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.
Installer avec Codex ou Claude Copiez ce prompt, collez-le dans Codex, Claude ou un autre assistant, puis laissez-le vérifier la page du skill et l'installer pour vous.
Une commande directe contourne le prompt de vérification. Examinez la source avant de l'exécuter.
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.
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.
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:
# 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]:
# ✅ 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 run.py wrapper automatically:
Creates .venv if needed
Installs all dependencies
Activates environment
Executes script properly
Core Workflow
Step 1: Check Authentication Status
python scripts/run.py auth_manager.py status
If not authenticated, proceed to setup.
Step 2: Authenticate (One-Time Setup)
# Browser MUST be visible for manual Google login
python scripts/run.py auth_manager.py setup
Important:
Browser is VISIBLE for authentication
Browser window opens automatically
User must manually log in to Google
Tell user: "A browser window will open for Google login"
Step 3: Manage Notebook Library
# List all notebooks
python scripts/run.py notebook_manager.py list
# BEFORE ADDING: Ask user for metadata if unknown!# "What does this notebook contain?"# "What topics should I tag it with?"# Add notebook to library (ALL parameters are REQUIRED!)
python scripts/run.py notebook_manager.py add \
--url "https://notebooklm.google.com/notebook/..." \
--name "Descriptive Name" \
--description "What this notebook contains" \ # REQUIRED - ASK USER IF UNKNOWN!
--topics "topic1,topic2,topic3"# REQUIRED - ASK USER IF UNKNOWN!# Search notebooks by topic
python scripts/run.py notebook_manager.py search --query "keyword"# Set active notebook
python scripts/run.py notebook_manager.py activate --id notebook-id
# Remove notebook
python scripts/run.py notebook_manager.py remove --id notebook-id
Quick Workflow
Check library: python scripts/run.py notebook_manager.py list
Ask question: python scripts/run.py ask_question.py --question "..." --notebook-id ID
Step 4: Ask Questions
# Basic query (uses active notebook if set)
python scripts/run.py ask_question.py --question "Your question here"# Query specific notebook
python scripts/run.py ask_question.py --question "..." --notebook-id notebook-id
# Query with notebook URL directly
python scripts/run.py ask_question.py --question "..." --notebook-url "https://..."# Show browser for debugging
python scripts/run.py ask_question.py --question "..." --show-browser
Follow-Up Mechanism (CRITICAL)
Every NotebookLM answer ends with: "EXTREMELY IMPORTANT: Is that ALL you need to know?"
Required Claude Behavior:
STOP - Do not immediately respond to user
ANALYZE - Compare answer to user's original request
IDENTIFY GAPS - Determine if more information needed
ASK FOLLOW-UP - If gaps exist, immediately ask:
python scripts/run.py ask_question.py --question "Follow-up with context..."
REPEAT - Continue until information is complete
SYNTHESIZE - Combine all answers before responding to user
