MCPInstall

llm-wiki-skill

Build and maintain a personal knowledge base using Karpathy's llm-wiki methodology across Claude Code, Codex, and OpenClaw agents.

Installs
568
Last 24h
—
Trending rank
—
Security
Not audited

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/reason-machines/trending-skills --skill llm-wiki-skill
  1. 01

    Install

    Run the command in your project. The CLI asks which agents to install for.

  2. 02

    Describe the task

    Ask your agent for something this skill covers. It loads llm-wiki-skill automatically when relevant.

  3. 03

    Review the result

    The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

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-skill

Manual 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/skills

Default Install Locations

PlatformPath
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 installer

Prerequisites

# 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 environments

Platform 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         # Config

Core 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.md

Ingest 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.md

Ingest 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.md

Ingest 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.md

Ingest 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.pdf

Ingest 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.md

Batch 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
done

Health 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 summaries

Source Routing Reference

Source TypeTool UsedRequires
Web articlesbaoyu-url-to-markdownChrome debug mode
X/Twitterbaoyu-url-to-markdownChrome debug mode + X login
Zhihubaoyu-url-to-markdownChrome debug mode
WeChatwechat-article-to-markdownuv
YouTubeyoutube-transcriptuv
XiaohongshuManual pasteNothing
PDF / Markdown / TextDirect pipelineNothing

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 extraction

WeChat 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 --help

bun/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-markdown

Codex Legacy Path Compatibility

# Old path still supported automatically:
~/.Codex/skills  # capital C — installer handles both
~/.codex/skills  # lowercase — new default

Agent Can't Find Installed Skill

# Verify install location for your platform
ls ~/.claude/skills/llm-wiki/   # Claude Code
ls ~/.codex/skills/llm-wiki/    # Codex
ls ~/.openclaw/skills/llm-wiki/ # OpenClaw

# Re-run installer if directory is missing
bash install.sh --platform <your-platform>

Source Registry Lookup

# Check registered sources and routing
cat scripts/source-registry.tsv

# Test routing for a URL
bash scripts/source-registry.sh route "https://mp.weixin.qq.com/s/example"

Key Design Principles

  1. Compile once, maintain — wiki pages are living documents, not ephemeral answers
  2. Bidirectional links — every entity and topic links to related nodes with [[name]]
  3. Immutable raw — source files in raw/ are never modified after ingestion
  4. Graceful degradation — if a tool fails, agent prompts for manual paste instead of crashing
  5. Platform-agnostic — same knowledge base works across all supported agents
  6. Obsidian-compatible — open your-wiki/ directly in Obsidian at any time

Quick Reference for Agents

Initialize wiki:     "Create a new wiki at <path>"
Add URL:             "Add <url> to my wiki"
Add file:            "Process <file path> into my wiki"
Add text:            "Add these notes to my wiki: <text>"
Batch process:       "Process all files in <folder> into my wiki"
Health check:        "Check my wiki for broken links and orphans"
Find information:    "What does my wiki say about <topic>"
Update a page:       "Update the [[entity]] page with new info from <source>"

FAQ

What does the llm-wiki-skill skill do?

Build and maintain a personal knowledge base using Karpathy's llm-wiki methodology across Claude Code, Codex, and OpenClaw agents.

How do I install llm-wiki-skill?

Run npx skills add https://github.com/reason-machines/trending-skills --skill llm-wiki-skill in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/llm-wiki-skill/ (personal) or .claude/skills/llm-wiki-skill/ (project).

Which AI agents can use llm-wiki-skill?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is llm-wiki-skill safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains llm-wiki-skill?

It is published by reason-machines in reason-machines/trending-skills. It has 568 recorded installs.

More from reason-machines/trending-skills

View all →

openclaw-control-center

reason-machines/trending-skills

Local-first, security-first control center for OpenClaw agents — visibility dashboard with readonly defaults, token attribution, collaboration tracing, and safe write operations.

