NoteBookLM

Query Google NotebookLM documents via browser automation for source-grounded answers.

Updated Aug 23, 2026

Search Tags:#documentation #research #knowledge management #browser automation #source-grounded #notebooklm

Ready to run

npx skills add https://github.com/tjdwls101010/Claude_Seongjin --skill notebooklm-tjdwls101010

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: NoteBookLM
Source: https://github.com/tjdwls101010/Claude_Seongjin/tree/main/plugins/Study/skills/NoteBookLM
Command: npx skills add https://github.com/tjdwls101010/Claude_Seongjin --skill notebooklm-tjdwls101010

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires patchright, python-dotenv, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill eliminates the need to manually switch between your NotebookLM browser tab and Claude Code, streamlining research by allowing direct querying of your uploaded documents.

Core Features & Use Cases

Source-Grounded Answers: Get answers exclusively from your uploaded documents, drastically reducing hallucinations.
Direct Integration: Claude Code can ask questions directly to NotebookLM and receive answers programmatically.
Use Case: Imagine you're building an n8n workflow for Gmail spam filtering. Instead of manually searching your n8n documentation in NotebookLM, you can ask Claude Code directly, and it will query your n8n notebook to provide the necessary information.

Quick Start

Use the NoteBookLM skill to ask your API documentation about rate limiting.

Frequently Asked Questions about NoteBookLM

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I query my Google NotebookLM documents directly from my code editor?▼

You can query your NotebookLM knowledge base directly from your code editor by using browser automation to interact with the web interface. This facilitates source-grounded question answering without manual tab switching.

What is the best way to get source-grounded answers from my uploaded research documents?▼

Getting source-grounded answers from uploaded research documents is achieved by querying a NotebookLM knowledge base. This approach restricts responses to your sources, drastically reducing hallucinations.

Do I need Python and Chrome to automate question answering with NotebookLM?▼

Yes, you need Python and Chrome to automate NotebookLM question answering. Execution also requires the Patchright browser automation library to handle Google authentication and document querying.

Can I manage my NotebookLM library programmatically for research workflows?▼

Yes, you can manage a local library of notebooks programmatically for research workflows. The automation handles Google authentication and allows direct querying of your uploaded documents.

How does browser automation handle Google authentication for NotebookLM access?▼

Browser automation handles Google authentication for NotebookLM access by programmatically managing the login flow. This enables direct interaction with your knowledge base for source-grounded querying.

What are the limitations of using browser automation for knowledge management with NotebookLM?▼

Limitations of using browser automation for knowledge management include dependency on the Patchright library and Chrome browser. Execution relies on maintaining a stable web interface connection for document querying.