learn-feynman SKILL.md skillA

learn-feynman from li-evan/bloom is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.

Install it, pinned
mdr add li-evan/bloom/learn-feynman@git:20260602.38b4fc8

Pins git:20260602.38b4fc8 in mdr.lock. Pin the fingerprint instead.

Audit grade
A, 17 of 17 checks passed
Kind
SKILL.md skill
Repository
li-evan/bloom
Path
skills/learn-feynman/SKILL.md
Versions recorded
1
Latest version
git:20260602.38b4fc8, committed Jun 2, 2026
Size
2,430 bytes
Repository stars
302
License
MIT

当用户学完一个东西想自查是否真懂、或觉得「好像懂了」但不确定时使用。用「费曼学习法」让他用自己的话把概念讲出来,你扮好奇学生专挑他含糊/跳过的地方追问,把「讲不顺的模糊处」揪出来作为没真懂的漏洞,定位是缺前置知识还是没想透,判断理解是否闭环。触发场景:我学完了考考我、自查一下、我好像懂了、我讲讲你看对不对、检验我的理解、这个我真懂了吗。.

Collected from public GitHub. Every version is saved exactly as it was and never changes. Install it at an exact version with the mdr tool, and every file is checked before it reaches your agent. The main file is checked against the SHA-256 fingerprint recorded here, and the others against the fingerprints GitHub keeps for its source commit. The automatic checks below grade the latest version, and the same checks always give the same file the same grade.

What the file says

# 费曼学习法(learn-feynman)

> 核心信条:**能简单地教会别人,才算真懂。** 讲的时候被简化或跳过的地方,正是"我以为我懂了"的幻觉核心点。

## 何时用

用户学完一个东西想验真伪,或隐约觉得"好像懂了但不踏实"。也是"重输入轻输出"的一次强制输出。

## 流程(考官 / 学生模式:用户讲,你挑漏洞)

### 第一步:让用户讲

请他**用自己的话、把你当外行**,把概念讲一遍。别让他背定义——要他解释、打比方。

### 第二步:扮好奇学生追问

专挑他**含糊带过、用术语糊弄、跳过的环节**追问:"为什么?""那这个是怎么来的?""举个例子?"命中他答不上来或开始绕的地方。

### 第三步:揪出"模糊处"= 漏洞

明确指出哪几处他没真懂(不是责备,是定位)。这些就是幻觉核心点。

### 第四步:定位漏洞性质

每个漏洞是:**① 缺前置知识**(→转 `learn-graph` 定位 / `learn-crossover` 看是否其实已会)还是 **② 有料但没想透**(→当场再讲一轮,直到讲顺)?

### 第五步:判断闭环

能顺畅讲通、追问不倒 = 闭环。否则明确指出还差哪一环。

## 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。

- 别太快放水——用户讲得顺也要追问一两个深的,确认不是表面流畅。
- 目标是定位漏洞,不是羞辱;找到漏洞是好事,说明知道往哪补。
- 同族 skill:`learn-occam` `learn-crossover` `learn-graph` `learn-prototype`。

Read the whole file at its exact version.

How to install

The exact contents, by fingerprint
mdr add li-evan/bloom/learn-feynman@sha256:8c6090cd3183dc5b

The line at the top of this page pins the label git:20260602.38b4fc8, which is what most people want. This one pins the sha256 fingerprint of the contents instead, so it survives a label being moved. Either way the exact version is written to mdr.lock, and mdr install downloads and checks those contents again, so it installs them exactly or stops with an error.

Badge

mdr badge

[![mdr](https://markdownregistry.com/badge/art_4xmskvye36iijgto.svg)](https://markdownregistry.com/a/art_4xmskvye36iijgto)

1 badge image fetches in 30 days. What the badge shows.

