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Open Agent Teams

OrganizationPopular
AI-Builder-Club
open-agent-teams

Delegate tasks to ANY CLI agent (claude, codex, aider, ...) running in a detached tmux session, with a race-safe done-signal protocol and multi-turn iteration. Use when delegating work to a non-Claude CLI agent, when the user says "tmux delegate", "run agent in tmux", "delegate to codex/aider", or when executor work should run in an observable background terminal instead of the Agent tool.

Overview

PublisherAI-Builder-Club
Repositoryskills
Skill nameopen-agent-teams
Stars
1.3K
Forks
159
Bundled files
2
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.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by AI-Builder-Club on GitHub. Read the source before you install it.

Installation

Install the Open 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.
  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/AI-Builder-Club/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/open-agent-teams .claude/skills/open-agent-teams
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Open 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 Open 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 Open 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.

open-agent-teams

Run any CLI agent as an executor inside a detached tmux session. Communication is: prompt in via CLI arg / send-keys, completion out via a file sentinel the agent touches, summary out via a result file the agent writes. File sentinels are used instead of tmux wait-for because a wait-for -S with no waiter is silently lost; files never race and allow timeouts.

All commands via the helper (make sure it runs from the skill dir):

SKILL_DIR/scripts/tdel

Initial setup (once per repo)

If the repo's CLAUDE.md (or AGENT.md) has no delegation rules yet, add the contents of references/CLAUDE.delegation-template.md to it — it defines the coordinator/executor roles and the ROLE: EXECUTOR prompt marker used below.

Workflow

  1. Start an agent on a task:

    tdel start <session> "<agent-cmd>" "<prompt>"
    # e.g. tdel start hello "claude --dangerously-skip-permissions" "make a hello world page"

    This appends the done-protocol to the prompt automatically (write summary to result file, then touch the done file).

  2. Wait for completion — ALWAYS via a background Bash task so you get woken up instead of blocking or polling:

    tdel wait <session> [timeout-sec]     # run with run_in_background: true

    Exit 0 = done (prints the agent's summary). Exit 124 = timeout (prints last pane lines for diagnosis). Non-zero also if the session died.

  3. Review the output (tdel result <session>, plus inspect the actual files the agent changed). If iteration is needed:

    tdel send <session> "<feedback / next instruction>"
    tdel wait <session>                   # again, run_in_background

    Each send is a new turn with its own done/result files — no signal cross-talk between turns.

  4. Debug a stuck or slow agent: tdel peek <session> [lines] shows the live pane. tdel status lists all sessions.

  5. Stop when finished: tdel stop <session> (kills the session and removes state under /tmp/agent-delegate/<session>).

Harness reference

How to launch each CLI agent autonomously (prompt is passed as the last positional arg by tdel start):

Harnessagent-cmd for tdel startBusy-pane signatureExitInterrupt
claudeclaude --dangerously-skip-permissions (--model, --effort low..max)esc to interrupt/exitEscape
codexcodex --dangerously-bypass-approvals-and-sandbox (--model, -c 'model_reasoning_effort="low..xhigh"')esc to interrupt/quitEscape
grokgrok --always-approve (--model, --reasoning-effort low|medium|high)Ctrl+c:cancelCtrl+Q twice within 1s (NOT /exit, NOT Ctrl+C)Ctrl+C (Escape does NOT interrupt)
pipi (--model, --thinking low..max; no permission system — always autonomous)Working.../quitEscape
opencodeopencode --prompt-style launch (--model provider/model)esc interrupt (no "to")/exitdouble Escape (flaky mid-shell-command)

Busy signatures matter on timeout: peek and grep for the signature — present = still working (extend the wait), absent = idle (it likely finished without touching the done file, or is stuck at a prompt).

Trust dialogs (first run per repo/worktree): claude (trust/bypass-permissions confirm), codex ("Do you trust..."), and pi can each show a dialog that blocks the prompt from processing. After start, peek within ~20s; if a dialog is showing, accept it with tdel key <session> Enter and verify via another peek that the task started. grok skips its picker when launched inside a git repo root.

Slash/skill popup hazard: prompts beginning with / or $ (skill invocations: /<skill> on claude/grok, $<skill> on codex) open an autocomplete popup — a fast Enter selects the popup instead of submitting, and grok needs a genuine second Enter. tdel send handles this automatically (longer settle + double Enter for /- or $-prefixed prompts).

Resume after exit: codex codex resume <session-id>, grok grok --resume <session-id> (ids printed on quit), opencode relaunch with --continue.

Rules

  • Prompts must be self-contained (context, constraints, expected output) — the executor can't see your conversation. Prefix with the repo's executor marker (ROLE: EXECUTOR ...) when the agent is Claude Code in a repo using the delegation rules (see Initial setup above).
  • Prompts are flattened to one line before sending (newlines would submit a TUI input box early) — write them accordingly; put large specs in a file and reference the path.
  • On timeout, peek first — agents sometimes finish but forget to touch the done file. If the work is visibly done, treat pane output + changed files as the result and stop or send a reminder.
  • Don't trust capture-pane as the deliverable — it's a rendered TUI snapshot. The result file and the actual changed files are the source of truth.
  • One task per session; parallel tasks = parallel sessions with distinct names.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Open Agent Teams AI skill do?

Delegate tasks to ANY CLI agent (claude, codex, aider, ...) running in a detached tmux session, with a race-safe done-signal protocol and multi-turn iteration. Use when delegating work to a non-Claude CLI agent, when the user says "tmux delegate", "run agent in tmux", "delegate to codex/aider", or when executor work should run in an observable background terminal instead of the Agent tool.

Why use Open Agent Teams on TypingMind?

Because you install it once and use it with any model. Open 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 Open Agent Teams in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AI-Builder-Club/skills/tree/main/skills/open-agent-teams. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Open 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 Open Agent Teams?

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

Is the Open Agent Teams AI skill free?

It is published on GitHub by AI-Builder-Club. 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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