Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add Leodorareluctant259/superpowers-zh --skill dispatching-parallel-agentsgit clone --depth 1 https://github.com/Leodorareluctant259/superpowers-zhWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/leodorareluctant259/superpowers-zh/dispatching-parallel-agents)<a href="https://agentmods.dev/skills/leodorareluctant259/superpowers-zh/dispatching-parallel-agents"><img src="https://agentmods.dev/badge/skills/leodorareluctant259/superpowers-zh/dispatching-parallel-agents.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00030 | $0.01862 |
| Opus 5 | $0.00015 | $0.00931 |
| Sonnet 5 | $0.00006 | $0.00372 |
| Haiku 4.5 | $0.00003 | $0.00186 |
Grade A, and why
dispatching-parallel-agents scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to dispatching-parallel-agents — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 183 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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
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
// 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:
- 聚焦的 - 一个清晰的问题域
- 自包含的 - 包含理解问题所需的所有上下文
- 明确输出要求 - 智能体应该返回什么?
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
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 183 lines · 30 tokens per session scan A a936ae1d0eb1
dispatching-parallel-agents is a skill published in the GitHub repository Leodorareluctant259/superpowers-zh (5 stars, last pushed 2d ago), licensed MIT. It adds 30 tokens to every session and 1,862 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to dispatching-parallel-agents, differing in 0 lines, and is treated as a copy.
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