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Agent Skill · 效率

multi-agent-analysis-execution(多智能体分析执行)

multi-agent-analysis-execution 用于补充效率相关能力,适合在 OpenClaw 中需要让 Agent 承接效率相关任务时使用。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。

multi-agent-analysis-execution 是效率类 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,按安装量在效率类的 21,003 个 Skill 里排第 14,516。

总安装 3,369周安装 139GitHub Stars 公开资料未说明下载 1,101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
1.0.4

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:multi-agent-analysis-execution(多智能体分析执行)
来源仓库:https://github.com/rubencoppensongit/multi-agent-analysis-execution
安装命令:
openclaw skills install multi-agent-analysis-execution
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 multi-agent-analysis-execution

这个 Skill 是做什么的

效率类 Skill 把重复的整理、汇总、转换工作交给助手完成,减少手工复制粘贴。

该技能通过协调器规划、执行治理和自动输出管理,实现复杂多代理工作流的编排与自动化。适用于需要高效协同多个 Agent 完成任务分解、并行处理及结果整合的场景。每次运行都会生成结构化输出,便于追踪进度与验证结果,提升整体执行效率。

安装命令为 openclaw skills install multi-agent-analysis-execution,建议在受控环境中测试后再投入生产。使用前需明确各代理角色与权限边界,避免因资源竞争或通信冲突导致任务失败。

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 multi-agent-analysis-execution;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

multi-agent-analysis-execution 怎么安装?

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

multi-agent-analysis-execution 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。

multi-agent-analysis-execution 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 multi-agent-analysis-execution 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。

multi-agent-analysis-execution 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。

multi-agent-analysis-execution 用的人多吗?

公开数据是累计安装 3,369 次,近一周安装 139 次,下载 1,101 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。

multi-agent-analysis-execution 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。
  • 需要处理效率类任务、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。

效率类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
github

GitHub 代码协作 · OpenClaw

7,632,918545需要联网MIT-0通过
nano-pdf

Nano PDF 文档 · OpenClaw

4,249,476231需要联网MIT-0通过
auto-updater

自动更新程序 · OpenClaw

2,964,063386操作浏览器MIT-0通过
video-frames

视频帧 · OpenClaw

2,621,304112需要联网MIT-0通过
gemini

Gemini 助手 · OpenClaw

2,547,39648需要联网MIT-0有提醒
multi-agent-analysis-execution

多智能体分析执行 · 本页

3,369—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
multi agent analysis and execution
description
Orchestrate complex multi-agent workflows with explicit coordinator planning, execution governance, and *automatic output management*. Each skill run creates its own isolated output namespace to prevent file accumulation and confusion from repeated executions.
version
1.0.0

multi_agent_coordinator - SKILL.md (Lean + Debug Mode)

Description

Orchestrate complex multi-agent workflows with an explicit coordinator-driven process that plans, sequences, and governs execution across multiple agents.

This version keeps the system lean by default while preserving the full coordination logic, guardrails, and execution discipline required for reliable multi-agent workflows.

Critical Rule: When this skill is invoked, the coordinator process MUST execute fully across all phases. No phases may be skipped or partially executed.


Core Principles

  1. Lean by default — minimal files, fast execution
  2. Debug on demand — full traceability when needed
  3. Run isolation always — every run gets its own directory

Run Directory (Always Created)

Each execution creates a unique directory:

Coordinator_runs/
└── run_YYYYMMDD_HHMMSS/
  • No absolute paths
  • Prevents collisions
  • Keeps runs isolated

Modes

mode = lean (default) | debug

Lean Mode (default)

  • Minimal output
  • No intermediate files

Debug Mode

  • Full artifact generation
  • Complete traceability

The Five-Phase Coordinator Process

MANDATORY EXECUTION CONTRACT

  • You MUST start at PHASE 0
  • You MUST execute phases sequentially (0 → 4)
  • You MUST NOT skip phases
  • You MUST NOT perform ad-hoc reasoning outside the coordinator structure
  • You MUST follow the planned execution (no improvisation during execution)

PHASE 0: COORDINATOR PLANNING

This phase defines the core intelligence of the skill and MUST be executed carefully.

Mandatory Planning Steps

  1. Task Plan Creation

- Analyze the problem - Answer: *"What steps are required to solve this?"* - Decompose into clear, atomic tasks - Limit the number of tasks to 15 for any given problem.

  1. Dependency Analysis

- Answer: *"What depends on what?"* - Identify ordering constraints - Identify parallelizable tasks

  1. Execution Group Formation

- Group independent tasks - Define strict execution order between groups

  1. Agent Specification (CRITICAL GUARDRAIL)

For each task (max 15 ): - Define a single-purpose agent - Assign a clear responsibility - Define: - Inputs - Outputs - Constraints (read/write, safety, isolation) - Work and scanning only limited to the workspace unless explicit approval of user - Agent prompt - Each task MUST map to exactly one agent - No credentials, tokens etc should be passed or to be found in the generated prompt. - If the sub agent requires credentials they should be available via ENV or other tools.

  1. Coordinator Execution Strategy

The coordinator MUST: - Maintain full control of execution - Enforce group sequencing - Ensure all agents complete before proceeding - Handle failures explicitly (no silent failures)

Lean Mode

  • All planning done in memory

Debug Mode

Persist planning artifacts


PHASE 1: EXECUTION

This phase executes the previously defined plan with strict governance.

Execution Rules (MANDATORY)

For each execution group in order:

  1. Spawn all agents with the generated prompt of phase 0 in the group (parallel allowed)
  2. Ensure agents only operate within their defined scope
  3. Wait for ALL agents in the group to complete
  4. Verify successful completion of each agent
  5. ONLY THEN proceed to next group

Failure Handling (GUARDRAIL)

  • If an agent fails:

- Coordinator MUST detect it - MUST stop progression OR handle explicitly - MUST report failure in final output

Lean Mode

  • In-memory execution

Debug Mode

  • Persist prompts and outputs

PHASE 2: OUTPUT MANAGEMENT

Core Rule

All outputs MUST remain scoped to the current run directory.

Lean Mode

Only create:

runs/run_YYYYMMDD_HHMMSS/
└── REPORT.final

Optional:

└── run.log

Debug Mode

Full structure:

runs/run_YYYYMMDD_HHMMSS/
├── TASK_PLAN.md
├── DEPENDENCY_GRAPH.md
├── EXECUTION_GROUPS.md
├── AGENT_REQUIREMENTS.md
├── prompts/
├── outputs/
└── REPORT.final

PHASE 3: REPORTING

The coordinator MUST consolidate all results.

Requirements

  • Include results from ALL agents
  • Verify execution order was respected
  • Report any failures or inconsistencies

Output:

REPORT.final

PHASE 4: CLEANUP

Lean Mode

  • Minimal footprint
  • No additional cleanup required

Debug Mode

Optional retention policy:

keep_last = N

Guardrails Summary

  • MUST execute all phases sequentially
  • MUST NOT skip planning
  • MUST NOT bypass coordinator
  • MUST enforce task → agent mapping (1:1)
  • MUST enforce execution group sequencing
  • MUST detect and report failures
  • MUST isolate each run in its own directory

Summary

  • Lean by default, debug when needed
  • Full coordinator logic preserved
  • Strong execution guarantees via guardrails
  • Every run isolated

平台分布

OpenClaw

78.38%
按下载量换算863

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 multi-agent-analysis-execution 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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