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Reject Vanity Metrics

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ace3000chao
reject-vanity-metrics

识别和拒绝虚荣指标,追踪可执行的真正进展。当团队在会议上只报好消息、不知道如何向投资人展示进展、感觉在进步但实际方向不清晰时,使用此Skill。

Overview

Publisherace3000chao
Repositorybook2startup
Skill namereject-vanity-metrics
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 Reject Vanity Metrics 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/008-reject-vanity-metrics
  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 Reject Vanity Metrics 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 Reject Vanity Metrics 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 Reject Vanity Metrics 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: 拒绝虚荣指标

Metadata

  • ID: leanstartup-008
  • 类型: principle
  • 来源: 《精益创业》第七章
  • 验证状态: ✅ 三重验证通过(V1: 3章以上论证, V2: 团队日常决策, V3: 极反直觉)

R — Reading(原文引用)

"虚荣指标是指那些让人感觉良好但无法指导行动的数据。如果我们被这些'总顾客数量'等等的虚荣指标误导,那么创新核算就无从谈起。"

"在会议上争论报告中测量单位的人都会发现这个问题。新创企业被虚荣指标误导非常危险。"

I — Interpretation(方法论骨架)

虚荣指标的核心特征:让人感觉良好,但无法告诉你该做什么。

常见虚荣指标:

虚荣指标听起来像什么实际在说什么
总用户数"我们有100万用户"但不知道多少人还在用
总收入"年收入500万"但不知道获客成本是多少
页面浏览量"日PV50万"但不知道用户在做什么
粉丝/关注数"微博10万粉丝"但不知道转化了多少付费

可执行指标的核心:能回答"我下一步该做什么"。

A1 — Past Application(书中案例)

IMVU的虚荣指标陷阱:IMVU每月报"总注册用户XX万",团队士气高涨。但同一时期,同期群数据显示每个新用户群的收益从未提升。当团队最终面对真实数据时,发现增长引擎早已停滞,错过了最佳转型时机。

Grockit的对比测试教训:团队花了6个月优化各种"指标"(总用户数、答题总数),感觉在进步。但对比测试揭示,他们自认为有效的功能实际上对用户行为毫无影响。如果不是用同期群对比测试,他们会继续在错误的方向上投入。

A2 — Future Trigger(何时调用)

当你听到以下问题时,就应该调用这个Skill:

  • "我们上周数据表现不错"——但说不清为什么好
  • "用户数增长了"——但不知道是自然增长还是营销拉动
  • "这个功能应该有效"——但没有数据支持
  • 会议上只报"好消息",没人提"坏消息"
  • 不知道下个月的优先级是什么

E — Execution(可执行步骤)

步骤1:列出你现在追踪的所有指标

列出团队目前追踪的TOP 10指标,逐个问:

步骤2:用三个问题验证每个指标

问题1:可执行吗?

"如果这个数字上升/下降,你知道下一步该做什么吗?"

  • 如果不能回答,说明是虚荣指标
  • 如果能回答"做X",继续问问题2

问题2:可使用吗?

"团队里的每个人都能理解这个数字的含义吗?"

  • 如果需要专业知识才能解释,说明不够"可使用"
  • 如果任何人都能理解,继续问问题3

问题3:可审查吗?

"任何人都能验证这个数字的真实性吗?"

  • 如果数据来源不透明,说明不是"可审查"
  • 如果来源透明、数据真实,这个指标通过了三重检验

步骤3:用可执行指标替换虚荣指标

虚荣 → 可执行
总用户数 → 同期群激活率
总收入 → 收入/同期群
页面浏览量 → 核心功能使用率
注册用户数 → 激活率+留存率

步骤4:建立指标仪表盘

原则:仪表盘只显示能指导行动的可执行指标,不超过5个核心指标。

让每个人都能看到:

  • 我们在追踪什么
  • 当前值是多少
  • 趋势是升还是降
  • 下一周优先做什么

B — Boundary(何时不适用)

不适用场景原因
向外部(如媒体)展示品牌影响力这时候虚荣指标是必要的品牌包装
成熟业务的董事会汇报成熟业务的标准和早期创业不同
只需要展示"规模"给投资人时但这不能代替内部决策用的可执行指标

作者盲点提醒:虚荣指标让人上瘾——因为它们总是看起来很好看。拒绝虚荣指标需要组织的勇气:愿意面对不好看的数字,愿意承认"我们以为在进步但实际上没有"。没有这种心理安全感的团队,会本能地选择相信虚荣指标。

关联Skills

  • 创新核算三步骤 — 教你建立正确的衡量体系
  • 三个"可"衡量指标 — 教你判断指标是否有效
  • 同期群分析 — 拒绝虚荣指标的核心工具

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 Reject Vanity Metrics AI skill do?

识别和拒绝虚荣指标,追踪可执行的真正进展。当团队在会议上只报好消息、不知道如何向投资人展示进展、感觉在进步但实际方向不清晰时,使用此Skill。

Why use Reject Vanity Metrics on TypingMind?

Because you install it once and use it with any model. Reject Vanity Metrics 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 Reject Vanity Metrics 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/008-reject-vanity-metrics. 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 Reject Vanity Metrics?

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 Reject Vanity Metrics?

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

Is the Reject Vanity Metrics 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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