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Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any CLI-based coding agent) for maximum throughput on implementation tasks. Use wh...

通信与消息

许可证:MIT-0

MIT-0 ·免费使用、修改和重新分发。无需归因。

版本:v1.0.0

统计:⭐ 1 · 216 · 0 current installs · 0 all-time installs

1

安装量(当前) 0

🛡 VirusTotal :可疑 · OpenClaw :良性

Package:aicodelion/agent-conductor

安全扫描(ClawHub)

  • VirusTotal :可疑
  • OpenClaw :良性

OpenClaw 评估

The skill is an instruction-only orchestrator that is internally consistent with its stated purpose (delegating code-execution tasks to CLI/agent tools) and does not request extra credentials or installs; however it gives broad runtime authority to run agent CLI commands and interact with the filesystem, so use caution when enabling it in a privileged/autonomous environment.

目的

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.

说明范围

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 t…

安装机制

No install spec and no code files beyond documentation — lowest-risk delivery model. Nothing is downloaded or written by the skill itself.

证书

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.

持久

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.

综合结论

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-ag…

安装(复制给龙虾 AI)

将下方整段复制到龙虾中文库对话中,由龙虾按 SKILL.md 完成安装。

请把本段交给龙虾中文库(龙虾 AI)执行:为本机安装 OpenClaw 技能「Agent Conductor」。简介:Orchestrate coding sub-agents (Claude Code, Codex, Cursor, Gemini Code, or any …。
请 fetch 以下地址读取 SKILL.md 并按文档完成安装:https://raw.githubusercontent.com/openclaw/skills/refs/heads/main/skills/aicodelion/agent-conductor/SKILL.md
(来源:yingzhi8.cn 技能库)

SKILL.md

打开原始 SKILL.md(GitHub raw)

---
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:

| Agent | Invoke Command |
|-------|---------------|
| Claude Code | `claude '<task>'` |
| OpenAI Codex | `codex '<task>'` |
| Cursor Agent | `cursor-agent '<task>'` |
| Gemini Code | `gemini-code '<task>'` |
| Any other | `your-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

| Duration | Mechanism |
|----------|-----------|
| < 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        (< 2 min)
Stage 2: Process       →  results.json           (needs Stage 1)
Stage 3: Report        →  report.md              (needs Stage 2)
```

See [references/patterns.md](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