Learn Occam

Community

Li-Evan

learn-occam

当用户纠结要不要学某个东西、学到什么程度，或在做时间/精力/项目取舍时使用。用「简易策略」先逼问要解决的既定问题，检验现有知识能否搞定，评估知识贬值速度与 ROI，用「探索 vs 应用」判断该学新的还是用现有的，给出「学 / 不学 / 只学最小够用」的结论，避免囤积会贬值的知识。触发场景：要不要学 X、值不值得深入、学到什么程度够、时间不够该学啥、该深挖还是够用就行。

Overview

Publisher	Li-Evan
Repository	`Bloom`
Skill name	`learn-occam`
Stars	292
Forks	43
Bundled files	Instructions only
License	MIT
Links	Skill source Repository Homepage

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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Li-Evan on GitHub. Read the source before you install it.

Installation

Install the Learn Occam 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/Li-Evan/Bloom/tree/main/skills/learn-occam
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/Li-Evan/Bloom.git /tmp/Bloom
mkdir -p .claude/skills
cp -r /tmp/Bloom/skills/learn-occam .claude/skills/learn-occam

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

Use it in TypingMind

Enable Learn Occam 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 Learn Occam 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 Learn Occam 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.

简易策略（learn-occam）

核心信条：这世界最有价值的不是知识，是你的时间。 能用现有知识解决的就别学新的；以后要用的，以后再学。

何时用

用户在纠结"要不要学 X / 学到什么程度 / 精力往哪放"。这是"广度优先、兴趣队列过长"倾向的刹车。

流程

第一步：先找"既定问题"

逼问一句：你要解决的具体问题是什么？ 没有具体问题、纯"感觉该学 / 别人都在学"→ 直接进"以后再学"队列，不占当下精力。理解知识的作用，重于知识本身。

第二步：现有知识能不能搞定

问清用户已经会什么——能解决就别学新的。拿不准"是不是其实已经会了"就配合 learn-crossover。

第三步：贬值速度 + ROI

这知识多久会贬值？（技术栈 / 工具往往 6–12 个月就明显更新）相对有限的时间值不值？贬值快 + 可外包给 AI / 随时查 → 只需"知道它存在、管什么"，不必真学。

第四步：探索 vs 应用（N 臂老虎机）

现在该"探索"（学新）还是"应用"（用现有）？探索成本越高 → 越该偏应用。只有目标够难、现有知识确实够不着时，简易策略才督促你学。

第五步：给结论

明确三选一：① 学（值得且现有搞不定）/ ② 不学（入"以后再学"队列）/ ③ 只学最小够用的那一块（点明是哪一小块）。要深挖就转 learn-graph 建路径。

注意

⚠️ 铁律·只用确证的已会知识：判断用户「已经会什么」只能用他确证学过的知识（亲口确认或可靠背景）；严禁把「正在讲的材料 / 文章作者背景 / 对话里别人的知识」当成用户会的。拿不准 → 直接问「⚠️ 你学过 ___ 吗？」，绝不替他假设。

简易策略不是"少学"，是"让问题决定你学什么"。
它的缺点是易陷局部最优——拿不准"是不是缺前置知识"时转 learn-graph。
同族 skill：learn-crossover(已会什么) learn-graph(系统建图) learn-prototype(动手迭代) learn-feynman(自查)。

Frequently asked questions

What does the Learn Occam AI skill do?

Why use Learn Occam on TypingMind?

Because you install it once and use it with any model. Learn Occam 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 Learn Occam in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Li-Evan/Bloom/tree/main/skills/learn-occam. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Learn Occam?

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 Learn Occam?

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

Is the Learn Occam AI skill free?

Yes. It is published on GitHub by Li-Evan 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

简易策略（learn-occam）

何时用

流程

第一步：先找"既定问题"

第二步：现有知识能不能搞定

第三步：贬值速度 + ROI

第四步：探索 vs 应用（N 臂老虎机）

第五步：给结论

注意

Frequently asked questions

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