by IssacW228 · Agent Tool · ★ 179
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git clone https://github.com/IssacW228/student-llm-wiki.git
Taken from the project's README on GitHub.
None of the 42 rules matched — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against 42 published rules built on the SlowMist agent-security taxonomy, refreshed every 8 hours.
The quality score combines nine heuristic checks of the repo and its README: completeness, clarity, specificity, examples, structure, agent readiness, step-by-step content, instruction quality and security notes. It rates how well the project explains itself to an agent, not the code.
| Stars | 179 |
| Forks | 5 |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 66/100 |
| Last Updated | 2026-06-16 |
| Created | 2026-06-01 |
| Platforms | claude-code |
| Est. Tokens | ~11k |
📚 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 文件夹,AI 自动帮你整理成结构化的 wiki 笔记,存在 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.
These tools work well together with student-llm-wiki for enhanced workflows:
Looking for a student-llm-wiki alternative? If you're comparing student-llm-wiki with other agent tool tools, these 6 projects are the closest alternatives on Agent Skills Hub — ranked by topic overlap, star count, and community traction.
The local-first LLM Wiki: open-source knowledge graph builder, RAG knowledge base, and agent memory store. Bui
Andrej Karpathy's LLM Wiki pattern as a skill & Claude Code plugin — turn accumulated sources into a self-main
Turn your markdown vault into a compounding knowledge wiki (Karpathy inspired). Six agent skills - knowledge g
Local-first AI PKM for coding conversations: import Claude Code/Cursor/Codex, distill notes, semantic search,
Read, write, search, and surgically edit Obsidian vault notes, tags, and frontmatter via MCP. STDIO or Streama
LLM-powered knowledge base from your Claude Code, Codex CLI, Copilot, Cursor & Gemini sessions. Karpathy's LLM
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Grades come from a rule-based scan built on the SlowMist agent-security taxonomy: 42 published rules, covering credential harvesting, data exfiltration, curl | sh installers and more. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: