OpenClaw

agent-orchestrator

Meta-agent skill for orchestrating complex tasks through autonomous sub-agents. Decomposes macro tasks into subtasks, spawns specialized sub-agents with dynamically generated SKILL.md files, coordinates file-based communication, consolidates results, and dissolves agents upon completion. MANDATORY TRIGGERS: orchestrate, multi-agent, decompose task, spawn agents, sub-agents, parallel agents, agent coordination, task breakdown, meta-agent, agent factory, delegate tasks

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查看来源 ↗安装与使用 SKILL.md ↗

安装与使用

请根据来源仓库和你的 AI 工具说明安装此技能。先阅读技能文件和依赖要求，再添加到工作流。

SkillHub CLI

skillhub install aatmaan1/agent-orchestrator

打开来源仓库，查看说明和兼容环境后，按来源提供的命令或步骤安装。

将来源链接提供给你的 Agent，让它先读取说明、核对依赖，并向你说明将执行的安装步骤。

查看来源 ↗使用指南

技能说明

Agent Orchestrator

Orchestrate complex tasks by decomposing them into subtasks, spawning autonomous sub-agents, and consolidating their work.

Core Workflow

Phase 1: Task Decomposition

Analyze the macro task and break it into independent, parallelizable subtasks:

1. Identify the end goal and success criteria
2. List all major components/deliverables required
3. Determine dependencies between components
4. Group independent work into parallel subtasks
5. Create a dependency graph for sequential work

Decomposition Principles:

Each subtask should be completable in isolation
Minimize inter-agent dependencies
Prefer broader, autonomous tasks over narrow, interdependent ones
Include clear success criteria for each subtask

Phase 2: Agent Generation

For each subtask, create a sub-agent workspace:

python3 scripts/create_agent.py <agent-name> --workspace <path>

This creates:

<workspace>/<agent-name>/
âââ SKILL.md          # Generated skill file for the agent
âââ inbox/            # Receives input files and instructions
âââ outbox/           # Delivers completed work
âââ workspace/        # Agent's working area
âââ status.json       # Agent state tracking

Generate SKILL.md dynamically with:

Agent's specific role and objective
Tools and capabilities needed
Input/output specifications
Success criteria
Communication protocol

See references/sub-agent-templates.md for pre-built templates.

Phase 3: Agent Dispatch

Initialize each agent by:

Writing task instructions to inbox/instructions.md
Copying required input files to inbox/
Setting status.json to {"state": "pending", "started": null}
Spawning the agent using the Task tool:

# Spawn agent with its generated skill
Task(
    description=f"{agent_name}: {brief_description}",
    prompt=f"""
    Read the skill at {agent_path}/SKILL.md and follow its instru...

来源信息

Source: github
Repository: openclaw/skills
Path: skills/aatmaan1/agent-orchestrator
Version: —
Commit: bce999a730b5ee2e265a9e2af2251e77ee409085
分类来源: rules
状态: active
可见性: public

这些信息来自收录时的来源分析，可能滞后；使用前请核对最新来源文件。

来源内容

SKILL.md

# Agent Orchestrator

Orchestrate complex tasks by decomposing them into subtasks, spawning autonomous sub-agents, and consolidating their work.

## Core Workflow

### Phase 1: Task Decomposition

Analyze the macro task and break it into independent, parallelizable subtasks:

```
1. Identify the end goal and success criteria
2. List all major components/deliverables required
3. Determine dependencies between components
4. Group independent work into parallel subtasks
5. Create a dependency graph for sequential work
```

**Decomposition Principles:**
- Each subtask should be completable in isolation
- Minimize inter-agent dependencies
- Prefer broader, autonomous tasks over narrow, interdependent ones
- Include clear success criteria for each subtask

### Phase 2: Agent Generation

For each subtask, create a sub-agent workspace:

```bash
python3 scripts/create_agent.py <agent-name> --workspace <path>
```

This creates:
```
<workspace>/<agent-name>/
âââ SKILL.md # Generated skill file for the agent
âââ inbox/ # Receives input files and instructions
âââ outbox/ # Delivers completed work
âââ workspace/ # Agent's working area
âââ status.json # Agent state tracking
```

**Generate SKILL.md dynamically** with:
- Agent's specific role and objective
- Tools and capabilities needed
- Input/output specifications
- Success criteria
- Communication protocol

See [references/sub-agent-templates.md](references/sub-agent-templates.md) for pre-built templates.

### Phase 3: Agent Dispatch

Initialize each agent by:

1. Writing task instructions to `inbox/instructions.md`
2. Copying required input files to `inbox/`
3. Setting `status.json` to `{"state": "pending", "started": null}`
4. Spawning the agent using the Task tool:

```python
# Spawn agent with its generated skill
Task(
description=f"{agent_name}: {brief_description}",
prompt=f"""
Read the skill at {agent_path}/SKILL.md and follow its instru...

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