Agent skill

Dispatching Parallel Agents

by jnMetaCode in jnMetaCode/superpowers-zh

“当面对 2 个以上可以独立进行、无共享状态或顺序依赖的任务时使用”

— description from SKILL.md by jnMetaCode
MITAuto-check passedAgent Workflows

Install Dispatching Parallel Agents

skills CLI
$ npx skills add jnMetaCode/superpowers-zh --skill dispatching-parallel-agents -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install jnMetaCode/superpowers-zh dispatching-parallel-agents --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/jnMetaCode/superpowers-zh.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dispatching-parallel-agents .claude/skills/dispatching-parallel-agents && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
dispatching-parallel-agents
GitHub stars
8.3k
Token cost
~778 tokens
SKILL.md length
138 words
Files
1
Skills in repo
21
Repo updated
First seen
Licence
MIT

At a glance

  • Works in 4 steps: 识别独立的问题域 → 创建聚焦的智能体任务 → 并行分派 → …
  • SKILL.md covers 概述, 何时使用, 模式 and 智能体提示词结构, plus 4 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

About this skill

Dispatching Parallel Agents is a skill in jnMetaCode/superpowers-zh (8.3k stars). Its SKILL.md is about 778 tokens. Licence: MIT.

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. 识别独立的问题域
  2. 创建聚焦的智能体任务
  3. 并行分派
  4. 审查与集成

What it can do on your machine

Read from SKILL.md and the folder at commit fe34019. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are dot, typescript and markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Dispatching Parallel Agents loads about 778 tokens when it runs. Until then it costs about 15 tokens; SKILL.md has 138 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~15
When it runs · the whole SKILL.md, loaded when a task matches
~778

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from jnMetaCode/superpowers-zh at commit fe34019, republished under its MIT licence (© jnMetaCode). 138 words, ~778 tokens.

Download SKILL.mdSave it as .claude/skills/dispatching-parallel-agents/SKILL.md (or your agent's skills folder).
name
dispatching-parallel-agents
description
当面对 2 个以上可以独立进行、无共享状态或顺序依赖的任务时使用
version
1.0.0
license
MIT

并行分派智能体

概述

你将任务委派给具有隔离上下文的专用智能体。通过精心设计它们的指令和上下文,确保它们专注并成功完成任务。它们不应继承你的会话上下文或历史记录——你要精确构造它们所需的一切。这样也能为你自己保留用于协调工作的上下文。

当你遇到多个不相关的失败(不同的测试文件、不同的子系统、不同的 bug),逐一排查会浪费时间。每个排查都是独立的,可以并行进行。

核心原则: 每个独立问题域分派一个智能体,让它们并发工作。

何时使用

dot
digraph when_to_use {
    "存在多个失败?" [shape=diamond];
    "它们是否独立?" [shape=diamond];
    "单个智能体排查所有问题" [shape=box];
    "每个问题域一个智能体" [shape=box];
    "能否并行工作?" [shape=diamond];
    "顺序执行智能体" [shape=box];
    "并行分派" [shape=box];

    "存在多个失败?" -> "它们是否独立?" [label="是"];
    "它们是否独立?" -> "单个智能体排查所有问题" [label="否 - 有关联"];
    "它们是否独立?" -> "能否并行工作?" [label="是"];
    "能否并行工作?" -> "并行分派" [label="是"];
    "能否并行工作?" -> "顺序执行智能体" [label="否 - 有共享状态"];
}

适用场景:

  • 3 个以上测试文件因不同根因失败
  • 多个子系统独立出现故障
  • 每个问题无需其他问题的上下文即可理解
  • 排查之间无共享状态

不适用场景:

  • 失败是相关的(修复一个可能修复其他的)
  • 需要理解完整的系统状态
  • 智能体之间会互相干扰

模式

1. 识别独立的问题域

按故障分组:

  • 文件 A 测试:工具审批流程
  • 文件 B 测试:批量完成行为
  • 文件 C 测试:中止功能

每个问题域是独立的——修复工具审批不会影响中止测试。

2. 创建聚焦的智能体任务

每个智能体获得:

  • 明确范围: 一个测试文件或子系统
  • 清晰目标: 让这些测试通过
  • 约束条件: 不修改其他代码
  • 预期输出: 你发现和修复内容的总结
3. 并行分派
typescript
// 在 Claude Code / AI 环境中
Task("修复 agent-tool-abort.test.ts 的失败")
Task("修复 batch-completion-behavior.test.ts 的失败")
Task("修复 tool-approval-race-conditions.test.ts 的失败")
// 三个任务并发运行
4. 审查与集成

当智能体返回时:

  • 阅读每个总结
  • 验证修复之间没有冲突
  • 运行完整测试套件
  • 集成所有更改

智能体提示词结构

好的智能体提示词应该是:

  1. 聚焦的 - 一个清晰的问题域
  2. 自包含的 - 包含理解问题所需的所有上下文
  3. 明确输出要求 - 智能体应该返回什么?
markdown
修复 src/agents/agent-tool-abort.test.ts 中 3 个失败的测试:

