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Game Selection

CommunityPopular
kangarooking
game-selection

当用户困惑「为什么有人攻击我/为什么大家卷来卷去/我怎么不在乎别人眼光/为什么妒忌」时调用。 核心理念: 人生同时存在零和地位游戏、正和财富游戏、单人游戏; 识别你玩的是哪种游戏, 避免地位游戏, 回到内在记分卡。 不适用于: 具体竞争策略制定（如何赢下某个比赛）。 Triggers: 地位/攀比/内卷/妒忌/别人怎么看我/零和/单人游戏/status game/envy

Overview

Publisherkangarooking
Repositorycangjie-skill
Skill namegame-selection
Stars
10.2K
Forks
1.2K
Bundled files
2
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.

  • 2 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 Game Selection 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.
  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/kangarooking/cangjie-skill.git /tmp/cangjie-skill
mkdir -p .claude/skills
cp -r /tmp/cangjie-skill/books/naval-almanack-skill/game-selection .claude/skills/game-selection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Game Selection 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 Game Selection 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 Game Selection 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.

游戏选择：识别地位游戏与单人游戏

R — 原文 (Reading)

财富创造是最近进化出来的正和游戏。地位争夺是古老的零和游戏。那些攻击财富创造的人通常只是在追求地位。……事实上，人生就是一场单人游戏。你是独自一个人来到世界的。也将独自死去。

— 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第一章·财富 / 第二章·幸福

I — 方法论骨架 (Interpretation)

人在一生中同时被卷入三种游戏，关键是识别自己在玩哪一种： ① 地位游戏（零和）——等级排名，赢家必须击倒别人，政治/体育/学术排名属此类；参与它会让人愤怒好斗； ② 财富游戏（正和）——把饼做大，人人可赢，是近现代才出现的新游戏； ③ 单人游戏（内在）——幸福、平静、自我成长，没有外部进度条和外部验证，所有真正的记分卡都在内在。 使用方法：被攻击时先问「他在玩什么游戏」（攻击创造财富者的人多在追求地位）； 被攀比/妒忌困扰时，用巴菲特的内在/外在记分卡测试，并用妒忌消解法——「如果我不愿与他完全交换身份，妒忌就无意义」。

A1 — 书中的应用 (Past Application)

案例 1: 巴菲特的内在记分卡

  • 问题: 用外部名声还是内在标准评价自己
  • 方法论的使用: 问「你想成为名声最差但最好的情人，还是名声最好但最糟糕的情人」
  • 结论: 所有真正的记分卡是内在的
  • 结果: 作者转向修炼内在自我

案例 2: 妒忌消解实验

  • 问题: 年轻时妒忌心重
  • 方法论的使用: 意识到「我不能只选他人生活的某几个片段，要么完全交换身份要么不妒忌」
  • 结论: 「一旦我意识到这一点，妒忌就会消失，因为我不想成为别人」
  • 结果: 妒忌不再主导情绪

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 被攻击/被比较：「为什么有人针对我/贬低我」
  2. 内卷倦怠：「大家都这么卷有意义吗」
  3. 妒忌：「看到别人成功我好难受」
  4. 意义校准：「我做这件事到底为了什么」

语言信号

  • "别人在玩什么游戏/为什么都针对我"
  • "我很妒忌/很在意别人看法"
  • "内卷/攀比/面子"
  • "status / zero-sum / why do people attack me / envy"

与相邻 skill 的区分

  • 与 long-term-compounding 的区别: 本 skill 识别博弈结构；复利 skill 处理时间尺度
  • 与 happiness-skill 的区别: 本 skill 是博弈分类，幸福 skill 是状态训练

E — 可执行步骤 (Execution)

  1. 识别游戏类型

    • 完成标准: 对当前处境回答「这是零和、正和、还是单人游戏？」
    • 判停条件: 若确认是零和地位游戏且非必要，直接标记「不值得赢」，跳到步骤 3

  2. 测试记分卡

    • 完成标准: 问自己「如果把外部评价全部移除，这件事我还做吗？」——区分内在/外在动机

  3. 跑妒忌消解

    • 完成标准: 对每个妒忌对象问「我愿意与他完全交换身份（包括所有反应/家庭/自我形象）吗？」；不愿→放下

  4. 回到单人游戏投入

    • 完成标准: 把本周至少 1 项行动改为「只为自己的内在标准」执行

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 用户需要在竞争里赢（体育/职场晋升）——此时应给竞争策略而非「退出游戏」
  • 地位游戏无法避免的场合（政治/组织内），本书立场是识别而非硬刚

作者在书中警告的失败模式

  • 玩地位游戏会让你变成愤怒好斗的人: 「你总是在窝里斗，损人利己」
  • 用外部进度条训练内在能力: 瑜伽/冥想难坚持是因为没有外在价值

作者的盲点 / 时代局限

  • 「完全不玩地位游戏」在组织生存中并不现实；作者有资本网络作为退路
  • 单人游戏叙事可能滑向回避现实竞争

容易混淆的邻近方法论

  • long-term-compounding: 长期正和游戏 vs 零和地位游戏是两类判据，先分类再选

相关 skills (阶段 3 定稿)

  • contrasts-with: long-term-compounding（正和/零和 vs 长期/短期）
  • composes-with: happiness-skill（单人游戏是幸福的地基）

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓ (v09)
  • 测试通过率: 见 test-results.md
  • 蒸馏时间: 2026-08-01

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 Game Selection AI skill do?

当用户困惑「为什么有人攻击我/为什么大家卷来卷去/我怎么不在乎别人眼光/为什么妒忌」时调用。 核心理念: 人生同时存在零和地位游戏、正和财富游戏、单人游戏; 识别你玩的是哪种游戏, 避免地位游戏, 回到内在记分卡。 不适用于: 具体竞争策略制定（如何赢下某个比赛）。 Triggers: 地位/攀比/内卷/妒忌/别人怎么看我/零和/单人游戏/status game/envy

Why use Game Selection on TypingMind?

Because you install it once and use it with any model. Game Selection 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 Game Selection in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kangarooking/cangjie-skill/tree/main/books/naval-almanack-skill/game-selection. 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 Game Selection?

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 Game Selection?

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

Is the Game Selection 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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