turns, facilitating multi-turn discussions and sustained parallel work.
Provider Integration: Work with any Anthropic- or OpenAI-compatible model, including your Codex subscription, without a Claude subscription.
Use Case: For a sustained parallel build/work scenario, spawn multiple teammates to work on different files simultaneously, or when you need a collaborator for a multi-turn task.

Quick Start

Use the 'team' skill to spawn a long-lived LLM teammate for a sustained task. Example: /team spawn --as worker-1 --model strong

Frequently Asked Questions about team

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

FAQPage Schema

How do I orchestrate long-lived LLM teammates for sustained parallel work in Claude Code?▼

You can orchestrate long-lived LLM teammates by using the team skill to spawn provider LLM instances that persist across turns, facilitating multi-turn discussions and sustained parallel work within Claude Code workflows. Use the spawn command to assign tasks and collect results.

Can I use OpenAI-compatible models as teammates without a Claude subscription?▼

Yes, you can integrate any Anthropic- or OpenAI-compatible model, including your Codex subscription, as a long-lived teammate without requiring a Claude subscription. The skill requires Claude Code for orchestration but uses provider-specific LLM APIs for backend execution.

What is the best way to manage task assignment and resource cleanup for provider LLM teammates?▼

The best way to manage task assignment and resource cleanup is using the team skill's lifecycle management, which handles spawning long-lived provider LLM teammates, collecting their results, and executing resource cleanup automatically within Claude Code workflows.

How do I spawn multiple LLM teammates to work on different files simultaneously?▼

To spawn multiple LLM teammates for simultaneous file work, use the spawn command with distinct identifiers like `--as worker-1` and specify the model strength. This enables sustained parallel build scenarios where teammates work on different files concurrently.

What are the limitations of using long-lived provider LLM teammates for multi-turn collaboration?▼

Limitations include the requirement for Claude Code to orchestrate the provider LLM APIs and the need for provider-specific APIs for backend execution. Resource cleanup must be managed properly to avoid lingering instances after sustained multi-turn collaboration ends.