# OpenClaw Multi-Agent Workflows - 4 Levels Explained

**Source:** https://www.reddit.com/r/openclaw/comments/1r2euvp/this_is_how_ive_learned_to_create_multiagent/
**Summarized:** 2026-02-23

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## TL;DR

OpenClaw has **4 levels of multi-agent support** built-in, from simple persistent agents to full A2A Protocol orchestration. No Docker required for levels 1-3—they all run in a single gateway process.

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## Level 1: Multiple Persistent Agents (Built-in)

Define isolated agents in config, each with their own workspace, system prompt, model, and tools:

```yaml
agents:
  list:
    - id: researcher
      default: true
      workspace: ~/.openclaw/workspace-research
    - id: coder
      workspace: ~/.openclaw/workspace-code

bindings:
  - agentId: researcher
    match: { channel: telegram, accountId: research-bot }
  - agentId: coder
    match: { channel: discord, guildId: "123456" }
```

Each agent has **full isolation**: separate session history, model config, tool permissions.

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## Level 2: Agent-to-Agent Communication (Built-in)

Enable `tools.agentToAgent` for agents to talk via `sessions_send`:

```yaml
tools:
  agentToAgent:
    enabled: true
    allow: ["researcher", "coder", "writer"]
```

- Ping-pong conversations (up to 5 turns by default)
- `sessions_spawn` for background sub-agents that report back
- Closest to "orchestrator delegates to specialist" pattern

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## Level 3: Cross-Agent Delegation (3-Level Hierarchy)

Work around single-level limits:

```
Orchestrator (main agent)
├─ sessions_send → Specialist A (sibling main agent)
│   ├─ sessions_spawn → subagent A1
│   └─ sessions_spawn → subagent A2
└─ sessions_send → Specialist B (sibling main agent)
    ├─ sessions_spawn → subagent B1
    └─ sessions_spawn → subagent B2
```

Config uses `subagents.allowAgents` for cross-agent spawning.

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## Level 4: True Multi-Agent Orchestration (A2A Protocol)

For advanced use cases with intelligent routing, review, retries, synthesis:

- **a2a-adapter**: Wraps OpenClaw agents as A2A Protocol servers
- Mix-and-match: OpenClaw + CrewAI + LangChain + n8n
- Can run as local Python processes or remote agents

Example:
```python
from a2a_adapter import load_a2a_agent, serve_agent

adapter = await load_a2a_agent({
    "adapter": "openclaw",
    "agent_id": "researcher",
    "thinking": "low",
    "async_mode": True,
})
serve_agent(agent_card=agent_card, adapter=adapter, port=9001)
```

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## Key Takeaways

| Level | Complexity | Setup |
|-------|-----------|-------|
| 1 | Low | Config only |
| 2 | Low-Medium | Config + enable tool |
| 3 | Medium | Config + cross-agent permissions |
| 4 | High | A2A Protocol + external orchestrator |

**Bottom line:** OpenClaw's built-in multi-agent (levels 1-3) requires only `~/.openclaw/config.yaml` changes—no additional infrastructure needed.