Quanmiao Wei Shang logo

Quanmiao Wei Shang

Community
ace3000chao
quanmiao-wei-shang

当你面临"战还是和"的重大抉择时, 当你有机会以最小代价获得最大成果时, 当你想理解"不战而屈人之兵"的最高境界时—— 调用此skill理解"全胜为上"的竞争哲学。

Overview

Publisherace3000chao
Repositorybook2startup
Skill namequanmiao-wei-shang
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 Quanmiao Wei Shang 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/孙子兵法skills/全胜为上
  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 Quanmiao Wei Shang 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 Quanmiao Wei Shang 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 Quanmiao Wei Shang 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: 全胜为上框架

R — 原文引用

"凡用兵之法,全国为上,破国次之;全军为上,破军次之;……是不战而屈人之兵,善之善者也。" ——孙子·谋攻第三

I — 方法论骨架

竞争的四层境界:

境界方式代价孙子评价
全国不战而屈人之兵零善之善者
破国战争征服极高次之
全军完整接收低上
破军歼灭有生力量高次之

核心洞察:

  • "不战"是最高效的胜利
  • 战争的代价不仅是金钱,更是生命和时间
  • 真正的高手让对手主动认输

现代转化:

古代现代商业
全国收购竞争对手而非打死
破国价格战打死对手
破军人才挖角
全军核心团队整体接收

A1 — 书中案例

孙武的上策:

  • "上兵伐谋" — 用战略智慧让对手放弃抵抗
  • "其次伐交" — 用外交手段孤立对手
  • "其次伐兵" — 不得已才动武

商业案例: 滴滴vs快的

  • 合并而非打死
  • 双方都避免了更大损耗
  • 投资人回报最大化

A2 — 未来触发情境

  • 🎯 有机会收购竞争对手时
  • 🎯 合作谈判中想"不战而屈"时
  • 🎯 团队面临被挖角风险时
  • 🎯 商业竞争中想以小博大时
  • 🎯 你想问"有没有不花钱也能赢的方法"时

E — 执行步骤

步骤1:评估"全 vs 破"

全胜收益 = 完整获得对方价值 - 战争成本
破胜收益 = 削弱对方价值 - 己方损耗

步骤2:寻找"不战"的可能

  • 对方有什么软肋可以施压?
  • 有什么共同利益可以绑定?
  • 有没有"合并"的可能?
  • 能否用"势"让对方主动退让?

步骤3:建立"全胜"的条件

  • 你的"势"是否足够大?
  • 对方是否有台阶可下?
  • 是否有中间人/投资人推动?

B — 边界(什么时候不适用)

❌ 边界1: 对手不愿屈服

  • 如果对手是"同归于尽"型
  • "全胜"只是你的一厢情愿

❌ 边界2: 时间紧迫

  • "全胜"往往需要更多时间
  • 如果时间窗口短,可能需要速战

❌ 边界3: 价值观冲突

  • 有时候"打"是必须的
  • 不是所有对手都值得"全胜"

相关Skills:

  • 伐谋框架
  • 合于利而动
  • 知彼知己

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 Quanmiao Wei Shang AI skill do?

当你面临"战还是和"的重大抉择时, 当你有机会以最小代价获得最大成果时, 当你想理解"不战而屈人之兵"的最高境界时—— 调用此skill理解"全胜为上"的竞争哲学。

Why use Quanmiao Wei Shang on TypingMind?

Because you install it once and use it with any model. Quanmiao Wei Shang 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 Quanmiao Wei Shang in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ace3000chao/book2startup/tree/master/孙子兵法skills/全胜为上. 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 Quanmiao Wei Shang?

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 Quanmiao Wei Shang?

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

Is the Quanmiao Wei Shang 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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