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Agent Conductor

作者 AICodeLion · GitHub ↗ · v1.0.0
cross-platform ⚠ suspicious
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在 OpenClaw 中安装
/install agent-conductor
功能描述
Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any CLI-based coding agent) for maximum throughput on implementation tasks. Use wh...
使用说明 (SKILL.md)

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:

Agent Invoke Command
Claude Code claude '\x3Ctask>'
OpenAI Codex codex '\x3Ctask>'
Cursor Agent cursor-agent '\x3Ctask>'
Gemini Code gemini-code '\x3Ctask>'
Any other your-agent-cmd '\x3Ctask>'

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

Duration Mechanism
\x3C 5 min Foreground: exec pty:true command:"AGENT_CMD '...'"
5–30 min Background: exec pty:true background:true timeout:1800 command:"AGENT_CMD '...'"
> 30 min Agent 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        (\x3C 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

Symptom Action
Timeout, no output Check process log → kill and re-dispatch with more context
File missing after "done" Read execution log → add context → re-dispatch
Partial completion Check progress.json → resume from checkpoint
Fails twice in a row Stop 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
安全使用建议
This skill is instruction-only and coherent for orchestrating CLI-based coding agents. Before installing: (1) Restrict which AGENT_CMD values the agent may invoke (use a controlled wrapper or allow-list) so the orchestrator cannot execute arbitrary system commands; (2) Run the skill in a sandbox or project-specific environment (not with root or system-wide access), since it routinely reads/writes files and runs processes; (3) Ensure any sub-agents you dispatch to are trusted and that their CLI tooling is configured with only the necessary credentials; (4) Review and supply safe completion/notification commands and avoid allowing the orchestrator to accept open-ended prompts that could trigger external network calls. These mitigations reduce the risk introduced by giving an orchestrator the ability to run arbitrary agent CLI commands and modify files.
功能分析
Type: OpenClaw Skill Name: agent-conductor Version: 1.0.0 The skill bundle is classified as suspicious due to its core functionality involving the execution of arbitrary commands via `exec command:"AGENT_CMD '...'"` as described in `SKILL.md`. While this capability is central to its stated purpose of orchestrating coding sub-agents, it represents a significant security risk if the `AGENT_CMD` placeholder is configured with malicious commands or if the orchestrating agent is compromised. There is no direct evidence of intentional malicious behavior, data exfiltration, or prompt injection designed to subvert the OpenClaw agent within the provided files; rather, the risk lies in the powerful primitive it exposes.
能力评估
Purpose & Capability
Name and description match the contents: the SKILL.md describes orchestrating coding sub-agents, task decomposition, parallel coordination, and verification. There are no unexpected required binaries, env vars, or config paths declared — consistent with an instruction-only orchestrator.
Instruction Scope
The instructions explicitly tell the orchestrator to dispatch CLI commands (AGENT_CMD), run background/foreground processes, read logs and progress files, and verify output files. All of these are directly relevant to orchestration. However the instructions grant broad discretion to execute arbitrary agent commands and scripts (including reading and writing arbitrary project files and running long-lived background processes), which increases the operational risk depending on what the agent is allowed to run.
Install Mechanism
No install spec and no code files beyond documentation — lowest-risk delivery model. Nothing is downloaded or written by the skill itself.
Credentials
The skill declares no required environment variables or credentials. The dispatch template mentions that tasks may include project-specific env vars (proxy, auth), which is reasonable — those would be provided per-dispatch and are not requested by the skill itself.
Persistence & Privilege
Flags show always:false and default autonomous invocation behavior. The skill does not request persistent privileges, nor does it modify other skills or system-wide settings in its instructions.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install agent-conductor
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /agent-conductor 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
agent-conductor 1.0.0 changelog - Initial release of agent-conductor skill. - Provides orchestration templates and guidelines for dispatching code, script, and data processing tasks to coding sub-agents. - Introduces agent-agnostic dispatch patterns for Claude Code, Codex, Cursor, Gemini Code, and any CLI-based agent. - Outlines best practices for task decomposition, parallel execution, and acceptance validation. - Defines clear criteria for when to delegate work versus handling within the orchestrator session.
元数据
Slug agent-conductor
版本 1.0.0
许可证
累计安装 1
当前安装数 1
历史版本数 1
常见问题

Agent Conductor 是什么?

Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any CLI-based coding agent) for maximum throughput on implementation tasks. Use wh... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 418 次。

如何安装 Agent Conductor?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install agent-conductor」即可一键安装,无需额外配置。

Agent Conductor 是免费的吗?

是的,Agent Conductor 完全免费(开源免费),可自由下载、安装和使用。

Agent Conductor 支持哪些平台?

Agent Conductor 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Agent Conductor?

由 AICodeLion(@aicodelion)开发并维护,当前版本 v1.0.0。

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