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Agent Skill · 研究检索

more-agent-orchestrator(更多 Agent 协调器)

more-agent-orchestrator 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。

more-agent-orchestrator 是研究检索类 Agent Skill,可用宿主为 OpenClaw,通过ClawHub获取,权限为执行命令;许可证为 MIT-0,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 13,534。

总安装 9,302周安装 380GitHub Stars 公开资料未说明下载 2,979核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT-0
版本
1.0.0

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:more-agent-orchestrator(更多 Agent 协调器)
来源仓库:https://github.com/lcp14262/more-agent-orchestrator
安装命令:
openclaw skills install more-agent-orchestrator
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 more-agent-orchestrator

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

more-agent-orchestrator 用于查找、检索和筛选相关信息,支持多代理任务分解与协调。适用于复杂工作流拆解为子任务并由不同 Agent 并行处理。自动创建子代理、分配职责并聚合最终结果。

安装命令:openclaw skills install more-agent-orchestrator;需确认权限与维护状态。注意协调开销可能增加延迟,建议合理设置超时与重试策略。

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 OpenClaw;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 openclaw skills install more-agent-orchestrator;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

more-agent-orchestrator 怎么安装?

在终端执行 openclaw skills install more-agent-orchestrator。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

more-agent-orchestrator 支持哪些 AI 工具?

公开资料标注支持 OpenClaw。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

more-agent-orchestrator 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 openclaw skills install more-agent-orchestrator 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。

more-agent-orchestrator 是免费的吗?

来源标注的许可证是 MIT-0。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

more-agent-orchestrator 用的人多吗?

公开数据是累计安装 9,302 次,近一周安装 380 次,下载 2,979 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

more-agent-orchestrator 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 专注 OpenClaw 一种宿主,触发方式和使用习惯不用来回切换。
  • 许可证明确为 MIT-0,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 OpenClaw,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
more-agent-orchestrator

更多 Agent 协调器 · 本页

9,302—执行命令MIT-0通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

name
agent-orchestrator
version
1.0.0
description
Multi-agent collaboration and task orchestration. Decompose complex tasks, spawn sub-agents, coordinate execution, and synthesize results.
author
lcp14262
license
MIT-0
repository
https://github.com/lcp14262/agent-orchestrator

Agent Orchestrator 🐙

Multi-agent collaboration and task orchestration for OpenClaw.

When a single agent isn't enough — orchestrate a team.

What It Does

Task Decomposition:

  • Analyzes complex tasks
  • Breaks them into independent sub-tasks
  • Identifies dependencies and parallelization opportunities

Agent Coordination:

  • Spawns sub-agents with specific instructions
  • Manages concurrent execution
  • Handles inter-agent communication
  • Monitors progress and health

Result Synthesis:

  • Collects results from all sub-agents
  • Resolves conflicts and inconsistencies
  • Synthesizes final deliverable
  • Provides execution summary

When to Use

Trigger Phrases:

  • "Break this down and have multiple agents work on it"
  • "Coordinate several agents to..."
  • "Parallelize this task"
  • "Have agents collaborate on..."
  • "Orchestrate a team to..."
  • "Decompose and distribute..."

Use Cases:

  1. Research Projects - Different agents research different aspects
  2. Code Reviews - Multiple agents review different files/modules
  3. Data Analysis - Parallel analysis of different datasets
  4. Content Creation - Agents write different sections, then synthesize
  5. Testing - Parallel test execution across scenarios
  6. Complex Workflows - Multi-step processes with dependencies

Quick Start

Basic Usage

Orchestrate this: Research the top 5 AI frameworks and compare their features, performance, and community support.

The orchestrator will:

  1. Decompose into sub-tasks (one per framework)
  2. Spawn 5 sub-agents
  3. Each agent researches one framework
  4. Synthesize comparison report

Advanced Usage

Orchestrate with options:
- Task: Analyze our Q4 sales data
- Agents: 4 (by region: North/South/East/West)
- Parallel: true
- Synthesis: consolidated_report

Architecture

┌─────────────────┐
│   Orchestrator  │
│     (Main)      │
└────────┬────────┘
         │
    ┌────┴────┬────────────┐
    │         │            │
┌───▼───┐ ┌──▼────┐  ┌────▼────┐
│Agent 1│ │Agent 2│  │Agent 3  │
│ Task A│ │ Task B│  │ Task C  │
└───┬───┘ └───┬───┘  └────┬────┘
    │         │            │
    └─────────┴────────────┘
              │
         ┌────▼────┐
         │Synthesis│
         │ Result  │
         └─────────┘

Configuration

Task Decomposition Strategy

StrategyDescriptionBest For
parallelAll sub-tasks run concurrentlyIndependent tasks
sequentialTasks run one after anotherDependent tasks
hybridMix of parallel and sequentialComplex workflows

