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Official Verified productivity Safety 4/5

agent-team-orchestration

Orchestrate multi-agent teams with defined roles, task lifecycles, handoff protocols, and review workflows. Use when: (1) Setting up a team of 2+ agents with different specializations, (2) Defining task routing and lifecycle (inbox → spec → build → review → done), (3) Creating handoff protocols between agents, (4) Establishing review and quality gates, (5) Managing async communication and artifact sharing between agents.

skill-install — Terminal

Install via CLI (Recommended)

clawhub install openclaw/skills/skills/arminnaimi/agent-team-orchestration
Or

What This Skill Does

The agent-team-orchestration skill provides a robust framework for managing multi-agent systems within OpenClaw. It shifts the burden of task management from manual oversight to an automated, role-based architecture. By enforcing structured task lifecycles (Inbox → Spec → Build → Review → Done), this skill prevents the 'agent drift' common in complex workflows. It enables developers to define specialized roles such as Orchestrators, Builders, Reviewers, and Ops, ensuring that each agent focuses on its core competency. The system promotes high-quality outcomes through mandatory review gates and standardized handoff protocols, which are critical for maintaining consistency in collaborative AI environments.

Installation

To integrate this orchestration framework into your OpenClaw environment, execute the following command in your terminal:

clawhub install openclaw/skills/skills/arminnaimi/agent-team-orchestration

Ensure that your environment has sufficient permissions for the agent to read and write to the shared artifact directories specified in your workflow configuration.

Use Cases

  • Software Development Teams: Deploy a Builder to write feature code and a Reviewer to perform automated code audits and security checks.
  • Content Production Pipelines: Use an Orchestrator to route research notes to a Writer, then to an Editor for tone and compliance verification.
  • Automated Data Processing: Coordinate an Ops agent to trigger daily data ingestions, with a secondary agent to validate the dataset integrity before final reporting.
  • Research Projects: Manage a team of agents that scrape data, synthesize findings, and generate a final whitepaper based on predefined editorial standards.

Example Prompts

  1. "Initialize a 3-agent team with an Orchestrator, a Python Developer, and a QA Reviewer to build a REST API for my user management service. Define the lifecycle as Inbox -> Spec -> Build -> Review."
  2. "Update my project orchestration to include a new quality gate: the Reviewer must now verify that all unit tests pass before moving any ticket from 'In Progress' to 'Done'."
  3. "Set up an async handoff protocol between the Data Scraper and the Data Analyst. Ensure the Analyst receives a summary of missing fields and the file path of the CSV artifacts."

Tips & Limitations

To maximize effectiveness, avoid assigning multiple roles to a single agent to prevent logic conflicts. Always enforce the 'Orchestrator-owns-state' rule; if agents update their own statuses, you lose the ability to audit the global pipeline. Note that this skill requires high-reasoning models for the Orchestrator and Reviewer roles; using cheaper models for these functions often leads to degraded quality control. For smaller tasks, this orchestration overhead may be unnecessary—use this for projects requiring high reliability and structured output.

Metadata

Stars4473
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Updated2026-05-01
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Add to Configuration

Paste this into your clawhub.json to enable this plugin.

{
  "plugins": {
    "official-arminnaimi-agent-team-orchestration": {
      "enabled": true,
      "auto_update": true
    }
  }
}

Tags(AI)

#multi-agent#workflow#automation#collaboration#orchestration
Safety Score: 4/5

Flags: file-write, file-read, code-execution