learn-graph SKILL.md skillA
learn-graph from li-evan/bloom is an agent skill: a SKILL.md folder an AI agent loads when a task calls for it.
mdr add li-evan/bloom/learn-graph@git:20260602.38b4fc8Pins 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-graph/SKILL.md- Versions recorded
- 1
- Latest version
- git:20260602.38b4fc8, committed Jun 2, 2026
- Size
- 2,725 bytes
- Repository stars
- 302
- License
- MIT
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「学到哪算够」。触发场景：系统学 X 领域、从哪开始学、学得不系统、想要 X 的全貌、规划学习路径、这个领域有多大。.
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
# 知识图谱学习法（learn-graph） > 核心信条：**自己一步步建图谱的过程，本身就是最有效的学习——不要直接套用别人给的图谱。** 绝大部分知识，都有一个从常识就能入门的点。 ## 何时用 用户要系统进入一个新领域，或焦虑"学得不够系统 / 不知何时算够"。 ## 流程（关键：和用户一起建，不是直接灌一张完整图） ### 第一步：锁定目标领域 X 和目的 用户为什么学 X？（接 `learn-occam` 的"既定问题"）目的决定图谱画到多细。 ### 第二步：构建图谱——只抓三件事 **概念/名称 · 用途 · 上下文关系（父子节点）**： - 子节点 = X 依托 / 基于什么；父节点 = X 服务于什么目标。 - **以提问引导用户一起填**（自己建图才学得到），别一次性灌完。先给骨架，留节点让他补。 ### 第三步：标注两个关键 - **复用价值**：哪些节点父节点多（像 Python）→ 优先学，回报最高。 - **入门点**：哪个节点"从常识就能入门"→ 学习路径的起点。 ### 第四步：输出学习路径 + 颗粒度 从入门点出发、沿父子关系排一条有效路径。颗粒度按需自由切换（领域图 → 细分学科图）。"学到哪算够"= 覆盖到能解决第一步那个目的的节点即可，不必学满。 ### 第五步：交接 - 拿不准某节点是不是缺前置知识 → 这正是图谱的强项，已在图上标出。 - 找到入门点要动手 → 转 `learn-prototype`（在图上找"最垃圾原型"的起点）。 ## 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。 - 强调"自己建"：多用提问让用户参与，别炫一张完美的图。 - 同族 skill：`learn-occam`(该不该学) `learn-crossover`(已会什么) `learn-prototype`(动手) `learn-feynman`(自查)。
Read the whole file at its exact version.
How to install
mdr add li-evan/bloom/learn-graph@sha256:73449bcf6083d613The 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.
[](https://markdownregistry.com/a/art_kfcef7qvn6w6dh6s)
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.
Audit of the latest version
- pass: Frontmatter block present
- pass: Frontmatter declares a name
- pass: Frontmatter declares a description
- pass: Size between 200 bytes and 200 KB (2725 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
li-evan/bloom · 302 stars · license MIT · pushed 2026-10-20 · branch main
API
GET https://markdownregistry.com/api/v1/artifacts/art_kfcef7qvn6w6dh6s GET https://markdownregistry.com/api/v1/resolve?ref=li-evan/bloom/learn-graph GET https://markdownregistry.com/api/v1/blob/73449bcf6083d6131270336c5464064f2e2180b225eae24a753121dde70e68cc
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.