Sw Agent Team Orch

What This Skill Does

The Agent Team Orchestration skill is a sophisticated framework designed to transition OpenClaw from a single-agent interface to a multi-agent ecosystem. It provides the structural scaffolding required to define specific agent roles, manage complex task lifecycles, and enforce quality control via rigorous handoff protocols. By utilizing this skill, users can orchestrate specialized agent teams where a 'Manager' agent acts as the conductor, delegating tasks to 'Specialist' agents based on their predefined expertise. It enforces a strict, state-persistent lifecycle—ranging from Inbox to Done—ensuring that work is tracked, reviewed, and finalized with high precision. This skill transforms the agent workflow from a series of ad-hoc requests into a production-grade pipeline, complete with quality gates that prevent regression and hallucinations.

Installation

To integrate this orchestration framework into your OpenClaw environment, execute the following command in your terminal: clawhub install openclaw/skills/skills/amdf01-debug/sw-agent-team-orch Ensure you have the latest version of ClawHub installed to maintain compatibility with the required shared-state management features.

Use Cases

• Complex Software Engineering: Establishing a team with a Product Manager agent, a Developer agent, and a QA agent to build and test features iteratively.
• Content Production Pipelines: Managing a team of researchers, writers, and editors to produce high-volume, quality-controlled documentation or creative assets.
• Data Engineering Workflows: Coordinating an extraction agent, a cleaning agent, and an analysis agent to process large datasets without data leakage or format inconsistency.

Example Prompts

1. "I need to set up a multi-agent team to manage my monthly blog production; please initialize the Orchestration skill using the standard software development template."
2. "Configure a task routing protocol for my research team where the Lead Researcher delegates to specific Subject Matter Experts and enforces a peer-review quality gate."
3. "Show me how to update our shared state definitions for the current agent coordination workflow to include the new API documentation requirements."

Tips & Limitations

• Focus on Atomicity: Do not overload agents with multiple concurrent tasks; this skill works best when agents remain focused on a single 'In Progress' item at a time.
• Persistence: Always rely on file-based shared state rather than relying on the agent's internal memory, which can be wiped during session resets or model restarts.
• Model Selection: Follow the strategy of using cost-efficient models for bulk processing tasks, while reserving high-reasoning, expensive models for the Manager agent’s final approval/review phase.
• Handoff Clarity: Never assume prior context. Every handoff must be explicit and structured, preferably using the provided JSON or Markdown brief templates to ensure no metadata is lost during the transfer between roles.