Agent Allocation

ModeDescriptionUse Case
autoOrchestrator decides agent countGeneral purpose
fixedSpecific number of agentsResource-constrained
per_taskOne agent per sub-taskMaximum parallelization

Synthesis Options

OptionDescription
mergeCombine all results as-is
summarizeGenerate executive summary
compareHighlight differences and similarities
consolidateMerge with conflict resolution

Examples

Example 1: Market Research

Task: Research the competitive landscape for project management software

Decomposition:
- Agent 1: Analyze Asana features and pricing
- Agent 2: Analyze Monday.com features and pricing
- Agent 3: Analyze Notion features and pricing
- Agent 4: Analyze ClickUp features and pricing
- Agent 5: Analyze emerging competitors

Synthesis: Comparative analysis report with recommendations

Example 2: Code Review

Task: Review the entire codebase for security vulnerabilities

Decomposition:
- Agent 1: Review authentication module
- Agent 2: Review API endpoints
- Agent 3: Review database queries
- Agent 4: Review file handling
- Agent 5: Review third-party dependencies

Synthesis: Security audit report with prioritized fixes

Example 3: Content Creation

Task: Write a comprehensive guide to OpenClaw skills

Decomposition:
- Agent 1: Introduction and setup
- Agent 2: Basic skill structure
- Agent 3: Advanced patterns
- Agent 4: Best practices
- Agent 5: Troubleshooting

Synthesis: Complete guide with consistent voice and formatting

Implementation Details

Task Decomposition Algorithm

  1. Analyze the main task for scope and complexity
  2. Identify natural breakpoints and independent components
  3. Estimate effort for each component
  4. Group related components into sub-tasks
  5. Determine dependencies between sub-tasks
  6. Output structured task list with metadata

Sub-Agent Spawning

{
  "runtime": "subagent",
  "mode": "run",
  "task": "<specific sub-task>",
  "timeoutSeconds": 300,
  "streamTo": "parent"
}

Progress Tracking

  • Track each sub-agent's status: pending → running → completed/failed
  • Monitor execution time
  • Handle timeouts and retries
  • Report progress to main session

Conflict Resolution

When sub-agents produce conflicting results:

  1. Flag the conflict
  2. Request clarification from each agent
  3. Escalate to human if unresolved
  4. Document the resolution

Error Handling

Sub-Agent Failures

ErrorHandling
TimeoutRetry once with extended timeout
CrashSpawn replacement agent
Invalid outputRequest clarification
Resource exhaustedQueue and retry later

Synthesis Failures

ErrorHandling
Missing resultsProceed with available data, flag gaps
Conflicting dataFlag for human review
Format mismatchNormalize before merging

Best Practices

Do's

✅ Clear task boundaries - Each sub-task should be self-contained ✅ Explicit success criteria - Define what "done" looks like ✅ Reasonable timeouts - Account for complexity ✅ Progressive synthesis - Synthesize as results arrive ✅ Human escalation - Know when to involve the user

Don'ts

❌ Over-parallelize - Too many agents creates coordination overhead ❌ Vague instructions - Sub-agents need clear, specific tasks ❌ Ignore dependencies - Sequential tasks must respect order ❌ Blind synthesis - Review before merging conflicting results ❌ No fallback - Always have a plan B for failures

Limitations

  • Context limits - Each sub-agent has independent context
  • Coordination overhead - More agents = more management
  • Cost - Multiple agents = higher token usage
  • Complexity - Debugging multi-agent flows is harder

Troubleshooting

Problem: Sub-agents produce inconsistent results

Solution:

  1. Standardize the output format in task instructions
  2. Add validation step before synthesis
  3. Use compare synthesis mode to highlight differences

Problem: Task takes too long

Solution:

  1. Increase parallelization
  2. Reduce scope per agent
  3. Set aggressive timeouts with retries

Problem: Results are too fragmented

Solution:

  1. Use consolidate synthesis mode
  2. Add explicit integration step
  3. Assign one agent to "editor" role

API Reference

Orchestrate Command

orchestrate <task> [options]

Options:
  --agents <n>        Number of sub-agents (default: auto)
  --mode <mode>       Execution mode: parallel|sequential|hybrid
  --timeout <sec>     Timeout per sub-agent (default: 300)
  --synthesis <type>  Synthesis type: merge|summarize|compare|consolidate
  --verbose           Show detailed progress

Status Command

orchestrate status <session_id>

Shows current orchestration session status

Changelog

v1.0.0 (2026-03-12)

  • Initial release
  • Task decomposition
  • Sub-agent spawning and coordination
  • Result synthesis
  • Progress tracking
  • Error handling

License

MIT


*Part of the multi-agent toolkit for OpenClaw*

*"Alone we can do so little; together we can do so much."*

平台分布

OpenClaw

93.32%
按下载量换算2,780

安全审计

VirusTotal

通过

ClawScan

通过

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 more-agent-orchestrator 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。目前只有一个公开来源,建议同时核对源仓库。

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