Token导航 LogoToken导航TokenDH.com
研究检索执行命令clawhub未标认证来源可访问clear审计提醒

subagent-orchestration子 Agent 编排

Agent Skill

subagent-orchestration 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

4,079

周安装

165

GitHub Stars

公开资料未说明

下载量

1,280
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:subagent-orchestration(子 Agent 编排)
来源仓库:https://github.com/wahajahmed010/subagent-orchestration
安装命令:
openclaw skills install subagent-orchestration
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install subagent-orchestration

简介

该技能有效编排 OpenClaw 子代理,涵盖工人、研究员与理事会三种类型。

  • 提供沙箱约束与超时控制机制,确保多代理协作时的资源安全与任务收敛。
  • 输出包含生成模式建议与错误恢复策略,提升自动化流程鲁棒性。
  • 安装前需评估并发代理数量对系统负载的影响,合理设置资源上限。
  • 输出为编排指令与状态监控接口,需配合命令行工具使用,不可脱离宿主运行。

SKILL.md

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

Agent Types

TypeToolsUse For
WorkerDefault (no web)File ops, script execution, git, code changes
Researcherollama_web_search, ollama_web_fetchWeb research, API lookups, live data
CouncilDefault (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 TypeMin TimeoutRecommended
Simple file ops120s180s
Research (web)300s600s
Council/review300s600s
Complex multi-step600s900s

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

SymptomCauseFix
Agent times outCan't access web toolsUse toolsAllow or pre-fetch content
Agent times outCan't run inline PythonWrite .py file, pass path
Agent times outrunTimeoutSeconds too lowSet runTimeoutSeconds: 900 in spawn call
Agent times outGateway under load (10s spawn timeout)Kill zombie subagents, wait, retry
Agent returns nothingMissing contextPaste data in task parameter
Agent stuck in loopVague taskAdd explicit "return X" instruction
Gateway crashesContext overflow on spawnUse lightContext: true
Spawn fails (10s gateway timeout)Gateway CPU overloadKill 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
}

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

82.7%
按下载量换算1,059

安全审计

VirusTotal

通过

ClawScan

可疑

Static analysis

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install subagent-orchestration 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills