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agent-conductorAgent 指挥

Agent Skill

agent-conductor 用于补充开发相关能力,适合在 OpenClaw 中需要让 Agent 承接开发相关任务时使用。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。

总安装

12,677

周安装

539

GitHub Stars

1

下载量

4,441
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:agent-conductor(Agent 指挥)
来源仓库:https://github.com/aicodelion/agent-conductor
安装命令:
openclaw skills install agent-conductor
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 agent-conductor

简介

agent-conductor 编排多个编码子代理以提升开发效率。

  • 适用于 OpenClaw 中并行处理大型代码项目的场景。
  • 支持 Claude Code、Cursor 等多种 CLI 工具接入。
  • 需配置各子代理的工作目录与通信密钥。
  • 注意任务分配均衡以避免资源争抢。agent-conductor 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

name
agent-conductor
description
Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any CLI-based coding agent) for maximum throughput on implementation tasks. Use when: (1) writing or modifying code files, (2) running scripts or data pipelines, (3) batch processing large datasets, (4) multi-stage workflows requiring parallel execution. Covers agent-agnostic dispatch templates, task decomposition, parallel coordination, and acceptance criteria. NOT for: simple file reads, config-only changes, or sending messages. Core principle — the orchestrator plans; the coding agents execute.

Agent Conductor 🎼

You conduct. Agents perform.

Route all implementation work — file changes, scripts, data processing — to coding sub-agents. The orchestrating session stays lean: it plans, decides, and validates. Agents do the execution.

Supported Agents

Agent-agnostic. Set your invoke command once:

AgentInvoke Command
Claude Codeclaude '<task>'
OpenAI Codexcodex '<task>'
Cursor Agentcursor-agent '<task>'
Gemini Codegemini-code '<task>'
Any otheryour-agent-cmd '<task>'

Use AGENT_CMD as a placeholder in the examples below.

When to Dispatch

Dispatch when the task involves any of:

  • Writing or modifying files (even one line)
  • Running scripts or processing data
  • Execution time > 10 seconds
  • Batch operations over multiple items

*If it produces file changes → dispatch it.*

Dispatch Template

## Task: [name]

### Requirement
[One sentence: what to produce and where]

### Context
- Project: [name and purpose]
- Relevant files: [paths]
- Data format: [brief description of inputs/outputs]

### Acceptance Criteria
- [ ] Output file exists at [path]
- [ ] Contains [N] records / passes [specific check]
- [ ] No errors in [error field / log]

### Gotchas
- [Known pitfall 1]
- [Known pitfall 2]

### Environment
- Language/runtime: [python3 / node / go / etc.]
- Working directory: [path]
- Special config: [proxy, auth, env vars if needed]

When done, notify with:
[your completion notification command]

Execution Mechanism

DurationMechanism
< 5 minForeground: exec pty:true command:"AGENT_CMD '...'"
5–30 minBackground: exec pty:true background:true timeout:1800 command:"AGENT_CMD '...'"
> 30 minAgent writes script → run in screen / tmux
Use pty:true if your platform requires it (needed for Claude Code; check other agents' docs).

Task Decomposition

Split large projects by stage, not by feature. Each stage must be independently verifiable.

Split when any of these apply:

  • Runtime > 30 minutes
  • More than one script needed
  • Batch > 100 items
  • Output of one step feeds the next
Stage 1: Prepare data  →  clean_data.csv        (< 2 min)
Stage 2: Process       →  results.json           (needs Stage 1)
Stage 3: Report        →  report.md              (needs Stage 2)

See references/patterns.md for parallel coordination, checkpoint/resume, and domain examples.

Acceptance Checklist

After any "done" signal, always verify:

  1. File exists — confirm output path
  2. Count correct — expected N vs. actual N records
  3. Non-empty — spot-check 2–3 outputs
  4. No silent errors — check error fields and null rates

*A completion signal ≠ acceptance. Run the checklist.*

Error Handling

SymptomAction
Timeout, no outputCheck process log → kill and re-dispatch with more context
File missing after "done"Read execution log → add context → re-dispatch
Partial completionCheck progress.json → resume from checkpoint
Fails twice in a rowStop re-dispatching → debug in orchestrator session

What NOT to Dispatch

  • Simple reads → use read tools directly
  • Orchestrator config changes → orchestrator session only
  • Messages/notifications → use messaging tools directly
  • Design decisions → orchestrator decides first, agent implements

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

77.25%
按下载量换算3,431

安全审计

VirusTotal

可疑

ClawScan

通过

Static analysis

未展示

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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

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