Data & Databases4.4K installs

inkos-multi-agent-novel-writing

reason-machines/trending-skills

Multi-agent CLI system for autonomous novel writing, auditing, and revision with human review gates

Docs & Writing2.8K installs

claude-hud-statusline

reason-machines/trending-skills

A Claude Code plugin that displays a real-time HUD showing context usage, active tools, running agents, and todo progress in your terminal statusline.

understand-anything-knowledge-graph

reason-machines/trending-skills

Turn any codebase into an interactive knowledge graph using Claude Code skills — explore, search, and ask questions about any project visually.

agency-agents-ai-specialists

reason-machines/trending-skills

A collection of specialized AI agent personalities for Claude Code, Cursor, Aider, Windsurf, and other AI coding tools — covering engineering, design, marketing, sales, and more.

AI & Agents2.1K installs

agent-browser-automation

reason-machines/trending-skills

Headless browser automation CLI for AI agents using native Rust binary with Chrome DevTools Protocol

Popular ai & agents skills

View category →

google-agents-cli-publish

google/agents-cli

This skill should be used when the user wants to "publish an agent", "publish my ADK agent", "register an agent with Gemini", "publish to Gemini" (formerly Gemini Enterprise), or needs guidance on the agents-cli publish gemini command. Also use when the user wants to "manage agents in Agent Registry", "list/update/delete registered agents", or "register an MCP server". Covers ADK vs A2A registration modes, programmatic and interactive usage, flag reference, auto-detection from deployment metadata, Agent Registry fleet management, and troubleshooting. Part of the agents-cli skills suite. Do NOT use for deployment (use google-agents-cli-deploy).

AI & Agents513.9K installs

google-agents-cli-eval

google/agents-cli

This skill should be used when the user wants to "run an evaluation", "evaluate my agent", "evaluate my ADK agent", "write an eval dataset", "analyze eval failures", "compare eval results", "optimize agent", or needs guidance on the Gemini platform eval methodology and the Quality Flywheel. Covers eval metrics, dataset schema, LLM-as-judge scoring, and common failure causes. Applies to any agents-cli project, whatever framework the agent is written in. Do NOT use for agent API code patterns (ADK: use google-agents-cli-adk-code), deployment (use google-agents-cli-deploy), or project scaffolding (use google-agents-cli-scaffold).

AI & Agents513.5K installs

skill-creator

anthropics/skills

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

OfficialAI & Agents416.4K installs

codex-pet

prime-skills/runcomfy-agent-skills

Codex Pet generator on RunComfy. Build a Codex-compatible Codex Pet spritesheet.webp + pet.json from a single reference image, drop it into ${CODEXHOME:-$HOME/.codex}/pets/ / and Codex picks it up as a custom Codex Pet next to the 8 built-ins. This skill produces the exact Codex Pet atlas Codex expects (1536x1872 PNG/WebP, 8 cols x 9 rows, 192x208 cells, 9 animation states — idle, running-right, running-left, waving, jumping, failed, waiting, running, review). Calls OpenAI GPT Image 2 edit ONCE via the local RunComfy CLI as runcomfy run openai/gpt-image-2/edit to produce a canonical Codex Pet pose, then assembles all 9 animation rows programmatically with ImageMagick micro-transforms — no Codex Pro, no $imagegen, no OPENAIAPIKEY required, only RUNCOMFYTOKEN. Triggers on "codex pet", "create codex pet", "make codex pet", "hatch codex pet", "/hatch image", "desktop pet codex", "codex pets", "spritesheet.webp", or any explicit ask to build a custom pet for OpenAI Codex.

AI & Agents402.1K installs

full-output-enforcement

leonxlnx/taste-skill

Overrides default LLM truncation behavior. Enforces complete code generation, bans placeholder patterns, and handles token-limit splits cleanly. Apply to any task requiring exhaustive, unabridged output.

AI & Agents401K installs

executing-plans

obra/superpowers

Use when executing an implementation plan in the current session as the implementer yourself — your human partner chose inline execution, or no subagent tool is available

AI & Agents245.7K installs