student-llm-wiki

Name: student-llm-wiki
Author: IssacW228

Pending

📚 Student LLM Wiki — AI-compiled knowledge base for university students. Drop course slides, get a persistent interlinked wiki. Feynman review, exam prep, confidence decay, cross-course connections. Based on Karpathy's LLM Wiki pattern. Works with Claude Cowork / Claude Code / Claudian + Obsidian.学生大语言模型维基百科——专为大学生打造的AI编译知识库。

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Installation

# Add to your Claude Code skills
git clone https://github.com/IssacW228/student-llm-wiki

Getting Started

Guides for using ide extensions skills like student-llm-wiki.

README.md

Frequently Asked Questions

What is student-llm-wiki?

student-llm-wiki is an open-source ide extensions skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by IssacW228. 📚 Student LLM Wiki — AI-compiled knowledge base for university students. Drop course slides, get a persistent interlinked wiki. Feynman review, exam prep, confidence decay, cross-course connections. Based on Karpathy's LLM Wiki pattern. Works with Claude Cowork / Claude Code / Claudian + Obsidian.学生大语言模型维基百科——专为大学生打造的AI编译知识库。. It has 178 GitHub stars.

Is student-llm-wiki safe to use?

student-llm-wiki's catalog security scan is still queued. You can run an instant dependency and prompt-injection check now with the "Scan for vulnerabilities" button above.

How do I install student-llm-wiki?

Clone the repository with "git clone https://github.com/IssacW228/student-llm-wiki" and add it to your Claude Code skills directory (see the Installation section above).

Are there alternatives to student-llm-wiki?

Yes. SkillsLLM lists many other IDE Extensions skills you can browse and compare side by side. Open the IDE Extensions category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh student-llm-wiki against similar tools.

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📚 Student LLM Wiki

用 AI 把课件变成你自己的知识库 Turn your course slides into a personal wiki with AI

中文 · English

中文

这是什么？

你把课件 PDF 丢进 raw/ 文件夹，AI 自动帮你整理成结构化的 wiki 笔记，存在 wiki/ 里。你用 Obsidian 浏览这些笔记，用 AI 工具来复习、出题、检查薄弱环节。你不需要手写任何笔记。

基于 Andrej Karpathy 的 LLM Wiki 模式。

你需要准备的东西

1. Obsidian（用来浏览笔记）

下载地址：https://obsidian.md/download
免费，支持 Windows / macOS / Linux / iOS / Android
安装后还需要在社区插件里安装 Dataview（用于首页动态面板）

2. 选一个 AI 工具（任选其一即可）

工具	适合人群	获取方式
Claude Code CLI	熟悉命令行	安装说明
Claude Code Web	不想装任何东西	claude.ai/code
Cursor	喜欢 IDE 界面	cursor.com
Trae	国内用户	trae.ai
Cowork	团队协作	参考 Cowork 文档
GitHub Copilot	已有订阅	VS Code 插件市场

3. 你的课件（PDF 或其他文本格式）

第一步：下载项目，用 Obsidian 打开

git clone https://github.com/IssacW228/student-llm-wiki.git
cd student-llm-wiki

然后打开 Obsidian → 「打开本地仓库」→ 选择 student-llm-wiki 文件夹。

必须安装 Dataview 插件：Obsidian 设置 → 社区插件 → 浏览 → 搜索 Dataview → 安装并启用。

第二步：选择你的 AI 工具并打开项目

确保已安装 Claude Code CLI 并登录
在项目目录运行：
```
claude
```
配置文件（.claude/）会自动加载，无需额外设置
直接输入命令或自然语言即可开始

打开 claude.ai/code
将此仓库连接到 Claude Code
配置文件（.claude/）自动识别，直接使用

用 Cursor 打开 student-llm-wiki 文件夹
规则文件已在 .cursor/rules/wiki.mdc，自动生效
在 Cursor 聊天框直接输入命令，无需额外配置

用 Trae 打开 student-llm-wiki 文件夹
Skills 已在 .trae/skills/，自动识别
在对话框直接输入命令

将 Cowork 项目指向 student-llm-wiki 文件夹
COWORK-INSTRUCTIONS.md 会自动加载
直接开始对话

用支持 Copilot 的编辑器打开项目文件夹
AGENTS.md 会被自动读取
直接在对话框输入命令

第三步：导入你的第一份课件

在 raw/ 下新建文件夹，用你的课程代号命名（如 raw/MATH1001/）
把课件 PDF 复制进去
在 AI 工具里输入：
```
ingest raw/MATH1001/L1.pdf
```
AI 会自动生成概念页、课程总览、来源摘要
回到 Obsidian，打开 Home.md 查看结果

同一份文件不会被重复导入（通过文件 hash 去重）。

命令速查

命令	作用
`ingest raw/XXXX/L1.pdf`	导入课件，自动生成笔记、课程总览、跨课连接记录
`lint`	检查笔记健康度：断链、孤立页、过期概念、缺失总览、术语表补全
`review XXXX`	费曼复习模式：AI 提问，你来回答
`exam-prep XXXX`	根据薄弱概念自动出练习题
`diagram ConceptName`	为某个概念页添加 Mermaid 图解（流程图/架构图/时序图等）

也可以用自然语言，比如「帮我复习这门课」或「把这个文件导入知识库」。

添加新课程

在 raw/ 下创建对应课程文件夹（如 raw/PHYS1001/）
把课件放进去
运行 ingest，课程总览页会自动创建
Home.md 首页会动态显示新课程，无需手动修改

