agentmods.dev

learn-crossover

learn-crossover is a skill for Claude Code from Li-Evan/Bloom. It costs 141 tokens per session (1,089 once invoked), scanned A, original, MIT.

A Chinese-language teaching method for explaining an unfamiliar concept through ideas the learner already knows. It matches the new concept's structure to confirmed knowledge instead of assuming the learner's background.

In plain words
What is it for?
Use it when teaching a technology, algorithm, theory, or field, especially when the learner feels unfamiliar with or overwhelmed by the topic.
Why use it?
It makes difficult subjects easier to approach by separating familiar patterns from the genuinely new parts.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the bloom plugin — 7 skills shipped together

not rated 303repo +8 18d ago A scan 141 tokens original MIT

Good fit Use it when teaching a technology, algorithm, theory, or field, especially when the learner feels unfamiliar with or overwhelmed by the topic.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/li-evan/bloom/learn-crossover
View source ↗ Li-Evan/Bloom bloomtutor.app
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add Li-Evan/Bloom --skill learn-crossover
Clone the repo
git clone --depth 1 https://github.com/Li-Evan/Bloom

Made for: Claude Code.

Or install bloom, the plugin that ships this one along with the rest of its 7 skills.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for learn-crossover

README.md
[![agentmods](https://agentmods.dev/badge/skills/li-evan/bloom/learn-crossover/github.svg)](https://agentmods.dev/skills/li-evan/bloom/learn-crossover)
Your own site
<a href="https://agentmods.dev/skills/li-evan/bloom/learn-crossover"><img src="https://agentmods.dev/badge/skills/li-evan/bloom/learn-crossover/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for learn-crossover

Your own site · 80×15
<a href="https://agentmods.dev/skills/li-evan/bloom/learn-crossover"><img src="https://agentmods.dev/badge/skills/li-evan/bloom/learn-crossover.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 141 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,089 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00141 $0.01089
Opus 5.5 $0.00056 $0.00436
Sonnet 5.5 $0.00028 $0.00218
Haiku 4.5 $0.00014 $0.00109

Measured 2mo ago against content hash 3e9359a262e8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

learn-crossover scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/learn-crossover/SKILL.md · 54 lines

What it actually says

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。

何时用

用户在学 / 接触一个新概念 X（新技术、新算法、新理论、新领域……），尤其觉得"陌生 / 有点难"的时候。难，往往不是智商问题，是它相对用户还存在"没接上的旧知识"。

流程

第一步：抓住 X 的本质结构（不堆术语）

用一两句话说清 X 到底在干什么——它的核心机制 / 结构是什么。剥掉术语外壳，留下"它本质是一个 ___"。只有先拿到结构，才能去匹配用户学过的东西。

第二步：弄清用户已经会什么

主动询问，建立"用户已掌握知识"的清单：

  • 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）

  1. 🎁 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"。
  2. 🔗 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。
  3. 🧩 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

X 体现了哪个反复出现的底层模式？（分治、自举 / bootstrap、阻尼-负反馈、探索 vs 应用、量变质变、控制变量、状态机……）。告诉用户"这个模式你在 、 也见过"，把 X 挂到他的元知识网上。

第五步：落点

一句话收尾，降低学习恐惧 + 指明剩下要新学的最小部分：

"所以 X 你已经会了 ___ 部分，真正全新、需要从头学的只有 ___。"

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。（最常见的翻车点：把材料作者的背景错安到学习者头上，整段跨界作废。）

  • 宁可多举具体例子（案例驱动），别给抽象框架。
  • 结构对应要给到字段级映射表，不要泛泛说"它们很像"。
  • 不确定某个跨界连接是否成立时，标注"这是个待验证的类比"——提出假说，允许被推翻。
  • 同族 skill：要"该不该学"用 learn-occam，要"系统建图"用 learn-graph，要"动手迭代"用 learn-prototype，要"自查懂没懂"用 learn-feynman。
Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 54 lines · 141 tokens per session scan A 3e9359a262e8

Subscribe to this mod's changes

learn-crossover is a skill published in the GitHub repository Li-Evan/Bloom (303 stars, last pushed 18d ago), licensed MIT. It adds 141 tokens to every session and 1,089 once invoked, about $0.0006 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Claude CodeLearning and teachingagent-skillsai-tutorchineseclaude-skill
Related

learn-crossover compared with skills from other repositories

learn-crossover next to 6 skills from other repositories
ModTypeStarsLast pushLicenceScanTokensWorks with
learn-crossoverLi-Evan/BloomSkill30318d agoMITA141Claude Code
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ai-pm-atom-lessonuimarch123-arch/ai-pm-atom-lessonSkill54mo agoMITA286Claude Code, Codex
deeptutor-cliHKUDS/DeepTutorSkill55kyesterdayApache-2.0A42Claude Code, Codex
scaffold-exercisesvinvcn/mattpocock-skills-zh-CNSkill5.6k9d agoMITA46Claude Code, Codex
learning-notes-automationchubbyguan/chubbyskillsSkill1.3k23d agoMITA58Claude Code, Codex
scaffold-exercisesdevcxl/mattpocock-skills-zhSkill5303d agoMITA51Claude Code, Codex