LLM Wiki Skill
Build and maintain a personal knowledge base using Karpathy's llm-wiki methodology across Claude Code, Codex, and OpenClaw agents.
- Skill ID
- reason-machines/trending-skills/llm-wiki-skill
- Publisher
- reason-machines
- Repository
- trending-skills
- Installs
- 0
- Files
- 1
- Synced
- Sep 23, 2026
Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.
reason-machines/trending-skills/llm-wiki-skillInstalls these files- SKILL.md
What this skill tells the agent
llm-wiki-skill — Multi-Platform Knowledge Base Builder
Skill by ara.so — Daily 2026 Skills collection.
Build a persistent, interlinked personal knowledge base from URLs, PDFs, markdown files, and raw text. Based on Karpathy's llm-wiki methodology: knowledge is compiled once and maintained, not re-derived from raw docs on every query.
What It Does
- Ingests articles, tweets, PDFs, YouTube transcripts, WeChat posts, and plain text
- Routes each source type to the best extraction tool automatically
- Generates structured wiki pages with
[[bidirectional links]] - Produces entity pages, topic pages, source summaries, and comparisons
- Outputs Obsidian-compatible local markdown files
- Detects orphaned pages, broken links, and contradictions via health checks
Installation
Recommended: Let Your Agent Install It
Give your agent the repo URL and ask it to install for your platform:
https://github.com/sdyckjq-lab/llm-wiki-skillManual Installation
Clone the repo anywhere, then run the installer for your platform:
# Claude Code
bash install.sh --platform claude
# Codex
bash install.sh --platform codex
# OpenClaw
bash install.sh --platform openclaw
# Auto-detect (only if one platform directory exists)
bash install.sh --platform auto
# Custom target directory (OpenClaw non-standard path)
bash install.sh --platform openclaw --target-dir /path/to/your/skillsDefault Install Locations
| Platform | Path |
|---|---|
| Claude Code | ~/.claude/skills/llm-wiki |
| Codex | ~/.codex/skills/llm-wiki |
| OpenClaw | ~/.openclaw/skills/llm-wiki |
Legacy Claude Setup (existing users)
bash setup.sh
# This is now a compatibility shim for the unified installerPrerequisites
# Check Chrome debug mode is running (needed for web extraction)
google-chrome --remote-debugging-port=9222 &
# Check uv is installed (needed for WeChat + YouTube extraction)
uv --version
# Install bun OR npm (one is enough for web extraction deps)
curl -fsSL https://bun.sh/install | bash
# OR: npm is already available in most environmentsPlatform Entry Points
After installation, read the platform-specific instructions:
- Claude Code:
platforms/claude/CLAUDE.md - Codex:
platforms/codex/AGENTS.md - OpenClaw:
platforms/openclaw/README.md
Knowledge Base Structure
your-wiki/
├── raw/ # Immutable source material
│ ├── articles/ # Web articles
│ ├── tweets/ # X/Twitter
│ ├── wechat/ # WeChat posts
│ ├── xiaohongshu/ # Xiaohongshu (manual paste only)
│ ├── zhihu/ # Zhihu
│ ├── pdfs/ # PDFs
│ ├── notes/ # Notes
│ └── assets/ # Images, attachments
├── wiki/ # AI-generated knowledge base
│ ├── entities/ # People, concepts, tools
│ ├── topics/ # Topic pages
│ ├── sources/ # Source summaries
│ ├── comparisons/ # Side-by-side analysis
│ └── synthesis/ # Cross-source synthesis
├── index.md # Master index
├── log.md # Operation log
└── .wiki-schema.md # ConfigCore Workflows
Initialize a New Knowledge Base
# Ask your agent:
"Create a new knowledge base at ~/my-wiki"
# The agent will scaffold the directory structure,
# generate index.md, log.md, and .wiki-schema.mdIngest a Web Article
# Agent command pattern:
"Add this article to my wiki: https://example.com/article"
# Under the hood, the agent routes to baoyu-url-to-markdown:
npx baoyu-url-to-markdown https://example.com/article > raw/articles/article-slug.mdIngest a YouTube Video
# Agent command pattern:
"Digest this YouTube video into my knowledge base: https://youtube.com/watch?v=abc123"
# Uses youtube-transcript via uv:
uvx youtube-transcript https://youtube.com/watch?v=abc123 > raw/articles/video-slug.mdIngest a WeChat Article
# Agent command pattern:
"Add this WeChat article to my wiki: https://mp.weixin.qq.com/s/..."
