Cross-Learning

Cross-Learning 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

adaptive-learningagent-skillsai-agentai-tutorbloom-2-sigmachineseclaude-codeclaude-skilledtecheducationfastapilearningllmpersonalized-learningreactself-hostedsocratic-methodstudy-tool

Install in seconds

Install Cross-Learning

Copy Cross-Learning 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-crossover ~/.claude/skills/learn-crossover

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

What Cross-Learning does

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.

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

Documentation

README

Excerpt

跨界原则学习法（learn-crossover）

核心信条：真正的快速学会，其实是「你已经学过了」。 跨界匹配的是结构，不是名词。

问用户的背景：学过哪些相关领域、做过什么项目、熟悉哪些工具 / 理论
只采纳对话中用户亲口确认学过的知识
目的：找出与 X 结构同构、或能解释 X 的旧知识

拿不准就直接问「你学过 ___ 吗？」，绝不从正在讲的材料 / 文章作者背景推断用户会什么。

第三步：按"跨界三猜想"组织输出（核心）

🎁 你其实已经学过（换了名字） —— 最高优先。X 是否就是用户已知的 Y 换了个领域名称？（如导数 = 梯度 = 变化率）。命中就直接说"你已经会了，它只是改名叫 X"。
🔗 结构同构（非常像） —— 给出用户学过的 Z 与 X 的字段级对应表（A↔a、B↔b……），并明确标出哪里相同、哪里不同。铁律：不一样归不一样，但相似部分就是学习杠杆，别因为"严格不同"就不用它。
🧩 可被解释（用已有知识解释） —— 用用户已掌握的 W 把 X 讲通。

第四步：点出元知识

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

Frequently asked about Cross-Learning

What else does Li-Evan publish alongside Cross-Learning?
Cross-Learning is one of 7 skills that DirSkills catalogs from Li-Evan/Bloom, the repository it ships in. Its siblings there include Bloom Tutor, Feynman Learning and Knowledge Graph Learning. Each one is a separate skill with its own page in this directory, installs the same way Cross-Learning 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 Cross-Learning compare to other AI Engineering skills?
Cross-Learning ranks #2316 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 Cross-Learning against them. Open each page to compare what they document and how they install.