Subagent Orchestration

---

name: subagent-orchestration description: "Orchestrate OpenClaw subagents effectively. Covers all three agent types (Worker, Researcher, Council) with correct spawning patterns, sandbox constraints, timeout strategies, and failure mode fixes. Includes multi-model council pattern via the council-of-llms companion skill. Prevents common failures: context overflow, gateway timeouts, web tool access, inline Python restrictions. Triggers on: spawn, delegate, subagent, agent timeout, agent failure, orchestration, multi-agent, council." tags: - subagent - orchestration - delegation - spawning - timeout - council - multi-agent - parallel - worker - researcher

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Subagent Orchestration

Agent Types

| Type | Tools | Use For | |------|-------|---------| | Worker | Default (no web) | File ops, script execution, git, code changes | | Researcher | ollama_web_search, ollama_web_fetch | Web research, API lookups, live data | | Council | Default (no web) | Analysis, review, decision-making with passed context |

Sandbox Constraints

Default subagents (Worker/Council) cannot:

Use ollama_web_fetch or ollama_web_search

Run python3 -c "..." inline commands

Access the main session's conversation history

They can:

Read/write files

Run scripts from .py files (python3 /path/to/script.py)

Execute simple shell commands

Use exec, read, write, edit tools

Spawning Patterns

Researcher (Web-Enabled)

sessions_spawn(
  toolsAllow: ["ollama_web_fetch", "ollama_web_search"],
  runtime: "subagent",
  mode: "run",
  lightContext: true,
  runTimeoutSeconds: 600,
  task: "Research X. Return: findings, sources, key metrics."
)

Worker (File/Code Ops)

sessions_spawn(
  runtime: "subagent",
  mode: "run",
  lightContext: true,
  runTimeoutSeconds: 300,
  task: "Run python3 /path/to/script.py. Report output."
)

Council (Multi-Model Deliberation)

# Spawn 3 parallel subagents with different models and perspectives
See skills/council-of-llms/SKILL.md for full details
sessions_spawn(model: "ollama/kimi-k2.6:cloud", label: "Council-Strategos", ...)
sessions_spawn(model: "ollama/deepseek-v4-pro:cloud", label: "Council-Analyticos", ...)
sessions_spawn(model: "ollama/gemma4:31b-cloud", label: "Council-Creativos", ...)
Then synthesize all 3 outputs into a unified verdict

Single-Model Council (Legacy — Avoid)

# WARNING: Single-model councils cause context overflow and produce shallow analysis
Use multi-model pattern above instead
sessions_spawn(
  runtime: "subagent",
  mode: "run",
  lightContext: true,
  runTimeoutSeconds: 900,
  task: "Review this data and decide: [data pasted inline]. Return: verdict, conditions, risks."
)

Timeout Strategy

| Task Type | Min Timeout | Recommended | |-----------|------------|-------------| | Simple file ops | 120s | 180s | | Research (web) | 300s | 600s | | Council/review | 300s | 600s | | Complex multi-step | 600s | 900s |

Never rush agents. Quality > speed. If an agent takes >60s, give the user a brief status update.

Delegation Rules

1. Never run long scripts yourself. Write the script, hand the file path to a subagent. 2. Pre-fetch web content yourself for Worker/Council agents — they can't browse. 3. Use Researcher agents when you need web data that subagents can't access. 4. Write .py files first — don't pass inline Python to subagents. 5. Paste context inline — Council agents don't have your conversation history.

Common Failure Modes

| Symptom | Cause | Fix | |---------|-------|-----| | Agent times out | Can't access web tools | Use toolsAllow or pre-fetch content | | Agent times out | Can't run inline Python | Write .py file, pass path | | Agent times out | runTimeoutSeconds too low | Set runTimeoutSeconds: 900 in spawn call | | Agent times out | Gateway under load (10s spawn timeout) | Kill zombie subagents, wait, retry | | Agent returns nothing | Missing context | Paste data in task parameter | | Agent stuck in loop | Vague task | Add explicit "return X" instruction | | Gateway crashes | Context overflow on spawn | Use lightContext: true | | Spawn fails (10s gateway timeout) | Gateway CPU overload | Kill stale subagents first, then retry |

Anti-Patterns

❌ Doing research yourself when a Researcher agent could handle it

❌ Running python3 -c inline in task descriptions

❌ Setting 120s timeouts on research tasks

❌ Re-spawning an agent that's still running (>60s = be patient)

❌ Not passing context because "the agent should know"

Config (openclaw.json)

Set subagent defaults in ~/.openclaw/openclaw.json:

{
  "agents": {
    "defaults": {
      "subagents": {
        "runTimeoutSeconds": 900,
        "maxConcurrent": 5
      }
    }
  }
}

Also set in ~/.openclaw/council-config.json:

{
  "default_timeout": 900,
  "max_tokens": 8192
}