# Notebooklm

Use this skill to query your Google NotebookLM notebooks directly from Claude Code for...

- Repository: https://github.com/guanyang/open-agent-hub (985 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-10-31
- Runs scripts: yes, review before use

## Install

Claude Code: `npx skills add guanyang/open-agent-hub --skill notebooklm -g -a claude-code -y`
Codex: `npx skills add guanyang/open-agent-hub --skill notebooklm -g -a codex -y`
Cursor: `npx skills add guanyang/open-agent-hub --skill notebooklm -g -a cursor -y`
Gemini CLI: `npx skills add guanyang/open-agent-hub --skill notebooklm -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add guanyang/open-agent-hub`

## Description

Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# NotebookLM Research Assistant Skill

Interact with Google NotebookLM to query documentation with Gemini's source-grounded answers. Each question opens a fresh browser session, retrieves the answer exclusively from your uploaded documents, and closes.

## When to Use This Skill

Trigger when user:
- Mentions NotebookLM explicitly
- Shares NotebookLM URL (`https://notebooklm.google.com/notebook/...`)
- Asks to query their notebooks/documentation
- Wants to add documentation to NotebookLM library
- Uses phrases like "ask my NotebookLM", "check my docs", "query my notebook"

## ⚠️ CRITICAL: Add Command - Smart Discovery

When user wants to add a notebook without providing details:

**SMART ADD (Recommended)**: Query the notebook first to discover its content:
```bash
# Step 1: Query the notebook about its content
python scripts/run.py ask_question.py --question "What is the content of this notebook? What topics are covered? Provide a complete overview briefly and concisely" --notebook-url "[URL]"

# Step 2: Use the discovered information to add it
python scripts/run.py notebook_manager.py add --url "[URL]" --name "[Based on content]" --description "[Based on content]" --topics "[Based on content]"
```

**MANUAL ADD**: If user provides all details:
- `--url` - The NotebookLM URL
- `--name` - A descriptive name
- `--description` - What the notebook contains (REQUIRED!)
- `--topics` - Comma-separated topics (REQUIRED!)

NEVER guess or use generic descriptions! If details missing, use Smart Add to discover them.

## Critical: Always Use run.py Wrapper

**NEVER call scripts directly. ALWAYS use `python scripts/run.py [script]`:**

```bash
# ✅ CORRECT - Always use run.py:
python scripts/run.py auth_manager.py status
python scripts/run.py notebook_manager.py list
python scripts/run.py ask_question.py --question "..."

# ❌ WRONG - Never call directly:
python scripts/auth_manager.py status  # Fails without venv!
```

The rest: https://github.com/guanyang/open-agent-hub/blob/HEAD/skills/notebooklm/SKILL.md