# notebooklm

Queries Google NotebookLM notebooks for citation-backed answers from uploaded sources and generates Studio assets like mind maps or quizzes.

- skill · `type=skill` · Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, OpenCode · ★ 213
- Author: roomi-fields
- License: MIT · policy=mirror · the beginning of the file is at the end of this page
- Source: https://github.com/roomi-fields/notebooklm-mcp/tree/HEAD/skills/notebooklm/SKILL.md
- Updated: 2026-10-24
- HTML: https://affpapa.org/en/nevibecode/skills/roomi-fields-notebooklm

## What it does

The skill connects your agent to the `@roomi-fields/notebooklm-mcp` engine either through direct MCP tools (`notebook_ask`, `source_add`) or via `scripts/nblm.sh` over HTTP at `http://localhost:3000`. It restricts answers strictly to passages uploaded to your Google NotebookLM notebooks. Every response includes direct source citations without drawing on general web knowledge.

Beyond answering questions, it triggers Studio generation endpoints. You can produce reports, flashcards, study quizzes, audio overviews, or mind maps from your source material. Pass a persistent `session_id` to continue a thread, or omit it to speed up standalone queries.

You must complete an interactive Google login in a real terminal via `notebooklm-mcp-setup-auth` before making queries. Free accounts hit a ceiling of roughly 50 queries per day, making offline batch caching necessary for extensive literature reviews.

## Install

### Claude Code (native platform)

1. **Skills CLI (Vercel)**
```bash
npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a claude-code
```

2. **Manually: put the files in place**
- File: `~/.claude/skills/notebooklm/SKILL.md` — Copy the whole skill folder; for one project use .claude/skills/notebooklm/

### Codex

1. **Skills CLI (Vercel)**
```bash
npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a codex
```

2. **Manually: put the files in place**
- File: `.agents/skills/notebooklm/SKILL.md` — For all projects use ~/.agents/skills/

### Cursor

1. **Skills CLI (Vercel)**
```bash
npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a cursor
```

2. **Manually: put the files in place**
- File: `.cursor/skills/notebooklm/SKILL.md` — Cursor also reads .agents/skills/ and .claude/skills/

### GitHub Copilot

1. **GitHub CLI**
```bash
gh skill install roomi-fields/notebooklm-mcp notebooklm
```

2. **Manually: put the files in place**
- File: `.github/skills/notebooklm/SKILL.md`

### Gemini CLI

1. **Skills CLI (Vercel)**
```bash
npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a gemini-cli
```

2. **Platform CLI**
```bash
gemini skills install https://github.com/roomi-fields/notebooklm-mcp --path skills/notebooklm
```

### Windsurf (Devin Desktop)

**Manually: put the files in place**
- File: `.devin/skills/notebooklm/SKILL.md` — The legacy .windsurf/skills/ path still works

### OpenCode

**Skills CLI (Vercel)**
```bash
npx skills add roomi-fields/notebooklm-mcp --skill notebooklm -a opencode
```

### Claude.ai

**Claude.ai**
- Zip the folder and upload it in Settings → Capabilities → Skills

Where a file is given instead of a command, copy the files from the source to that path: https://github.com/roomi-fields/notebooklm-mcp/tree/HEAD/skills/notebooklm/SKILL.md

## When to use it
- query private NotebookLM notebooks with verified passage citations
- generate Studio study aids such as quizzes, flashcards, and mind maps
- check connection and Google authentication status
- list available Google NotebookLM notebooks and inspect sources

## Example prompts
- List my NotebookLM notebooks
- Ask notebook 123abc what methodology was used in the study
- Generate a mind map for notebook 456def

## Source text · SKILL.md · MIT

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BEGIN THIRD-PARTY FILE 662ec8b1a5e0bc52
````text
---
name: notebooklm
description: This skill should be used when the user wants to query their Google NotebookLM notebooks for citation-backed, source-grounded answers, or manage notebooks, sources, and Studio content (audio, report, video, infographic, presentation, data table, flashcards, quiz, mind map). It drives the @roomi-fields/notebooklm-mcp engine — via the notebooklm MCP tools when they are available in the session, otherwise via its HTTP REST API — and covers Google login, citation formats, the daily-quota-aware batch/ingestion pattern, and source discovery.
---

# NotebookLM

## Overview

NotebookLM answers questions **only from the sources uploaded to a notebook**,
with inline citations to the exact passages used — no open-web knowledge, so
answers are hallucination-resistant and fully traceable. This skill drives the
`@roomi-fields/notebooklm-mcp` engine to query notebooks, manage sources, and
generate Studio content, and encodes the patterns that make NotebookLM usable at
research scale (citation formats, the ~50-queries/day quota, batch-to-cache).

## Choosing the transport

Two ways reach the same engine — pick per what the session already has:

1. **notebooklm MCP tools** — if tools such as `notebook_ask` / `source_add` /
   `server_health` (or `mcp__notebooklm__*`) are available in the session, call
   them directly. This is the preferred path and needs no server.
2. **HTTP REST API** — otherwise, use the bundled `scripts/nblm.sh`, which talks
   to a running NotebookLM MCP server (default `http://localhost:3000`,
   override with `NOTEBOOKLM_SERVER_URL`). If no server is reachable, ask the
   user to start one (`npm run start:http` from a clone) or to install the MCP.

Both are backed by the same account and session, so the choice is purely about
which is already wired up.

## Prerequisite: one Google login

NotebookLM needs a signed-in Google session (saved once, reused across runs).
Verify with `nblm.sh health` (or the `server_health` tool) — look for
`authenticated: true`. If not authenticated, run the interactive login **in a
terminal** (a visible Chrome window opens):

```bash
notebooklm-mcp-setup-auth          # global install
# or:  scripts/nblm.sh auth
```

Run the login in a terminal rather than through an in-client tool: interactive
Google login can take minutes and a stdio client's tool-call timeout may cut it
off.

## Core tasks

Use `scripts/nblm.sh` for the REST path (or the equivalent MCP tool):

```bash
scripts/nblm.sh health                       # reachability + auth status
scripts/nblm.sh notebooks                     # list notebooks (id + name)
scripts/nblm.sh ask "<question>" <notebook_id>   # citation-backed answer (JSON citations)
scripts/nblm.sh generate <notebook_id> report   # audio|report|video|infographic|presentation|data_table|flashcards|quiz|mind_map
```

- **Ask**: the script requests `source_format: json`, so the answer carries
````
END THIRD-PARTY FILE 662ec8b1a5e0bc52

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