# Uses wechat-article-to-markdown via uv:
uvx wechat-article-to-markdown https://mp.weixin.qq.com/s/... > raw/wechat/article-slug.mdIngest a PDF
# Agent command pattern:
"Process this PDF into my wiki: /path/to/paper.pdf"
# OR drag a file into the chat
# No external tool needed — goes directly into main pipeline:
cp /path/to/paper.pdf raw/pdfs/paper.pdfIngest Raw Text or Notes
# Just paste text to your agent:
"Add these notes to my wiki: [paste content]"
# Agent writes directly to:
echo "your content" > raw/notes/note-slug.mdBatch Process a Folder
# Agent command pattern:
"Process all files in ~/Downloads/research into my wiki"
# Agent iterates over files and routes each by type
for f in ~/Downloads/research/*; do
# agent determines type and processes accordingly
doneHealth Check
# Agent command pattern:
"Run a health check on my knowledge base"
# Agent checks for:
# - Orphaned pages (no incoming links)
# - Broken [[wiki links]]
# - Contradictory information across pages
# - Missing source summariesSource Routing Reference
| Source Type | Tool Used | Requires |
|---|---|---|
| Web articles | baoyu-url-to-markdown | Chrome debug mode |
| X/Twitter | baoyu-url-to-markdown | Chrome debug mode + X login |
| Zhihu | baoyu-url-to-markdown | Chrome debug mode |
wechat-article-to-markdown | uv | |
| YouTube | youtube-transcript | uv |
| Xiaohongshu | Manual paste | Nothing |
| PDF / Markdown / Text | Direct pipeline | Nothing |
Source registry lives at: scripts/source-registry.tsv Routing logic lives at: scripts/source-registry.sh
Wiki Page Conventions
Entity Page (wiki/entities/andrej-karpathy.md)
# Andrej Karpathy
## Overview
Former OpenAI/Tesla researcher, creator of llm-wiki methodology.
## Key Ideas
- [[llm-wiki]] — compile knowledge once, maintain over time
- [[nanoGPT]] — minimal GPT implementation for education
## Sources
- [[sources/llm-wiki-gist-2024]]
- [[sources/karpathy-interview-2023]]
## Related
- [[topics/language-models]]
- [[entities/openai]]Topic Page (wiki/topics/retrieval-augmented-generation.md)
# Retrieval-Augmented Generation
## Summary
...
## Key Entities
- [[entities/langchain]]
- [[entities/llamaindex]]
## Comparisons
- [[comparisons/rag-vs-finetuning]]
## Sources
- [[sources/rag-paper-2020]]Source Summary (wiki/sources/article-slug.md)
# Source: Article Title
- **URL**: https://example.com/article
- **Date ingested**: 2026-04-10
- **Type**: web article
## Key Points
1. ...
2. ...
## Entities Mentioned
- [[entities/...]]
## Raw**: [[raw/articles/article-slug]]Troubleshooting
Chrome / Web Extraction Fails
# Start Chrome with remote debugging enabled
google-chrome --remote-debugging-port=9222 --no-first-run &
# Verify it's running
curl http://localhost:9222/json/version
# For X/Twitter: make sure you're logged in on that Chrome session
# Then retry the extractionWeChat or YouTube Extraction Fails
# Install uv if missing
curl -LsSf https://astral.sh/uv/install.sh | sh
source $HOME/.cargo/env
# Re-run installer to pick up uv
bash install.sh --platform claude # or your platform
# Verify uv tools work
uvx youtube-transcript --help
uvx wechat-article-to-markdown --helpbun/npm Dependency Install Fails
# The installer auto-selects bun or npm — check which is available
which bun && echo "bun found"
which npm && echo "npm found"
# Manually install web extraction deps with npm
npm install -g baoyu-url-to-markdownCodex Legacy Path Compatibility
# Old path still supported automatically:
~/.Codex/skills # capital C — installer handles bothMore from reason-machines
Use this skill in a project
Open any RiverX project, search the Skills panel for reason-machines/trending-skills/llm-wiki-skill, and install it in one click.
