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more-agent-orchestrator更多 Agent 协调器

Agent Skill

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。

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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: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

简介

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。

SKILL.md

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: pendingrunningcompleted/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."*

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。

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安装前确认

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