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AI EngineeringPython

Learn Deep

Learn Deep 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 Deep

Copy Learn Deep 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-deep ~/.claude/skills/learn-deep

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

What Learn Deep does

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.

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

Documentation

README

Excerpt

深度学习一个概念（learn-deep）

把 learn-crossover / learn-occam / learn-graph / learn-prototype / learn-feynman 五个视角编排成一遍全景，给用户学任何概念的"一次扫透 + 选方向"。

何时用

用户说"想学 / 理解 / 搞懂 / 讲讲一个概念 X"时——这是默认入口，一次跑完五视角，用户再选深入哪个。例外：用户明确只要某一个角度（"用跨界讲""帮我建图谱""考考我"）→ 直接用对应的单个 learn-* skill，别全跑。

开跑前

先问清用户的背景：学过哪些相关领域、做过什么、熟悉哪些工具 / 理论。后面 crossover / occam / graph 都要用到。只采纳用户亲口确认学过的。

五视角执行顺序（这个弧线最顺：先降门槛 → 定深度 → 给地图 → 动手 → 验收）

1️⃣ crossover — 先用"你已经会一半"降门槛

抓住 X 的本质结构（剥术语），按三猜想给 🎁其实已学过 / 🔗结构同构（字段级对应表）/ 🧩可用已有知识解释，点出元知识。先激发信心，再谈深入。

2️⃣ occam — 框定"该学多深"

定位"既定问题"（学 X 解决什么）、现有知识够不够、X 的贬值速度与 ROI，给"够用就停 / 只学最小那块 / 值得深挖"的深度边界。不是劝退，是防止一上来过度钻。

3️⃣ graph — 给一张地图，知道 X 在哪、学到哪算够

X 在所属领域的知识图谱骨架（概念/用途/父子节点），标复用价值最高的节点 + 从常识能入门的点，给学习路径。引导用户补节点（自己建图才学得到）。

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

Frequently asked about Learn Deep

What else does Li-Evan publish alongside Learn Deep?
Learn Deep 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 Deep 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 Deep compare to other AI Engineering skills?
Learn Deep ranks #2319 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 Deep against them. Open each page to compare what they document and how they install.

More from Li-Evan/Bloom

Learn Deep 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 Occam

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.

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 Deep is one of 2631 AI Engineering skills cataloged on DirSkills, ranked #2319 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.