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Multi Agent Coordinator

Community
ArchieIndian
multi-agent-coordinator

Orchestrates multiple parallel OpenClaw agents — tracks health, detects timeouts, reconciles conflicting outputs, and manages structured handoffs

Overview

PublisherArchieIndian
Repositoryopenclaw-superpowers
Skill namemulti-agent-coordinator
Stars
74
Forks
14
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

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

Installation

Install the Multi Agent Coordinator 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/ArchieIndian/openclaw-superpowers/tree/main/skills/openclaw-native/multi-agent-coordinator
  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/ArchieIndian/openclaw-superpowers.git /tmp/openclaw-superpowers
mkdir -p .claude/skills
cp -r /tmp/openclaw-superpowers/skills/openclaw-native/multi-agent-coordinator .claude/skills/multi-agent-coordinator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multi Agent Coordinator 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 Multi Agent Coordinator 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 Multi Agent Coordinator 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.

multi-agent-coordinator

When running 3+ OpenClaw agents in parallel, the flat agents.list[] config becomes unmanageable, channel "bleeding" occurs between agents, parallel agents can produce contradictory outputs, and there is no timeout detection for silent agent failures.

This skill lives in the orchestrator agent and provides: a shared agent registry, health-check heartbeats, output consistency checks, and structured inter-agent handoffs.

Agent registry

Register each sub-agent when it starts:

python3 run.py --register agent-id=coder role=code_implementation channel=C001
python3 run.py --register agent-id=reviewer role=code_review channel=C002

The registry tracks: agent ID, role, channel, status, last-seen timestamp, and current task.

Health checks

The orchestrator pings each registered agent's last-seen timestamp. An agent is considered timed out if it hasn't updated in longer than the configured timeout (default: 30 minutes).

Invoke periodically:

python3 run.py --health-check

On timeout detection: write AGENT_TIMEOUT to state, alert the orchestrator, and prompt: "Agent coder hasn't responded in 45 minutes. Reassign task or wait?"

Output consistency checkpoint

Before merging parallel agent outputs:

python3 run.py --consistency-check --agents coder reviewer --key "api_design"

The orchestrator compares outputs for the same key and flags contradictions. Example: coder proposes POST /users, reviewer proposes PUT /users/{id} for the same operation — these are flagged as contradictions requiring human resolution before merge.

Structured handoff

Pass context from one agent to another:

python3 run.py --handoff --from coder --to reviewer --task-file handoff.yaml

Handoff files capture: what was done, what wasn't, key decisions made, constraints discovered, and next recommended action. This extends task-handoff (which is single-agent) to the multi-agent case.

Difference from workflow-orchestration

workflow-orchestration executes a linear sequence of steps in a single agent. multi-agent-coordinator manages a parallel fleet: independent agents with their own sessions, channels, and context windows.

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 Multi Agent Coordinator AI skill do?

Orchestrates multiple parallel OpenClaw agents — tracks health, detects timeouts, reconciles conflicting outputs, and manages structured handoffs

Why use Multi Agent Coordinator on TypingMind?

Because you install it once and use it with any model. Multi Agent Coordinator 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 Multi Agent Coordinator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ArchieIndian/openclaw-superpowers/tree/main/skills/openclaw-native/multi-agent-coordinator. 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 Multi Agent Coordinator?

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 Multi Agent Coordinator?

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

Is the Multi Agent Coordinator AI skill free?

It is published on GitHub by ArchieIndian. 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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