Subagent Orchestration

该工具用于高效编排OpenClaw子代理，支持Worker（文件/代码操作）、Researcher（网页调研）、Council（多模型决策）三类代理，规范生成模式、沙箱约束、超时策略，解决上下文溢出、代理超时等常见故障。典型场景含文件处理、网页调研、多模型审议等，输入为规范的sessions_spawn调用，输出子代理执行结果或统一结论，配套council-of-llms技能实现多模型议会模式。

wahajahmed010

热度 46.68

最近更新 2026-05-11 17:45:54

分类：开发依赖：代码执行 / 联网浏览搜索 / 读写文件 / MCP 服务 / 内部调用大模型应用场景：代码生成 / 调试排错 / API 集成 / 自动化脚本 ...

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add subagent-orchestration

Metadata

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"]

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

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