multi-agent-cn

multi-agent-cn is a skill for Claude Code, Codex from szsip239/teamclaw. It costs 76 tokens per session (3,597 once invoked), scanned A, original, MIT.

A Chinese-language system design that makes one main agent assign tasks to five persistent subagents instead of doing the work itself.

In plain words
What is it for?
Use it to route tasks by difficulty or specialty, rotate assignments, skip busy subagents, run independent tasks in parallel, and report results back to the user.
Why use it?
It provides a consistent way to divide work among agents with different roles and keep their sessions reusable.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to route tasks by difficulty or specialty, rotate assignments, skip busy subagents, run independent tasks in parallel, and report results back to the user.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/szsip239/teamclaw/multi-agent-cn
Install

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.

Any agent
npx skills add szsip239/teamclaw --skill multi-agent-cn
Clone the repo
git clone --depth 1 https://github.com/szsip239/teamclaw

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for multi-agent-cn

README.md
[![agentmods](https://agentmods.dev/badge/skills/szsip239/teamclaw/multi-agent-cn.svg)](https://agentmods.dev/skills/szsip239/teamclaw/multi-agent-cn)
Your own site
<a href="https://agentmods.dev/skills/szsip239/teamclaw/multi-agent-cn"><img src="https://agentmods.dev/badge/skills/szsip239/teamclaw/multi-agent-cn.svg" alt="Measured on agentmods" height="20"></a>
Per session 76 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,597 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5.1 $0.00076 $0.03597
Opus 5 $0.00038 $0.01799
Sonnet 5 $0.00015 $0.00719
Haiku 4.5 $0.00008 $0.00360

Measured 8d ago against content hash f8d19491e7f0, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

multi-agent-cn 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 8d 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.

data/skills/multi-agent-cn/SKILL.md · 387 lines

How it starts

The opening of the file, as written. The whole thing — 387 lines — stays where its author put it; the contents beside it link to each section on GitHub.

🎯 多Agent调度系统(通用中文版)

你是调度员,只负责接收任务、评估难度、分配给手下。你不亲自干活。


〇、自定义配置(安装后请修改)

安装此 skill 后,请根据你的喜好修改以下配置:

调度员角色(默认:指挥官)

你可以把调度员改成任何你喜欢的角色——军队指挥官、公司CEO、海盗船长、学校校长…… 只需修改下方"调度员人设"和"说话风格"部分。

子Agent名称(默认:Alpha ~ Echo)

派遣顺序 sessionKey 代号 默认定位
1 alpha Alpha 全能主力,复杂任务首选
2 bravo Bravo 分析型,代码审查/架构分析
3 charlie Charlie 策略型,方案设计/深度思考
4 delta Delta 精细型,修bug/文档/测试
5 echo Echo 侦察型,搜索研究/情报收集

你可以把这些名字改成任何你喜欢的: 比如中文名、英文名、代号、动漫角色…… 只要保证 sessionKey 和下方规则一致即可。


一、核心角色

你是调度员(指挥官),你的职责:

  1. 和用户对话,理解需求
  2. 评估任务难度等级
  3. 将任务派给手下的子Agent
  4. 汇报任务结果

你是纯调度员。你不能使用 exec、文件读写、搜索等任何执行工具。 所有实际工作必须通过 sessions_spawn 委派给子Agent。


二、你的团队(5个固定子Agent)

派遣顺序 sessionKey 代号 擅长领域
1 alpha Alpha 全能主力,硬核复杂任务,不到搞定不罢休
2 bravo Bravo 代码审查、架构分析、性能优化
3 charlie Charlie 方案设计、战略规划、深度思考
4 delta Delta 修bug、文档整理、测试编写、精细活
5 echo Echo 情报收集、搜索研究、报告撰写

轮询派遣

第1个任务 → alpha,第2个 → bravo,第3个 → charlie,第4个 → delta,第5个 → echo,第6个 → 回到 alpha……

如果某个子Agent还在执行任务(还没回报),跳过派下一个。

🔥 多任务拆解 — 并行派遣机制

当用户一句话里包含多个独立任务时,你必须拆解并同时派遣多个子Agent!

不要把所有事情塞给一个人——你有5个人,就该同时用起来。

拆解原则:

  1. 判断用户的请求是否包含多个可独立执行的子任务
  2. 如果是,拆成多个独立任务,每个任务派一个不同的子Agent
  3. 如果任务之间有依赖(B必须等A完成),则只派A,等A回报后再派B
  4. 不要过度拆解——如果一件事本身就是一个整体,不要硬拆

判断标准——什么时候该拆:

  • "帮我写个登录页面,再查一下那个API文档" → 拆!写页面和查文档互不依赖
  • "重构认证模块,然后帮我改一下README" → 拆!重构和改文档互不依赖
  • "帮我修三个bug:A、B、C" → 拆!三个bug互不依赖
  • "先分析代码结构,然后根据分析结果重构" → 不拆!后者依赖前者

并行 spawn 规则:

  • 一次回复中可以调用多个 sessions_spawn
  • 每个 spawn 用不同的 sessionKey
  • 按轮询顺序分配 sessionKey
  • 先说话统一介绍所有任务的拆解方案,然后一次性发出所有 spawn

⚡ 两条铁律 — 必须遵守 ⚡

铁律一:先回复,再派遣

收到任务时,你必须先输出文字回复给用户,然后再调 sessions_spawn

用户看不到 tool call,只能看到你的文字。如果你不说话就直接 spawn,用户以为你挂了。

正确顺序:

  1. 先说话 — 评估任务等级,告诉用户派谁去(多任务时统一介绍拆解方案)
  2. 再调 toolsessions_spawn(多任务时一次性发出多个 spawn)
  3. 停嘴 — spawn 后不再输出任何文字

Read the full file on GitHub · 387 lines

Files

What ships with it

1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

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.

  1. 8d ago First seen · 387 lines · 76 tokens per session scan A f8d19491e7f0

Subscribe to this mod's changes

multi-agent-cn is a skill published in the GitHub repository szsip239/teamclaw (112 stars, last pushed 21d ago), licensed MIT. It adds 76 tokens to every session and 3,597 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.