AI Second Brain

A knowledge base that an AI agent builds and maintains for you, in plain markdown files you own. Everything you read, watch and save gets turned into linked wiki pages, connected to everything already there, and you can ask it questions.

This repo is the full version of the guide: the concepts, the setup, the vault template, the agent skills, the scripts, and the resources. Free, no signup, nothing to install beyond Obsidian and an agent.

Read it on the web: undefined-ui.github.io/second-brain-os — the full guide with search and navigation, plus every vetted link in one filterable page.

The problem it solves

You save things with the intention of coming back. You never do. Bookmarks, screenshots, read-later queues and half-filled Notion pages accumulate without compounding, because filing and linking them is boring work that humans stop doing after two weeks.

Hand that work to an agent and the system stays alive. That is the whole idea.

Quickstart

One evening. Nine steps, each with a full page behind it.

# copy the starter vault, skills, commands and agents
git clone https://github.com/undefined-ui/second-brain-os.git
cp -r second-brain-os/vault-template ~/brain

mkdir -p ~/brain/.claude
cp -r second-brain-os/skills   ~/brain/.claude/skills
cp -r second-brain-os/commands ~/brain/.claude/commands
cp -r second-brain-os/agents   ~/brain/.claude/agents

cd ~/brain && claude

1. Install Obsidian and open ~/brain with "Open folder as vault"
2. Set up Claude Code, in the terminal or the Code tab of the desktop app
3. Connect over MCP if you want the agent to reach the vault from anywhere. Optional, skip it on day one
4. Get interviewed for your CLAUDE.md instead of writing it by hand
5. Set up the two layers: a wiki for what you know, projects for what you are doing
6. Scope down to one project when you want to ship something
7. Install the Web Clipper, clip an article to raw/, run /ingest
8. Connect live data: calendar, email, chat
9. Put maintenance on a schedule and wake up to a vault that filed itself

Then feed it ten more sources before judging it. The graph is not interesting at five pages and it is hard to look away from at fifty.

Full walkthrough: Setup.

How it works

   you                    raw/                 agent                 wiki/
 ┌───────┐          ┌──────────────┐      ┌────────────┐      ┌──────────────┐
 │ clip  │  ──────> │ articles     │ ───> │  ingest    │ ───> │ sources/     │
 │ save  │          │ transcripts  │      │  extract   │      │ concepts/    │
 │ dump  │          │ pdfs         │      │  link      │      │ entities/    │
 └───────┘          │ chat exports │      │  lint      │      │ synthesis/   │
                    └──────────────┘      └────────────┘      └──────────────┘
                                                │                     │
                                                │   ask anything      │
                                                └─────────────────────┘

Raw material is an archive you never read. The wiki is the artifact, written in plain language, one idea per page, densely linked. New sources update existing pages instead of piling up beside them, which is why the vault gets better as it grows rather than just bigger.

Alongside the wiki sits a project layer: one folder per project, each with its own CLAUDE.md and an Inputs / Process / Outputs / Feedback pipeline. The wiki holds what you know, the projects hold what you are doing, and they feed each other. The two layers covers why keeping them separate matters more than it sounds.

What is in here

The guide

Ten sections, 77 pages, written to be followed rather than skimmed. From the concept through setup, capture, structure, the graph, automation, retrieval, publishing, and what to do when each of them breaks.

Design decisions

This setup is opinionated. The three rules that matter most, and why:

Nothing is ingested until it is linked. A page that lands unconnected is invisible within a week. Linking is the entire value, so it happens in the same run or the ingest is not finished.

Contradictions are recorded, never overwritten. When a new source disagrees with a page, both positions stay, with dates and sources. The history of what you believed and why is the one thing your vault has that a search engine does not.

No vector database until you need one. A personal corpus is small and already structured. Structured pages plus links answer questions that chunk similarity cannot, at zero infrastructure cost. When RAG earns its place covers the threshold.

Who this is for

Anyone who reads a lot and retains less than they want to: researchers, engineers, writers, students, people who watch three hours of technical video a week and remember none of it.

It is not for team wikis, it is not a Notion replacement, and it will not organise a vault you never add to.

Portability

Everything here is markdown files, wikilinks and SKILL.md files. It works with Claude Code, and with any agent that reads files. Obsidian is a viewer for the graph, not a dependency. If you walk away from every tool named in this repo, you keep the folder and everything in it.

Learning materials

The source document, and the research behind the design decisions in this guide.

Full notes: reading.md and papers.md.

Tools and plugins

Obsidian plugins ranked by installs from the official community stats, September 2026. The full catalog is in plugins.md and tools.md.

Outside Obsidian: Web Clipper for capture, Claude Code for maintenance, yt-dlp and OCRmyPDF for processing, ripgrep, NetworkX, Kuzu and Gephi for the graph, and Quartz to publish.

Skills and other implementations

This repo ships 18 skills, 72 commands, 6 subagents and 4 scripts: one skill per workflow in the guide, and a command for every scoped version of it you would actually run.

Other implementations, counted the same way. A repo shipping sixteen skills counts as sixteen. Stars from the GitHub API, September 2026.

Where the format itself is defined: anthropics/skills (20 skills), obra/superpowers (14), VoltAgent/awesome-agent-skills (index of 1,000+). Notes on each: skills.md.

Graph, RAG and memory repos

Alternative homes for a vault, from Logseq to AFFiNE, plus RAG frameworks and AI-native note apps: repositories.md and tools.md.

Contributing

Corrections, resources and real examples are welcome. Read CONTRIBUTING.md first: every factual claim needs a primary source, and tool listings need a reason to exist.

Credit

The LLM wiki pattern is Andrej Karpathy's, published as a gist on 4 April 2026. This repo is one implementation of it, plus the parts the gist deliberately leaves undefined.

MIT licensed.