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Llm Wiki Setup

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NulightJens
llm-wiki-setup

Initialize a Karpathy-style LLM wiki (personal knowledge base / AI second brain) in a folder. Creates a CLAUDE.md schema with routing table and naming conventions, AGENTS.md mirror, raw/wiki directory structure, and index.md/log.md scaffolding — a complete working vault in one pass. Use when the user asks to "set up an LLM wiki", "create a second brain", "build a personal knowledge base", "install the Karpathy wiki pattern", "initialize a knowledge vault", or points at an empty folder and wants to turn it into an AI-maintained wiki.

Overview

PublisherNulightJens
Repositoryai-second-brain-skills
Skill namellm-wiki-setup
Stars
103
Forks
17
Bundled files
5
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by NulightJens on GitHub. Read the source before you install it.

Installation

Install the Llm Wiki Setup AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/NulightJens/ai-second-brain-skills/tree/main/llm-wiki-setup
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/NulightJens/ai-second-brain-skills.git /tmp/ai-second-brain-skills
mkdir -p .claude/skills
cp -r /tmp/ai-second-brain-skills/llm-wiki-setup .claude/skills/llm-wiki-setup
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Llm Wiki Setup in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Llm Wiki Setup on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Llm Wiki Setup is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

llm-wiki-setup

Install the Karpathy LLM wiki pattern into a folder. One pass, three questions, a working vault a beginner can use immediately.

What gets created

<vault>/
├── CLAUDE.md              # the map — routing table, schema, workflows, guardrails
├── AGENTS.md              # minimal mirror for Codex and other non-Claude agents
├── .gitignore
├── raw/                   # immutable source documents (LLM reads, never writes)
│   └── .gitkeep
└── wiki/                  # LLM-owned markdown
    ├── index.md           # catalog of every page, organized by category
    └── log.md             # chronological operation log with grep-friendly prefix

Optional additions the user may request at setup time:

  • wiki/hot.md — 500-char rolling buffer for fast recent-context lookup (executive-assistant use cases)
  • Nested wiki subfolders: wiki/entities/, wiki/concepts/, wiki/sources/, wiki/analyses/

Setup flow

Ask these three questions in a single message:

  1. Vault path? Absolute path. Will be created if it doesn't exist.
  2. Flat or nested wiki? Flat is the default (Karpathy's preference — cleaner, grep-friendly). Nested adds subfolders for larger or mixed-topic vaults.
  3. Include hot cache? Optional wiki/hot.md rolling buffer. Default: no.

Build procedure

  1. Safety check. If <vault>/CLAUDE.md or <vault>/wiki/ already exists, stop and ask the user — do not overwrite without explicit confirmation.
  2. Create directories. <vault>, <vault>/raw/, <vault>/wiki/. For nested layout, also create wiki/entities/, wiki/concepts/, wiki/sources/, wiki/analyses/.
  3. Install the schema. Copy templates/CLAUDE.md → <vault>/CLAUDE.md, replacing {{LAYOUT}} with flat or nested. Copy templates/AGENTS.md → <vault>/AGENTS.md.
  4. Scaffold the wiki. Copy templates/index.md → <vault>/wiki/index.md. Copy templates/log.md → <vault>/wiki/log.md, replacing {{DATE}} with today's date (YYYY-MM-DD) and {{LAYOUT}} with the layout choice.
  5. Optional extras. If hot cache was requested, create <vault>/wiki/hot.md with a header comment only. Create <vault>/raw/.gitkeep.
  6. Gitignore. If <vault>/.gitignore does not exist, copy templates/gitignore → <vault>/.gitignore. If it already exists, append any missing lines from the template — do not overwrite.
  7. Git init. If <vault> is not already a git repo: git init && git add . && git commit -m "chore: initialize LLM wiki". If it is already a git repo with a clean working tree, stage the new files and commit them separately as chore: add LLM wiki scaffold. If the repo has uncommitted changes, stop and ask the user how to proceed.
  8. Verify. Read <vault>/CLAUDE.md back and confirm the {{LAYOUT}} placeholder was replaced. If it wasn't, fix it and amend (or create a follow-up commit).

Report to user

On completion, print exactly:

LLM wiki initialized at <vault>

Layout: <flat|nested>
Hot cache: <yes|no>

Next steps:
1. Drop a source into <vault>/raw/ (PDF, markdown, web clip, transcript)
2. Open Claude Code in the vault:  cd <vault> && claude
3. Say: "Ingest the new source I just added to raw/"

Claude will read it, extract entities and concepts, write wiki pages,
update wiki/index.md, and append to wiki/log.md. A substantive source
typically touches 10–15 pages — that is normal and the whole point.

For periodic gap-filling research, install and run the wiki-self-heal skill.

Notes

  • The CLAUDE.md template is the hero file. It encodes the three-layer architecture, the routing table, naming conventions, workflows, and guardrails. Beginners read it to understand the system — it's also documentation, not just instructions for the LLM. Keep it intact during the copy; only {{LAYOUT}} is substituted.
  • The AGENTS.md template is a minimal mirror for OpenAI Codex and other non-Claude agents that don't read CLAUDE.md.
  • Never overwrite existing files without explicit user confirmation (steps 1 and 6).
  • The vault is just a git repo of markdown files. No database, no embeddings, no vector store. That is intentional — naming conventions and wiki/index.md replace RAG infrastructure at this scale.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Llm Wiki Setup AI skill do?

Initialize a Karpathy-style LLM wiki (personal knowledge base / AI second brain) in a folder. Creates a CLAUDE.md schema with routing table and naming conventions, AGENTS.md mirror, raw/wiki directory structure, and index.md/log.md scaffolding — a complete working vault in one pass. Use when the user asks to "set up an LLM wiki", "create a second brain", "build a personal knowledge base", "install the Karpathy wiki pattern", "initialize a knowledge vault", or points at an empty folder and wants to turn it into an AI-maintained wiki.

Why use Llm Wiki Setup on TypingMind?

Because you install it once and use it with any model. Llm Wiki Setup is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Llm Wiki Setup in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/NulightJens/ai-second-brain-skills/tree/main/llm-wiki-setup. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Llm Wiki Setup?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Llm Wiki Setup?

As many as you like. As long as a model supports skills, you can use Llm Wiki Setup with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Llm Wiki Setup AI skill free?

Yes. It is published on GitHub by NulightJens under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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