Partner With Admired

Q: What does the Partner With Admired AI skill do?

用户在选择合作伙伴、投资管理层、或评估是否应该与某人/某组织建立长期关系时。 语言信号:"这个管理层怎么样"/"要不要和这个人合作"/"两个机会选哪个"/"信任怎么验证" 不适用于:不需要长期关系评估的纯交易性决策。

Community

kangarooking

partner-with-admired

用户在选择合作伙伴、投资管理层、或评估是否应该与某人/某组织建立长期关系时。语言信号:"这个管理层怎么样"/"要不要和这个人合作"/"两个机会选哪个"/"信任怎么验证" 不适用于:不需要长期关系评估的纯交易性决策。

Overview

Publisher	kangarooking
Repository	`buffett-letters-skill`
Skill name	`partner-with-admired`
Stars	109
Forks	20
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 Partner With Admired 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/buffett-letters-skill/tree/main/partner-with-admired
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.

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/buffett-letters-skill.git /tmp/buffett-letters-skill
mkdir -p .claude/skills
cp -r /tmp/buffett-letters-skill/partner-with-admired .claude/skills/partner-with-admired

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

Use it in TypingMind

Enable Partner With Admired 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 Partner With Admired 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 Partner With Admired 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.

只与喜欢和钦佩的人合作（含吃自己的饭）

R — 原文 (Reading)

"We would rather achieve a return of X while associating with people whom we strongly like and admire than realize 110% of X by making a sour or unpleasant relationship." (1987) "We eat our own cooking." (1983)

I — 方法论骨架

两个合并的原则：

只与喜欢的人合作：宁取100%X配好关系，不要110%X配差关系。因为差关系会在你最意想不到的时候伤害你
吃自己的饭：验证信任的终极方法——看管理者是否把自己的钱也投进去

为什么重要：你无法改变别人的品格。短期回报差异远小于长期信任的价值。差的管理者会在顺境时拿走功劳，在逆境时背叛你。

A1 — 书中的应用

案例: TTI / Paul Andrews

问题: 为什么选择卖给伯克希尔而非竞争对手或PE？
使用: 竞争对手会裁人，PE关注"退出策略"——只有伯克希尔承诺永远持有
结果: 收购后收益增长673%，Paul Andrews继续热爱他的工作

案例: Mrs. B / Nebraska Furniture Mart

使用: "给了Mrs. B一张$5500万的支票，她给了我们她的承诺——这是一笔公平交易"
结果: 无需审计的信任创造了非凡回报

A2 — 触发场景

选择投资目标时评估管理层
选择商业合作伙伴
决定是否信任某个人的承诺
两个机会选一个（回报vs关系质量）

语言信号

"这个管理层可不可信？"
"应该和这个人合作吗？"
"两个机会怎么选？"
"怎么验证一个人的诚信？"

E — 可执行步骤

检验"吃自己的饭"
- 完成标准：管理者是否将自己的大部分财富投在了同一个地方？
做"钦佩测试"
- 完成标准：你愿意你的子女为这个人工作吗？如果不愿意 → 不合作
计算"关系折价"
- 完成标准：即使回报低10-20%，好关系是否仍然值得？如果是 → 选择好关系

B — 边界

"喜欢"不等于"软弱"——巴菲特也解雇过不称职的管理者
在某些市场（如高频交易），关系不重要
作者盲点：巴菲特有选择权——他可以等待好的伙伴出现；小投资者可能没有这个选择

审计信息

验证通过: V1 ✓ / V2 ✓ / V3 ✓
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.json2 KB

Frequently asked questions

What does the Partner With Admired AI skill do?

Why use Partner With Admired on TypingMind?

Because you install it once and use it with any model. Partner With Admired 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 Partner With Admired in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kangarooking/buffett-letters-skill/tree/main/partner-with-admired. 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 Partner With Admired?

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 Partner With Admired?

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

Is the Partner With Admired 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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Partner With Admired

Overview