NotebookLM Claude Code Skill

Let Claude Code chat directly with NotebookLM for source-grounded answers based exclusively on your uploaded documents

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 - answers only from your uploaded documents.

Installation • Quick Start • Why NotebookLM • How It Works • MCP Alternative

⚠️ Important: Local Claude Code Only

This skill works ONLY with local Claude Code installations, NOT in the web UI.

The web UI runs skills in a sandbox without network access, which this skill requires for browser automation. You must use Claude Code locally on your machine.

The Problem

When you tell Claude Code to "search through my local documentation", here's what happens:

Massive token consumption: Searching through documentation means reading multiple files repeatedly
Inaccurate retrieval: Searches for keywords, misses context and connections between docs
Hallucinations: When it can't find something, it invents plausible-sounding APIs
Manual copy-paste: Switching between NotebookLM browser and your editor constantly

The Solution

This Claude Code Skill lets Claude Code chat directly with NotebookLM — Google's source-grounded knowledge base powered by Gemini 2.5 that provides intelligent, synthesized answers exclusively from your uploaded documents.

Your Task → Claude asks NotebookLM → Gemini synthesizes answer → Claude writes correct code

No more copy-paste dance: Claude asks questions directly and gets answers straight back in the CLI. It builds deep understanding through automatic follow-ups, getting specific implementation details, edge cases, and best practices.

Why NotebookLM, Not Local RAG?

Approach	Token Cost	Setup Time	Hallucinations	Answer Quality
Feed docs to Claude	🔴 Very high (multiple file reads)	Instant	Yes - fills gaps	Variable retrieval
Web search	🟡 Medium	Instant	High - unreliable sources	Hit or miss
Local RAG	🟡 Medium-High	Hours (embeddings, chunking)	Medium - retrieval gaps	Depends on setup
NotebookLM Skill	🟢 Minimal	5 minutes	Minimal - source-grounded only	Expert synthesis

What Makes NotebookLM Superior?

Pre-processed by Gemini: Upload docs once, get instant expert knowledge
Natural language Q&A: Not just retrieval — actual understanding and synthesis
Multi-source correlation: Connects information across 50+ documents
Citation-backed: Every answer includes source references
No infrastructure: No vector DBs, embeddings, or chunking strategies needed

Installation

The simplest installation ever:

# 1. Create skills directory (if it doesn't exist)
mkdir -p ~/.claude/skills

# 2. Clone this repository
cd ~/.claude/skills
git clone https://github.com/PleasePrompto/notebooklm-skill notebooklm

# 3. That's it! Open Claude Code and say:
"What are my skills?"

When you first use the skill, it automatically:

Creates an isolated Python environment (.venv)
Installs all dependencies including Google Chrome
Sets up browser automation with Chrome (not Chromium) for maximum reliability
Everything stays contained in the skill folder

Note: The setup uses real Chrome instead of Chromium for cross-platform reliability, consistent browser fingerprinting, and better anti-detection with Google services

Quick Start

1. Check your skills

Say in Claude Code:

"What skills do I have?"

Claude will list your available skills including NotebookLM.

2. Authenticate with Google (one-time)

"Set up NotebookLM authentication"

A Chrome window opens → log in with your Google account

3. Create your knowledge base

Go to [notebooklm.google.com](https://notebooklm.goo

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pleaseprompto/notebooklm-skill

README