Agent Teams logo

Agent Teams

Organization
UitbreidenOS
agent-teams

Orchestrate multi-agent teams in Claude Code — set up coordinated sessions with task delegation, inter-agent communication, and parallel execution

Overview

PublisherUitbreidenOS
RepositoryUitKit
Skill nameagent-teams
Stars
14
Forks
5
Bundled files
Instructions only
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by UitbreidenOS on GitHub. Read the source before you install it.

Installation

Install the Agent Teams AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/UitbreidenOS/UitKit/tree/main/plugins/uitkit-ai-engineering/skills/agent-teams
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/UitbreidenOS/UitKit.git /tmp/UitKit
mkdir -p .claude/skills
cp -r /tmp/UitKit/plugins/uitkit-ai-engineering/skills/agent-teams .claude/skills/agent-teams
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Agent Teams in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Agent Teams on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Agent Teams is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Agent Teams Skill

When to activate

  • Complex features spanning multiple layers (frontend + backend + tests)
  • Research tasks requiring parallel investigation of competing hypotheses
  • Large refactors where multiple files can be changed independently
  • Code review requiring simultaneous analysis from different perspectives
  • Building new modules where each teammate owns a separate component

When NOT to use

  • Sequential tasks where each step depends on the previous (use a single session)
  • Same-file edits — teammates will overwrite each other
  • Simple tasks where spawning a team adds more overhead than value
  • Tasks with many inter-task dependencies — coordination cost dominates

Instructions

  1. Assess team viability. Is the work parallelizable? Do tasks touch different files? If yes to both, proceed.

  2. Define roles. Each teammate needs a clear role, scope, and boundary:

    Teammate 1: "Frontend Engineer" — React components, styling, client-side logic
    Teammate 2: "Backend Engineer" — API endpoints, database queries, validation
    Teammate 3: "QA Engineer" — Integration tests, edge cases, error handling
  3. Set up the lead session. The lead coordinates — it does NOT write code:

    Create a task list with clear ownership. Assign each task to a specific teammate.
    Use the task list as the shared communication channel.
  4. Define communication protocol. Teammates share findings via task updates, not direct messages:

    • Update task status when work is done
    • Add comments with key findings or blockers
    • Lead reviews progress and reassigns if needed
  5. Set conflict boundaries. Prevent file collisions:

    Teammate 1 owns: src/components/**, src/styles/**
    Teammate 2 owns: src/api/**, src/models/**
    Teammate 3 owns: tests/**, src/utils/validation/**
    Shared (read-only): src/config/**, package.json
  6. Synthesize results. After teammates complete their work, the lead:

    • Reviews all changes for consistency
    • Resolves any conflicts at boundaries
    • Runs integration tests to verify the pieces work together
    • Creates a unified commit with a clear message
  7. Common team patterns:

    PatternTeammatesBest for
    Layer SplitFrontend + Backend + TestsFeature development
    Hypothesis Race2-3 investigatorsDebugging complex issues
    Research Panel3-4 researchers + synthesizerArchitecture decisions
    Review PanelSecurity + Performance + DXCode review
    Module FactoryN builders (1 per module)Large scaffolding

Example

Lead: "Build a user authentication module. Teammate assignments:
- @frontend: Login form, auth context, protected routes (src/components/auth/**)
- @backend: Auth API, JWT generation, session management (src/api/auth/**)  
- @qa: Auth integration tests, token expiry tests (tests/auth/**)

Rules:
1. Don't touch files outside your scope
2. Update your task when done
3. If you need something from another teammate, add a comment — don't block

Let's go."

[Teammates work in parallel]

Lead (after all done):
"Reviewing changes... frontend and backend agree on the /auth/login contract.
Tests cover both success and failure paths. All integration tests pass.
Merging into single commit: feat(auth): add JWT authentication module"

Built with UitKit · Claude Code

Frequently asked questions

What does the Agent Teams AI skill do?

Orchestrate multi-agent teams in Claude Code — set up coordinated sessions with task delegation, inter-agent communication, and parallel execution

Why use Agent Teams on TypingMind?

Because you install it once and use it with any model. Agent Teams is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Agent Teams in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/UitbreidenOS/UitKit/tree/main/plugins/uitkit-ai-engineering/skills/agent-teams. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Agent Teams?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Agent Teams?

As many as you like. As long as a model supports skills, you can use Agent Teams with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Agent Teams AI skill free?

It is published on GitHub by UitbreidenOS. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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