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Fast Pulse Fast Growth

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ace3000chao
fast-pulse-fast-growth

用于设计组织节奏和会议体系。当用户在讨论会议效率、组织节奏、成长速度时激活。 不适用于：个人时间管理（那是GTD范畴）、具体的会议议程设计。 关键 trigger：提到会议太多/太少、成长瓶颈、决策太慢、组织效率。

Overview

Publisherace3000chao
Repositorybook2startup
Skill namefast-pulse-fast-growth
Stars
93
Forks
14
Bundled files
1
LicenseMIT
Links
Skill sourceRepository
  • 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 Fast Pulse Fast Growth AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/fast-pulse-fast-growth
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

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/fast-pulse-fast-growth .claude/skills/fast-pulse-fast-growth
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Fast Pulse Fast Growth 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 Fast Pulse Fast Growth 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 Fast Pulse Fast Growth 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.

Fast Pulse Fast Growth

R — 原文 (Reading)

"Those who pulse faster, grow faster."

— Verne Harnish, Scaling Up, 第1章

I — 方法论骨架 (Interpretation)

Scaling Up 的组织进化论核心命题：组织的心跳（会议节奏）越快，成长越快。这不是关于忙碌，而是关于反馈回路的速度。

人类的神经系统需要高频反馈才能快速学习和调整——组织也一样。一年一次战略会议、一季度一次复盘的组织，在VUCA环境中必然反应迟钝。

Scaling Up 标准节奏：日站会（daily huddle）→ 周例会（weekly meeting）→ 月复盘（monthly review）→ 季规划（quarterly planning）→ 年审视（annual summit）。每层节奏解决不同时间跨度的问题，缺一不可。

快脉搏的本质不是开更多会，而是让决策周期匹配业务变化的周期。零售可能需要日节奏，战略可能需要季节奏，但每个层级都不能缺失。

A1 — 书中的应用 (Past Application)

案例 1: 某零售连锁从月到周的蜕变

  • 问题: 总部与门店的决策周期差：总部每月开一次经营会，门店每天遇到问题，但解决方案要30天后才能下达。
  • 方法论的使用: 将总部经营会从每月改为每周，同时要求每个区域负责人每周到2家门店实地了解情况。引入"日站会"在门店层面解决日常问题，无需上报。
  • 结论: 层级化的节奏体系让问题在合适的层级被解决，总部聚焦战略，门店自主运营。
  • 结果: 门店问题平均解决时间从28天缩短到3天，单店利润率提升11%。

案例 2: 科技公司的"双周节奏"

  • 问题: 产品迭代采用季度OKR，但互联网环境三个月内的用户反馈已经发生了巨大变化，季度目标经常在第三个月完全失效。
  • 方法论的使用: 建立"双周节奏"：每两周做一次小的产品路线图回顾，双周内不允许路线图变更（保证执行力），双周结束时可以调整下一双周的优先级。
  • 结论: 快节奏不意味着没有稳定性——关键是在"执行周期"和"复盘周期"之间找到平衡。
  • 结果: 产品方向调整的响应时间从90天缩短到14天，用户NPS在半年内提升22点。

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 感觉决策太慢时：用户说"一个事情要开三次会才能定下来"或"等批下来市场都变了"。
  2. 会议体系混乱时：有太多临时的"对齐会"，或者会议很多但没有决策质量。
  3. 组织扩张后协调成本上升时：从20人扩到100人，跨部门协作变得缓慢而复杂。
  4. 讨论要不要开某种会议时：在犹豫某个新的定期会议是否必要。
  5. 季度目标经常无法完成时：可能是节奏设计问题——目标定在季度但执行反馈在月度，纠偏太晚。

语言信号 (用户的话里出现这些就应激活)

  • "会议太多了……"
  • "决策太慢……"
  • "成长遇到瓶颈……"
  • "节奏……"
  • "多久开一次……"

与相邻 skill 的区分

  • 与 Less Is More Priorities 的区别：聚焦是内容选择，快脉搏是时间节奏——你可以聚焦得很好但节奏太慢导致错过窗口。
  • 与 Strategy Must Be Discussed Weekly 的区别：战略周论解决的是战略思考的频率，这个解决的是整体组织的节奏设计，包括执行、反馈、复盘全周期。

E — 可执行步骤 (Execution)

当 skill 被激活后，agent 应按以下步骤执行:

  1. 诊断当前各层级节奏的覆盖情况

    • 绘制当前组织的"节奏地图"：日（谁和谁开会/碰头）→ 周（固定周会有什么）→ 月（月度复盘谁参加）→ 季（季度规划和谁负责）
    • 完成标准：一张覆盖5个时间层级的当前节奏图

  2. 识别缺失或过慢的节奏层级

    • 常见问题：日层级缺失（没有日站会，信息传递靠微信群随意化）→ 月层级过重（所有问题都积累到月度解决）→ 季层级缺失（没有真正的季度复盘）
    • 判停条件：若节奏图显示5个层级都已覆盖，直接进入步骤3

  3. 修复最关键的节奏断层

    • 选择标准：当前对组织伤害最大的节奏缺失（如门店扩张后日层级沟通断掉）
    • 设计最小可行节奏：先建立习惯，再优化质量
    • 完成标准：产出一份包含新增/调整节奏的落地计划（谁、在什么时候、讨论什么）

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 团队<5人的极早期阶段：5人以内几乎不需要正式节奏，口头沟通效率更高，建立过多会议反而伤害创业公司的敏捷优势。
  • 强监管合规场景：如金融、医疗行业的某些合规要求本身就有固定节奏，过度增加频率可能违反监管规定。
  • 远程分布式团队的跨时区协作：如果核心团队跨越5个以上时区，日节奏的可行性需要特殊设计，不能简单套用标准框架。

作者在书中警告的失败模式

  • 把节奏等同于"更多的会"——没有决策产出的日站会是形式主义，快节奏反而消耗组织能量。

作者的盲点 / 时代局限

  • 对异步协作工具（飞书、Slack、Notion）支撑下的分布式节奏覆盖不足——书中以现场会议为主要场景假设。

容易混淆的邻近方法论

  • Strategy Must Be Discussed Weekly：战略周论是快脉搏框架在"战略层面"的具体落地——前者是后者的子集，但快脉搏还包括日/月的执行节奏。

相关 skills (阶段 3 填充)

  • depends-on: [less-is-more-priorities]
  • contrasts-with: [strategy-must-be-discussed-weekly]
  • composes-with: [weekly-stop-item]

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.

Frequently asked questions

What does the Fast Pulse Fast Growth AI skill do?

用于设计组织节奏和会议体系。当用户在讨论会议效率、组织节奏、成长速度时激活。 不适用于：个人时间管理（那是GTD范畴）、具体的会议议程设计。 关键 trigger：提到会议太多/太少、成长瓶颈、决策太慢、组织效率。

Why use Fast Pulse Fast Growth on TypingMind?

Because you install it once and use it with any model. Fast Pulse Fast Growth 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 Fast Pulse Fast Growth in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/ScalingUp-skills/fast-pulse-fast-growth. 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 Fast Pulse Fast Growth?

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 Fast Pulse Fast Growth?

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

Is the Fast Pulse Fast Growth 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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