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AI EngineeringPython

Learn Occam

Learn Occam is an AI Engineering skill for Claude Code, published by Li-Evan in Bloom.

248 stars39 forkson Li-Evan/BloomAdded 2026/09/02+3% in starsRepository updated 2026/06/23

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Install in seconds

Install Learn Occam

Copy Learn Occam into your Claude Code skills folder. Run the command in your terminal, or review the source on GitHub before installing.

terminal

npx degit https://github.com/Li-Evan/Bloom/tree/main/skills/learn-occam ~/.claude/skills/learn-occam

Requires Node.js. Downloads this skill only — not the rest of the repository — into your Claude Code skills folder.

Without Node.js

git clone https://github.com/Li-Evan/Bloom.git

Clones the whole repository, then copy the skill’s own directory into your skills folder yourself.

In this catalog

Source file: skills/learn-occam/SKILL.md in Li-Evan/Bloom
Installs to: ~/.claude/skills/learn-occam
Collection: One of 7 skills cataloged from this repository
Category: AI Engineering — 2631 skills

What Learn Occam does

Learn Occam helps decide whether to learn something, how far to go, or whether to use existing knowledge instead. It asks for the concrete problem, checks what is already known, and returns learn, don't learn, or learn the minimum needed.

Learn Occam is cataloged under AI Engineering on DirSkills. Learn Occam comes from a repository tagged adaptive-learning, agent-skills, ai-agent, ai-tutor and bloom-2-sigma.

Documentation

README

Excerpt

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

This is the opening of the README. Read the full README on GitHub.

Frequently asked about Learn Occam

What else does Li-Evan publish alongside Learn Occam?
Learn Occam is one of 7 skills that DirSkills catalogs from Li-Evan/Bloom, the repository it ships in. Its siblings there include Bloom Tutor, Cross-Learning and Feynman Learning. Each one is a separate skill with its own page in this directory, installs the same way Learn Occam does, and is maintained by Li-Evan in that same repository. The rest of the collection is listed on the Li-Evan/Bloom page.
How does Learn Occam compare to other AI Engineering skills?
Learn Occam ranks #2320 by stars among the 2631 AI Engineering skills in this catalog. The most-starred ones next to it are Architecture Decision Records, AI-First Engineering and Agentic OS. DirSkills ranks by the star count of the repository each skill ships in, so that order reflects how popular those repositories are rather than any review of Learn Occam against them. Open each page to compare what they document and how they install.

More from Li-Evan/Bloom

Learn Occam is one of 7 skills cataloged on DirSkills from Li-Evan/Bloom.

See all 7 skills →

Bloom Tutor

Bloom Tutor uses a Chinese, one-on-one Socratic learning flow to study a topic through generated lesson files, feedback, and learning logs. Use it when starting a new subject, continuing a course, or reviewing progress.

Cross-Learning

Cross-Learning helps explain a new concept by linking it to knowledge the user already has. It is used when something feels unfamiliar or hard, to map it to known structures, analogies, and underlying patterns.

Feynman Learning

Feynman Learning helps users test whether they really understand a concept by explaining it in their own words and answering follow-up questions. Use it when someone says they “kind of get it” and wants to find the gaps.

Knowledge Graph Learning

Knowledge Graph Learning helps you build a concept-and-relationship map for a new field so you can learn it systematically. It is used when you need a starting point, a learning path, or a clear answer to how much is enough.

Learn Deep

Learn Deep helps a user understand a new concept from multiple angles: prior knowledge, depth, knowledge map, prototype, and Feynman-style checks. Use it when someone wants to learn, understand, or explain a concept before choosing a deeper direction.

Prototype Learning

Prototype Learning helps users start with a minimal version of a task, identify what is wrong with it, and improve through repeated hypothesis and testing. Use it when someone wants to make, study, or improve something and needs a structured way to begin.

More AI Engineering skills

Learn Occam is one of 2631 AI Engineering skills cataloged on DirSkills, ranked #2320 by stars among them.

Browse all AI Engineering skills →

Architecture Decision Records

Architecture Decision Records captures architectural decisions made during Claude Code sessions as structured ADRs, recording context, alternatives, and rationale. Use it when significant technical choices are made so future developers understand why the codebase is shaped the way it is.

AI-First Engineering

AI-First Engineering defines process, review, and architecture standards for teams where AI agents produce most implementation output. Use it to set ownership rules, quality gates, and evaluation criteria for agent-generated code.

Agentic OS

Agentic OS codifies a persistent multi-agent operating system architecture for Claude Code. Use it when building a multi-agent workflow with file-based memory, slash commands, and scheduled automation that survives session restarts.