nblm

Query Google NotebookLM notebooks for source-grounded, citation-backed answers via Gemini.

Updated Mar 3, 2026
One-click install
npx skills add https://github.com/shimseonjo/lectuer_factory --skill nblm-shimseonjo
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: nblm
Source: https://github.com/shimseonjo/lectuer_factory/tree/main/.claude/skills/nblm
Command: npx skills add https://github.com/shimseonjo/lectuer_factory --skill nblm-shimseonjo

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires agent-browser, notebooklm-py, python-dotenv, ebooklib, beautifulsoup4, lxml, pypdf, patchright, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill allows you to query your Google NotebookLM notebooks directly from Claude Code, enabling you to get source-grounded, citation-backed answers from Gemini without switching contexts.

Core Features & Use Cases

  • Source-Grounded Answers: Get answers directly from your uploaded documents, minimizing hallucinations.
  • Contextual Queries: Ask questions about your research, notes, or any documents you've added to NotebookLM.
  • Use Case: Imagine you're working on a coding project and need to recall a specific detail from a technical document you previously uploaded to NotebookLM. You can simply ask Claude Code, and it will retrieve the answer directly from your notebook, complete with citations.

Quick Start

Use the nblm skill to ask Claude Code what the documentation says about authentication.

Frequently Asked Questions about nblm

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

FAQPage Schema
How do I query my Google NotebookLM documents from a coding agent?

You can query your Google NotebookLM documents directly from AI coding agents to get source-grounded, citation-backed answers from Gemini without switching contexts or leaving your development environment.

What's the best way to get citation-backed answers from my research notes?

Querying Google NotebookLM through an AI assistant retrieves answers directly from your uploaded documents, minimizing hallucinations by providing source-grounded responses complete with citations for your research notes.

Does querying NotebookLM require browser automation setup?

Querying NotebookLM integrates browser automation via agent-browser and a Python API client to handle library management, authentication, and media generation automatically, handling environment setup for you.

Can I use this with documents uploaded to Z-Library?

Yes, the Skill supports Z-Library integration, allowing you to query your uploaded research documents and technical notes through Google NotebookLM using the Gemini API.

How do I ask an AI assistant about a technical document I previously uploaded?

You can ask your AI coding agent to retrieve specific details from technical documents uploaded to NotebookLM, and it will query the notebook to return the answer directly with citations.

What formats are supported for uploading files to the knowledge base?

The Skill processes knowledge base queries using dependencies for EPUB files, PDF documents, and HTML parsing to extract source-grounded answers from your uploaded research and notes.