Business Model Evaluator

Community

kangarooking

business-model-evaluator

当用户需要评估一个生意/行业/公司的商业模式好坏时使用。典型触发：用户说"这个生意值得做吗""这个行业好不好赚钱""这家公司有护城河吗""为什么有的行业很苦却赚不到钱"。核心工具：差异化→护城河→定价能力的三段递推链，加上"能涨价=有护城河"的快速验证法。不适用于：纯财务分析（看财报数字）、股票技术分析、个人理财建议。

Overview

Publisher	kangarooking
Repository	`duan-yongping-skill`
Skill name	`business-model-evaluator`
Stars	57
Forks	13
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 kangarooking on GitHub. Read the source before you install it.

Installation

Install the Business Model Evaluator 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/kangarooking/duan-yongping-skill/tree/main/business-logic/business-model-evaluator
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/kangarooking/duan-yongping-skill/tree/main/business-logic/business-model-evaluator

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/kangarooking/duan-yongping-skill.git /tmp/duan-yongping-skill
mkdir -p .claude/skills
cp -r /tmp/duan-yongping-skill/business-logic/business-model-evaluator .claude/skills/business-model-evaluator

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

Use it in TypingMind

Enable Business Model Evaluator 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 Business Model Evaluator 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 Business Model Evaluator 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.

商业模式评估：差异化→护城河→定价能力

R — 原文 (Reading)

"差异化指的是产品能满足用户的某个或某些别人满足不了的需求。能够长期维持的差异化就是护城河。"

— 段永平, 第2节

"能涨价的东西就表示他有'护城河'。定价能力和护城河其实是一回事吧？"

— 段永平, 第2节

I — 方法论骨架 (Interpretation)

这是一套评估商业模式好坏的递推分析链：

差异化（用户需要但对手无法满足的东西）→ 护城河（能长期维持的差异化）→ 定价能力（能涨价而客户不流失）

三段之间存在严格的递推关系：

没有差异化 → 只能靠价格竞争 → 行业整体不赚钱（如航空、光伏）
有差异化但不持久 → 短期赚钱但很快被复制 → 不是真正的护城河
有持久差异化 → 可以持续提价 → 好的商业模式

快速验证法：看这家公司过去几年能不能持续涨价而客户不跑。能涨价=有护城河。成本优势不是可持续的护城河——低价谁都能做，但能涨价需要消费者不可替代的认可。

行业差异化的光谱：差异化极小（航空、光伏、大宗商品）→ 差异化中等（智能手机、汽车）→ 差异化很大（白酒、奢侈品、苹果生态）。差异化越大的行业越容易出好公司。

A1 — 书中的应用 (Past Application)

案例 1: 航空业——差异化极小的反面教材

问题: 为什么巴菲特说"如果有一个富有远见的资本家在场，他会把所有飞机打下来"？
方法论的使用: 航空业的差异化极小——消费者选择航班的核心诉求是从A到B的成本最低，没有品牌忠诚度
结论: 差异化小→护城河浅→没有定价能力→长期不赚钱
结果: 自人类首次飞行以来，航空公司股东的累计回报为负值

案例 2: 茅台——差异化和定价能力的正面案例

问题: 茅台的商业模式为什么好？
方法论的使用: 巨大的感知和口味差异化（白酒没有人因为便宜5%就换品牌），而且库存会增值而非贬值
结论: 差异化大→护城河深→持续提价能力→极好的商业模式
结果: 茅台多年持续提价而销量不减，库存越久越值钱

案例 3: 苹果——差异化的终极形态

问题: 苹果为什么比其他手机公司赚钱多得多？
方法论的使用: 苹果的差异化不仅是硬件，而是整个生态系统（iOS+iCloud+App Store）的锁定效应——用户转换成本极高
结论: 生态系统级别的差异化是最深的护城河
结果: 苹果占智能手机行业利润的绝大部分

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

用户在考虑是否进入某个行业或做某个生意
用户在评估一家公司是否值得投资（买股票或收购）
用户在分析竞争对手为什么比自己赚钱
用户的产品利润率低，想知道根本原因
用户在判断一个行业是"好行业"还是"苦行业"

语言信号 (用户的话里出现这些就应激活)

"这个生意/行业值得做吗"
"为什么XX行业那么苦/不赚钱"
"这家公司有护城河吗"
"我们的利润率为什么这么低"
"为什么苹果/茅台那么赚钱"
"好生意的标准是什么"

与相邻 skill 的区分

与 right-business-people-price 的区别: right-business-people-price 是投资三要素的总纲（告诉你看什么维度），本 skill 是 Right Business 维度的深入展开（教你具体怎么分析商业模式）
与 profit-above-pursuit 的区别: profit-above-pursuit 诊断企业文化（人的因素），本 skill 分析商业模式（生意的因素）

E — 可执行步骤 (Execution)

识别差异化
- 完成标准: 列出该行业/公司产品的所有差异化点，标注每个差异化点是"用户可感知"还是"表面不同"
- 判断: 如果找不到任何用户真正需要但对手无法满足的点 → 差异化极小 → 大概率不是好商业模式
评估差异化的可持续性
- 完成标准: 对每个差异化点问"对手能在1-3年内复制吗？"
- 判停条件: 如果所有差异化都能被快速复制 → 不是护城河 → 不值得长期投入
测试定价能力（护城河验证）
- 完成标准: 回答"如果涨价10-20%，客户会跑吗？为什么跑或不跑？"
- 关键信号: 能涨价而不流失客户 = 有护城河；成本优势不是可持续护城河
综合判断
- 完成标准: 给出"差异化→护城河→定价能力"三段结论，以及最终商业模式评级

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

早期创业项目（差异化可能尚未形成，但潜力巨大——此时用差异化框架会过度否定）
垄断性行业（行政垄断的定价能力不反映商业模式优劣）
纯短期交易（不是为了长期持有或经营，差异化的重要性降低）

作者在书中警告的失败模式

把成本优势当护城河: "没有见过成本优势可以成护城河的，很少有企业能长期维持低成本"
把规模当护城河: 规模大不等于差异化，不等于有定价能力
忽视差异化的动态性: "差异化在不断变化，大家都有的差异化就变成基本需求"

作者的盲点 / 时代局限

段永平的分析框架偏向消费类/品牌类企业，对技术驱动型公司（AI、生物医药）的差异化评估可能需要补充（如专利壁垒、网络效应等）
"能涨价=有护城河"在强监管行业（如电力、通信）不适用——涨价受政策限制

容易混淆的邻近方法论

波特五力: 波特分析行业竞争格局，本 skill 聚焦单一公司的差异化可持续性——更聚焦、更可操作
SWOT分析: SWOT是全面但肤浅的扫描，本 skill 是深度递推链——因果逻辑更清晰

审计信息

验证通过: V1 ✓ / V2 ✓ / V3 ✓
测试通过率: {{%}} (详见 test-prompts.json)
蒸馏时间: 2026-04-16

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.json7 KB

Frequently asked questions

What does the Business Model Evaluator AI skill do?

Why use Business Model Evaluator on TypingMind?

Because you install it once and use it with any model. Business Model Evaluator 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 Business Model Evaluator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kangarooking/duan-yongping-skill/tree/main/business-logic/business-model-evaluator. 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 Business Model Evaluator?

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 Business Model Evaluator?

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

Is the Business Model Evaluator AI skill free?

Yes. It is published on GitHub by kangarooking 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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Business Model Evaluator

Overview