项目结构

student-llm-wiki/
├── raw/              ← 放课件（只读，AI 不会修改这里）
│   └── XXXX/         ← 按课程分文件夹
├── wiki/             ← AI 生成的笔记（自动维护）
│   ├── concepts/         ← 概念页（每概念一页，含图解）
│   ├── courses/          ← 课程总览（ingest 时自动创建）
│   ├── sources/          ← 课件摘要
│   ├── exam-prep/        ← 练习题
│   ├── connections-log.md  ← 跨课程连接发现记录
│   ├── contradictions.md   ← 矛盾与张力追踪
│   ├── glossary.md         ← 中英术语表（自动填充）
│   ├── overview.md         ← 跨课程综述（自动更新）
│   ├── index.md            ← 总目录
│   └── hot.md              ← AI 上下文缓存（每次 session 首读）
├── Home.md           ← Obsidian 首页仪表盘
│
│   以下为 AI 工具配置文件，无需修改：
├── .claude/          ← Claude Code 配置
├── .cursor/          ← Cursor 配置
├── .trae/            ← Trae 配置
├── AGENTS.md         ← Copilot/Codex 配置
└── COWORK-INSTRUCTIONS.md  ← Cowork 配置

致谢

Andrej Karpathy's LLM Wiki — 原始模式
claude-obsidian — hot cache、manifest 去重、skill 拆分
Obsidian — 知识平台

许可证

MIT

English

What is this?

You drop course PDF slides into the raw/ folder. The AI automatically organizes them into structured wiki notes in wiki/. You browse the notes with Obsidian, and use AI tools to review, generate practice questions, and surface weak spots. You never write notes yourself.

Based on Andrej Karpathy's LLM Wiki pattern.

Prerequisites

1. Obsidian (for browsing your notes)

Download: https://obsidian.md/download
Free. Available on Windows / macOS / Linux / iOS / Android
After installing, also install the Dataview community plugin (required for the Home dashboard)

2. An AI tool (pick just one)

Tool	Best for	Get it
Claude Code CLI	Terminal users	Install guide
Claude Code Web	No install needed	claude.ai/code
Cursor	IDE-style interface	cursor.com
Trae	—	trae.ai
Cowork	Team use	See Cowork docs
GitHub Copilot	Existing subscribers	VS Code marketplace

3. Your course slides (PDF or other text formats)

Step 1: Clone the repo and open in Obsidian

git clone https://github.com/IssacW228/student-llm-wiki.git
cd student-llm-wiki

Open Obsidian → "Open folder as vault" → select the student-llm-wiki folder.

Install the Dataview plugin: Obsidian Settings → Community plugins → Browse → search Dataview → Install and enable.

Step 2: Open the project with your AI tool

Make sure Claude Code CLI is installed and you're logged in
Run in the project folder:
```
claude
```
The config folder (.claude/) is auto-detected — no extra setup needed
Type commands or plain English to get started

Go to claude.ai/code
Connect this repository to Claude Code
The .claude/ config is auto-detected — start typing commands directly

Open the student-llm-wiki folder in Cursor
Rules are pre-configured in .cursor/rules/wiki.mdc — auto-applied
Type commands in the Cursor chat panel

Open the student-llm-wiki folder in Trae
Skills are pre-configured in .trae/skills/ — auto-detected
Type commands in the chat panel

Point your Cowork project at the student-llm-wiki folder
COWORK-INSTRUCTIONS.md loads automatically
Start chatting

Open the project in an editor with Copilot support
AGENTS.md is read automatically
Type commands in the chat panel

Step 3: Ingest your first slide deck

Create a folder under raw/ named after your course (e.g. raw/MATH1001/)
Copy your PDF into that folder
In your AI tool, type:
```
ingest raw/MATH1001/L1.pdf
```
The AI generates concept pages, a course overview, and a source summary
Switch to Obsidian and open Home.md to see your new notes

The same file won't be ingested twice — files are tracked by hash.

Commands

Command	What it does
`ingest raw/XXXX/L1.pdf`	Import a slide deck — generates notes, course overview, and cross-course link records
`lint`	Check wiki health: broken links, orphan pages, stale concepts, missing overviews, glossary gaps
`review XXXX`	Feynman review mode: AI quizzes you
`exam-prep XXXX`	Auto-generate practice questions from weak concepts
`diagram ConceptName`	Add a Mermaid diagram to a concept page (flowchart / architecture / sequence / etc.)

You can also use plain English: "quiz me on this course" or "import this file into the wiki".

Adding a new course

Create a folder under raw/ for the course (e.g. raw/PHYS1001/)
Put your slides in it
Run ingest — a course overview page is created automatically
The Home.md dashboard updates dynamically — no manual edits needed

Project structure

student-llm-wiki/
├── raw/              ← Your slides (read-only — AI never modifies this)
│   └── XXXX/         ← One folder per course
├── wiki/             ← AI-generated notes (auto-maintained)
│   ├── concepts/         ← Concept pages (one per concept, with diagrams)
│   ├── courses/          ← Course overviews (auto-created on ingest)
│   ├── sources/          ← Slide summaries
│   ├── exam-prep/        ← Practice questions
│   ├── connections-log.md  ← Cross-course link discovery log
│   ├── contradictions.md   ← Contradiction & tension tracker
│   ├── glossary.md         ← Bilingual term index (auto-populated)
│   ├── overview.md         ← Cross-course synthesis (auto-updated)
│   ├── index.md            ← Master catalog
│   └── hot.md              ← AI context cache (read first each session)
├── Home.md           ← Obsidian dashboard
│
│   AI tool config — no need to touch these:
├── .claude/          ← Claude Code config
├── .cursor/          ← Cursor config
├── .trae/            ← Trae config
├── AGENTS.md         ← Copilot/Codex config
└── COWORK-INSTRUCTIONS.md  ← Cowork config

Credits

Andrej Karpathy's LLM Wiki — the original pattern
claude-obsidian — hot cache, manifest dedup, skill decomposition
Obsidian —