Versions

The registry has recorded 1 version of this file, committed on Jun 2, 2026.

versioncommittedcommitsizeaudit
git:20260602.38b4fc8 latest2026-06-02 38b4fc8 2,430 BA view

Audit of the latest version

A  17 of 17 checks passed. Fixed automatic checks with no AI involved, so the same checks give the same answer every run.
  • pass: Frontmatter block present
  • pass: Frontmatter declares a name
  • pass: Frontmatter declares a description
  • pass: Size between 200 bytes and 200 KB (2430 bytes)
  • pass: No zero-width or bidi control characters
  • pass: No instruction hidden inside an HTML comment
  • pass: No link to an exfiltration or paste host
  • pass: No credential-shaped string
  • pass: No instruction to send local credentials anywhere
  • pass: No text hidden with inline styles
  • pass: No prompt-injection phrasing
  • pass: No curl or wget piped into a shell
  • pass: No recursive delete of root, home or parent
  • pass: No instruction to read or print local credentials
  • pass: No base64 blob over 200 characters
  • pass: No link to a raw IP address
  • pass: No script tag

Source

GitHub

li-evan/bloom · 302 stars · license MIT · pushed 2026-10-20 · branch main

API

GET https://markdownregistry.com/api/v1/artifacts/art_4xmskvye36iijgto
GET https://markdownregistry.com/api/v1/resolve?ref=li-evan/bloom/learn-feynman
GET https://markdownregistry.com/api/v1/blob/8c6090cd3183dc5b8c58e671b0f327d7ca0c0bcb05b36130de2ebe62cdd0a38e

Your AI assistant does the legwork. You hear about the deals worth your word. Hand yours the standing instructions at modelranch.com and it joins the network that reads files like this one.

Guides: the SKILL.md format and its required fields · what to check before you install a skill · how to pin a skill to an exact version · where to find agent skills · keeping a team on the same skills · which agent file does what.

More from li-evan/bloom

bloom-tutor SKILL.md skill
li-evan/bloom · skills/bloom-tutor/SKILL.md · Use when 用户想以一对一苏格拉底导师的方式系统学习一个课题——开一门新课、推进课题的下一篇、提交学习反馈或说「我读完了」、或整理/查看学习日志。基于 Bloom 2 Sigma…
git:20260607.9ee2aaf · audit A · 302 stars
learn-crossover SKILL.md skill
li-evan/bloom · skills/learn-crossover/SKILL.md · 当用户学习或接触一个新概念/新技术/新算法/新领域时使用(尤其感到陌生或有点难时)。用「跨界原则」拿用户已掌握的知识快速撬动新知识——指出他其实已经学过的同一个东西(换了名字)、结构同构的旧知识、能解释新知识的已有知识,并点出新概念体现的跨…
git:20260602.38b4fc8 · audit A · 302 stars
learn-deep SKILL.md skill
li-evan/bloom · skills/learn-deep/SKILL.md · 用户学任何新概念/新技术/新理论的默认深度入口——一次性用五个视角把概念讲透并帮他选深入方向:crossover 用已会的撬动、occam 框定该学多深、graph 建知识地图、prototype 最小原型迭代、feynman…
git:20260602.38b4fc8 · audit A · 302 stars
learn-graph SKILL.md skill
li-evan/bloom · skills/learn-graph/SKILL.md · 当用户要系统学一个新领域、不知道从哪入手、或担心「学得不够系统」时使用。用「知识图谱学习法」和用户一起构建该领域的概念/用途/父子节点图谱(自己建图的过程本身就是学习),标出复用价值最高的节点和「从常识就能入门的点」,给出有效学习路径并回答…
git:20260602.38b4fc8 · audit A · 302 stars
learn-occam SKILL.md skill
li-evan/bloom · skills/learn-occam/SKILL.md · 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 /…
git:20260602.38b4fc8 · audit A · 302 stars
learn-prototype SKILL.md skill
li-evan/bloom · skills/learn-prototype/SKILL.md · 当用户要做/研究一个东西、想提升某个技能、或觉得某个产出不够好想改进时使用。用「改良主义」先逼出一个最垃圾但能跑的原型,再引导他自己洞察缺陷、提出问题,提改良假说→实践检验→迭代,信奉「洞察缺陷 > 如何优化 >…
git:20260602.38b4fc8 · audit A · 302 stars

Every file in li-evan/bloom

Browse by kind, by grade A, or by owner.