1. "should abort tool with partial output capture" - 期望消息中包含 'interrupted at'
2. "should handle mixed completed and aborted tools" - 快速工具被中止而非完成
3. "should properly track pendingToolCount" - 期望 3 个结果但得到 0 个

这些是时序/竞态条件问题。你的任务:

1. 阅读测试文件,理解每个测试验证的内容
2. 找到根因——是时序问题还是实际 bug?
3. 修复方式:
   - 用基于事件的等待替换任意超时
   - 如果发现中止实现中的 bug 则修复
   - 如果测试的是已变更的行为则调整测试期望

不要只是增加超时时间——找到真正的问题。

返回:你发现了什么以及修复了什么的总结。

常见错误

错误做法:太宽泛: "修复所有测试" - 智能体会迷失方向 正确做法:具体明确: "修复 agent-tool-abort.test.ts" - 聚焦的范围

错误做法:无上下文: "修复竞态条件" - 智能体不知道在哪里 正确做法:提供上下文: 粘贴错误信息和测试名称

错误做法:无约束: 智能体可能会重构所有代码 正确做法:设置约束: "不要修改生产代码" 或 "只修复测试"

错误做法:模糊的输出要求: "修好它" - 你不知道改了什么 正确做法:明确要求: "返回根因和修改内容的总结"

不适用的场景

关联性失败: 修复一个可能修复其他的——先一起排查 需要完整上下文: 理解问题需要看到整个系统 探索性调试: 你还不知道什么坏了 共享状态: 智能体会互相干扰(编辑同一文件、使用同一资源)

实际案例

场景: 大规模重构后,3 个文件中出现 6 个测试失败

失败情况:

  • agent-tool-abort.test.ts:3 个失败(时序问题)
  • batch-completion-behavior.test.ts:2 个失败(工具未执行)
  • tool-approval-race-conditions.test.ts:1 个失败(执行计数 = 0)

决策: 独立的问题域——中止逻辑、批量完成、竞态条件各自独立

分派:

智能体 1 → 修复 agent-tool-abort.test.ts
智能体 2 → 修复 batch-completion-behavior.test.ts
智能体 3 → 修复 tool-approval-race-conditions.test.ts

结果:

  • 智能体 1:用基于事件的等待替换了超时
  • 智能体 2:修复了事件结构 bug(threadId 位置不对)
  • 智能体 3:添加了等待异步工具执行完成的逻辑

集成: 所有修复互相独立,无冲突,完整测试套件全部通过

验证

智能体返回后:

  1. 审查每个总结 - 理解改了什么
  2. 检查冲突 - 智能体是否编辑了同一段代码?
  3. 运行完整套件 - 验证所有修复协同工作
  4. 抽查 - 智能体可能犯系统性错误

© jnMetaCode, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/dispatching-parallel-agents of jnMetaCode/superpowers-zh.

Open the folder on GitHubat commit fe34019

Compare with similar skills

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Categories

Questions about Dispatching Parallel Agents

How do I install Dispatching Parallel Agents in Claude Code?

Run `npx skills add jnMetaCode/superpowers-zh --skill dispatching-parallel-agents -a claude-code`. Or copy the skill folder (skills/dispatching-parallel-agents in jnMetaCode/superpowers-zh) into .claude/skills/dispatching-parallel-agents in your project. Claude Code loads it when a task matches its description.

How do I install Dispatching Parallel Agents in Codex?

Run `npx skills add jnMetaCode/superpowers-zh --skill dispatching-parallel-agents -a codex`. Or copy the skill folder (skills/dispatching-parallel-agents in jnMetaCode/superpowers-zh) into .agents/skills/dispatching-parallel-agents in your project. Codex loads it when a task matches its description.

Can I use Dispatching Parallel Agents in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add jnMetaCode/superpowers-zh --skill dispatching-parallel-agents -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dispatching-parallel-agents, .gemini/skills/dispatching-parallel-agents, .github/skills/dispatching-parallel-agents and .opencode/skills/dispatching-parallel-agents in your project.

What does Dispatching Parallel Agents need to run?

SKILL.md names no scripts, command-line tools or credentials: Dispatching Parallel Agents is instructions for the agent only.

Does Dispatching Parallel Agents access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Dispatching Parallel Agents safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Dispatching Parallel Agents use?

Dispatching Parallel Agents is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Dispatching Parallel Agents use?

About 778 tokens (SKILL.md is roughly 3.1k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Dispatching Parallel Agents?

Skills that share tags, products or a category with Dispatching Parallel Agents: Claude Code Agent Development (anthropics/claude-plugins-official, 37k stars), Subagent Driven Development (Asvarox/allkaraoke, 261 stars), Dispatching Parallel Agents (ultralisp/ultralisp, 258 stars) and Paseo Advisor Second Opinion (getpaseo/paseo, 20k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dispatching Parallel Agents?

jnMetaCode (a GitHub user) maintains it in jnMetaCode/superpowers-zh, which has 8,265 GitHub stars. The repository holds 21 skills in this directory. The repository was last updated on October 4, 2026.

Source: jnMetaCode/superpowers-zh on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.