Weekly Stop Item

Q: What does the Weekly Stop Item AI skill do?

用于建立持续反馈机制和消除组织障碍。当用户在讨论团队效率、员工反馈、流程优化时激活。 不适用于：一次性重大决策、战略规划讨论、与外部合作伙伴的沟通。 关键 trigger：提到员工抱怨、流程冗余、执行障碍、团队卡点。

Community

ace3000chao

weekly-stop-item

用于建立持续反馈机制和消除组织障碍。当用户在讨论团队效率、员工反馈、流程优化时激活。不适用于：一次性重大决策、战略规划讨论、与外部合作伙伴的沟通。关键 trigger：提到员工抱怨、流程冗余、执行障碍、团队卡点。

Overview

Publisher	ace3000chao
Repository	`book2startup`
Skill name	`weekly-stop-item`
Stars	93
Forks	14
Bundled files	1
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
1 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by ace3000chao on GitHub. Read the source before you install it.

Installation

Install the Weekly Stop Item AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/weekly-stop-item
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/weekly-stop-item

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/ace3000chao/book2startup.git /tmp/book2startup
mkdir -p .claude/skills
cp -r /tmp/book2startup/ScalingUp-skills/weekly-stop-item .claude/skills/weekly-stop-item

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Weekly Stop Item in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Weekly Stop Item on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Weekly Stop Item is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Weekly Stop Item

R — 原文 (Reading)

"Each senior leader formally talks to one employee each week and asks, 'What should the company Start/Stop/Keep doing?' Pay particular attention to the 'stops.'"

— Verne Harnish, Scaling Up, 第1章

I — 方法论骨架 (Interpretation)

Scaling Up 将"每周识别一个Stop项"作为高层领导者最重要的反馈机制。不是年度survey，不是季度复盘，而是每周一次、一对一、强制性地从一线员工获取真实反馈。

Start/Stop/Keep 是个简单到任何人都能理解的框架，但"Stop"才是核心——人们通常知道什么不该做，但很少被邀请说出来。组织越大，信息在传递过程中失真越多，高层听到的往往是美化过的版本。

每周只选一个Stop项，强制优先级：组织不可能一次改变十件事，但一定能改变一件事。

A1 — 书中的应用 (Past Application)

案例 1: 某制造企业的"沉默成本"挖掘

问题: 副总发现工厂效率停滞，每次开会都是"一切正常"，但利润没有改善。
方法论的使用: 每周五下午，副总亲自到车间找一名工人单独聊，用Start/Stop/Keep框架。三周后，一名老员工说："Stop让我们加班后还要花2小时填纸质考勤表。"
结论: 这个"小事"涉及工厂200多人，每月浪费约600小时在无意义的行政流程上。
结果: 取消纸质考勤改为人脸识别，次月工厂净利润提升3%。

案例 2: 科技公司的跨部门壁垒拆除

问题: 产品和研发互相指责对方导致上线延误，协作成本居高不下。
方法论的使用: CEO每周分别与一名产品经理和一名工程师单独吃饭，用Start/Stop/Keep收集反馈。第四周，两人都提到同一个Stop项："Stop在每次发布前临时增加需求。"
结论: 问题根源是需求变更没有正式流程，导致开发和测试反复返工。
结果: 建立"需求冻结日"制度，发布延误率下降70%。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

感觉信息不通透时：用户说"我不知道下面的人在想什么"或"开会时大家都不说真话"。
流程效率低下时：有明显的执行摩擦，但不确定根本原因在哪里。
组织扩张后文化稀释时：团队从30人扩到100人，创始人感觉和一线脱节了。
员工绩效问题反复出现时：同一个问题在不同人身上反复发生，可能是系统性障碍而非个人问题。
战略落地效果不好时：方向定了但执行跟不上，不知道卡在哪里。

语言信号 (用户的话里出现这些就应激活)

"我想知道一线……"
"为什么执行力……"
"员工不敢说……"
"流程太……"
"那个问题又出现了"

与相邻 skill 的区分

与 Routine Sets You Free 的区别：Routine强调的是建立自己的习惯体系，这个强调的是从员工那里获取反馈——前者是自我管理，后者是组织感知。
与 Don't Demotivate; Dehassle 的区别：去障碍原则告诉管理者要主动消除障碍，这个skill提供了收集障碍信息的具体方法。

E — 可执行步骤 (Execution)

当 skill 被激活后，agent 应按以下步骤执行:

建立每周一对一反馈节奏
- 固定时间（如周五下午）、固定形式（一杯咖啡或一段散步）、选择不同层级或部门的员工
- 完成标准：未来4周已锁定4个不同的对话对象
用 Start/Stop/Keep 框架收集并记录
- 谈话时先问Start（什么应该开始做），再问Keep（什么应该保持），最后问Stop（什么应该停止）——把Stop留到最后，因为这是最重要的
- 完成标准：每次谈话后记录3个Stop候选项
每周选出1个最高优先Stop项并采取行动
- 选择标准：影响面最大（跨部门/多人受影响）、实施成本最低、预期效果最明显
- 判停条件：若连续3周没有可行的Stop项，重新审视反馈质量——可能是对话对象选择不对或心理安全感不足
- 完成标准：选出Stop项后，在下周对话时主动告知进展（闭环反馈）

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

作为绩效考核工具：一旦反馈与考核挂钩，员工会说他们认为你想听的话，而不是真话。
在信任严重缺失的组织中使用：当员工已经不相信高层会真正改变时，这个方法会被视为作秀，需要先修复基本信任。
外部董事或投资人角色：他们和员工之间没有足够的信任基础，面对面反馈往往无效。

作者在书中警告的失败模式

问了不行动，问了不闭环，是最大的失败模式——员工会很快学会"说也没用"。

作者的盲点 / 时代局限

对远程和分布式团队的执行方式没有提供具体指导——线下一对一散步的方法在远程环境需要调整。

容易混淆的邻近方法论

Weekly Stop Item 与**数据驱动决策（Data-Driven）**：数据告诉你发生了什么，这个skill告诉你为什么和该做什么——两者互为补充，但数据不能替代直接对话。

审计信息

验证通过: V1 ✓ / V2 ✓ / V3 ✓
测试通过率: 待填充
蒸馏时间: 2026-04-26

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

test-prompts.json2 KB

Frequently asked questions

What does the Weekly Stop Item AI skill do?

Why use Weekly Stop Item on TypingMind?

Because you install it once and use it with any model. Weekly Stop Item is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Weekly Stop Item in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/weekly-stop-item. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Weekly Stop Item?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Weekly Stop Item?

As many as you like. As long as a model supports skills, you can use Weekly Stop Item with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Weekly Stop Item AI skill free?

Yes. It is published on GitHub by ace3000chao under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Weekly Stop Item

Overview