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Mvp Building

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ace3000chao
mvp-building

构建最小化可行产品来快速验证创业假设。当你有了一个创业想法、不确定顾客是否真的需要它、想在投入大量资源前先测试核心假设时,使用此Skill。

Overview

Publisherace3000chao
Repositorybook2startup
Skill namemvp-building
Stars
93
Forks
14
Bundled files
1
LicenseMIT
Links
  • 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 Mvp Building 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/精益创业skills/skills/001-mvp构建法
  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.

Use it in TypingMind

Enable Mvp Building 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 Mvp Building 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 Mvp Building 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.

Skill: MVP构建法

Metadata

  • ID: leanstartup-001
  • 类型: framework
  • 来源: 《精益创业》第五章
  • 验证状态: ✅ 三重验证通过(V1: 5+章节佐证, V2: 实战高频, V3: 非常识)

R — Reading(原文引用)

"最小化可行产品是满足早期用户核心需求的最简单产品形态,用于启动学习反馈循环。"

"如果在没有真实数据证实顾客会改变行为之前就开发新产品,就像是在黑暗中去射击。"

I — Interpretation(方法论骨架)

MVP的核心逻辑是**"最快速最便宜地验证最危险的假设"**:

  • 不是"做一个功能不全的产品凑合",而是"为验证假设而精确设计"
  • MVP的目的是学习,不是"发布产品"
  • 判断标准不是"功能多少",而是"能否在最短时间内、用最低成本获得关于核心假设的真实反馈"

A1 — Past Application(书中案例)

IMVU的第一个产品:作者团队花了6个月开发了一个"糟糕透顶"的产品,发布后几乎没人用。但通过快速迭代,最终获得6000万用户和5000万美元年收入。如果当初花2年做"完美产品"再发布,可能早就倒闭了。

Facebook的起步:第一个版本只有一个功能——投票选头像好不好看。根据用户反馈才逐步添加功能。

A2 — Future Trigger(何时调用)

当你听到以下问题时,就应该调用这个Skill:

  • "我有一个产品想法,怎么验证它有没有市场需求?"
  • "我要做一个App/平台/服务,应该从哪里开始?"
  • "团队总说资源不够开发所有功能,先做什么?"
  • "投资人要我做出完整产品才能给钱,但我只有有限的时间和预算"
  • "我在犹豫要不要把所有功能都做完再发布"

E — Execution(可执行步骤)

步骤1:识别最危险的假设

列出你的商业计划中最可能在市场上站不住脚的假设:

  • 顾客真的有这样的问题/需求吗?
  • 顾客愿意为此付费吗?
  • 你的解决方案是顾客会接受的吗?

原则:挑那个"如果错了整个业务就垮了"的假设优先验证。

步骤2:设计最小化实验

针对这个假设,设计一个能获得真实反馈的最简单产品:

  • 能否做一个一页纸的展示页面,看顾客会不会点击"注册"?
  • 能否做一个手动流程代替自动系统,先看顾客是否真的需要这个服务?
  • 能否做一个视频/模型给目标顾客看,收集真实反应?

判断标准:这个MVP能否在2周内、用最小资源完成,且能回答"顾客是否真的需要这个?"

步骤3:发布并收集真实行为数据

  • 关键是观察顾客的行为,而非问他们"你想要什么"
  • 顾客说的可能是错的,但顾客做的基本是真的
  • 如果顾客只是"感兴趣"但没有实际行动,说明假设未验证

步骤4:根据数据决定下一步

  • 数据支持假设 → 继续投入,开发更完整的产品
  • 数据不支持假设 → 立即调整/转型,不要把资源浪费在错误方向
  • 数据不明确 → 设计新的实验继续验证

B — Boundary(何时不适用)

不适用场景原因
硬件/制造业产品开发物理产品无法像软件一样快速迭代,MVP成本太高
需要大量初始资本的餐饮/零售店实体店开业前无法做真正的MVP测试
高度监管行业(医疗/金融)合规要求限制MVP的边界
已经是成熟市场的复制型业务这种情况下"验证"的意义不同,更多是执行问题

作者盲点提醒:MVP方法最适合软件/SaaS/互联网产品。对于需要实体生产的产品,MVP的成本和周期都不可控,需要调整策略。

关联Skills

  • Build-Measure-Learn循环 — MVP是BML循环的起点
  • 对比测试 — MVP验证后,用A/B测试优化
  • 转型决策树 — MVP数据不好时,知道何时转型

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 Mvp Building AI skill do?

构建最小化可行产品来快速验证创业假设。当你有了一个创业想法、不确定顾客是否真的需要它、想在投入大量资源前先测试核心假设时,使用此Skill。

Why use Mvp Building on TypingMind?

Because you install it once and use it with any model. Mvp Building 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 Mvp Building in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/精益创业skills/skills/001-mvp构建法. 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 Mvp Building?

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 Mvp Building?

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

Is the Mvp Building 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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