Peer Selection logo

Peer Selection

CommunityPopular
kangarooking
peer-selection

当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values

Overview

Publisherkangarooking
Repositorycangjie-skill
Skill namepeer-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 Peer 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/peer-selection .claude/skills/peer-selection
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Peer 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 Peer 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 Peer 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.

同伴选择：五只黑猩猩

R — 原文 (Reading)

有个“五只黑猩猩的理论”，你可以通过它最常接触的五个黑猩猩来预测一个黑猩猩的行为。……你不应该随意地选择你的朋友，仅仅是因为你们住的比较近或者碰巧在一起工作。选择了正确的五只黑猩猩的人，是最快乐和最乐观的人。

— 纳瓦尔·拉维坎特, 《纳瓦尔宝典》 第二章·幸福

I — 方法论骨架 (Interpretation)

你的行为、情绪和成就由最常接触的五个人预测——所以同伴选择是人生最重要的主动决策之一。 三个原则： ① 主动选择——朋友不是地理/巧合的产物，而是价值观筛选的结果； ② 按场景配置——「工作时，身边要有比你更成功的人；玩乐时，身边要有比你更快乐的人」； ③ 远离负向者——愤世嫉俗者/悲观主义者会传染负面预期；处理冲突的第一规则是「不要和那些经常发生冲突的人在一起」；「如果你不能看到你与某人一起工作一辈子，那么连一天也不要和他共事」。 判断信号：总说自己诚实的人多半不诚实；花很多时间谈论价值观的人可能在掩盖什么； 价值观一致时小事不重要，价值观冲突才是争吵的根源。

A1 — 书中的应用 (Past Application)

案例 1: 贝赫扎德的「哇」

  • 问题: 如何保持对生活的感恩与乐观
  • 方法论的使用: 学习热爱生活、不浪费时间在不快乐的人身上
  • 结论: 他的诀窍是「停止询问为什么，开始说哇」
  • 结果: 成为作者心中选择正确同伴的样板

案例 2: 从生活中剔除负面者

  • 问题: 有人做损害他人的事
  • 方法论的使用: 第一次提醒，不改就保持距离、从生活中切割
  • 结论: 「越想靠近我的，你的价值观必须要更好」
  • 结果: 圈子成为价值观过滤后的结果

A2 — 触发场景 (Future Trigger) ★

用户会在什么情境下需要这个 skill?

  1. 换城市/换工作后的交友
  2. 被朋友拖累：「朋友总在抱怨，我也变消极了」
  3. 择偶/亲密关系选择
  4. 想改变圈子：「我想认识更优秀/更快乐的人」

语言信号

  • "我该交什么样的朋友"
  • "要不要疏远某人"
  • "怎么认识优秀的人/换圈子"
  • "who should I surround myself with / toxic friends"

与相邻 skill 的区分

  • 与 long-term-compounding 的区别: 本 skill 选「和谁生活」；复利 skill 选「和谁做生意」
  • 与 honesty-communication 的区别: 诚实是自我标准，本 skill 是外部筛选标准

E — 可执行步骤 (Execution)

  1. 盘点你的五只黑猩猩

    • 完成标准: 列出最常接触的 5 人，逐个标「积极/消极/中性」，评估他们预测了你的什么行为

  2. 按场景调整配置

    • 完成标准: 明确工作圈和玩乐圈分别缺什么（更成功/更快乐），列出 1 个具体加入动作（活动/社群/项目）

  3. 处理负向关系

    • 完成标准: 对每个消极关系选一：改造（明确沟通）、边界（减少接触频次）、或切割（退出）
    • 判停条件: 若对方是亲属/同事无法切割，改为设置接触边界并补齐正向外圈

  4. 建立价值观检查

    • 完成标准: 写下一份 3–5 条核心价值观清单，用来判断新朋友是否「小事不重要、大事一致」

B — 边界 (Boundary) ★

不要在以下情况使用此 skill

  • 必须共事的同事/家人（先边界，再切割）
  • 用户自身处于低谷、把责任全推给环境（先自我负责再选圈）

作者在书中警告的失败模式

  • 随意选友: 「仅仅是因为你们住的比较近或者碰巧在一起工作」
  • 与经常冲突的人在一起: 冲突是低质量关系的信号，不是性格磨合

作者的盲点 / 时代局限

  • 「远离不快乐的人」在家庭/社群文化中的执行成本高，且可能滑向同温层
  • 五只黑猩猩是预测性比喻，非严谨心理学结论

容易混淆的邻近方法论

  • long-term-compounding: 生意伙伴选「能共事一辈子」；生活同伴选「价值观一致+积极」

相关 skills (阶段 3 定稿)

  • composes-with: happiness-skill、long-term-compounding、honesty-communication

审计信息

  • 验证通过: V1 ✓ / V2 ✓ / V3 ✓ (v15)
  • 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 Peer Selection AI skill do?

当用户纠结交朋友/选伴侣/换圈子、感觉被周围人拖累、问「该不该疏远某人」时调用。 核心理念: 五只黑猩猩理论(你的行为由最常接触的5人预测); 同伴是主动选择而非巧合; 只与价值观一致者深交, 远离愤世嫉俗者/愤怒者。 不适用于: 职场必须共事的同事关系(可先设边界)。 Triggers: 朋友/圈子/伴侣/该不该疏远/被拖累/五只黑猩猩/peer/friends/circle/values

Why use Peer Selection on TypingMind?

Because you install it once and use it with any model. Peer 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 Peer 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/peer-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 Peer 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 Peer Selection?

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

Is the Peer 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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