Notebooklm

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:

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:

1. Creates .venv if needed

2. Installs all dependencies

3. Activates environment

4. 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

1. Check library: python scripts/run.py notebook_manager.py list

2. 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:

1. STOP - Do not immediately respond to user

2. ANALYZE - Compare answer to user's original request

3. IDENTIFY GAPS - Determine if more information needed

4. ASK FOLLOW-UP - If gaps exist, immediately ask:

   python scripts/run.py ask_question.py --question "Follow-up with context..."

   

5. REPEAT - Continue until information is complete

6. SYNTHESIZE - Combine all answers before responding to user

Script Reference

Authentication Management (auth_manager.py)

python scripts/run.py auth_manager.py setup    # Initial setup (browser visible)
python scripts/run.py auth_manager.py status   # Check authentication
python scripts/run.py auth_manager.py reauth   # Re-authenticate (browser visible)
python scripts/run.py auth_manager.py clear    # Clear authentication

Notebook Management (notebook_manager.py)

python scripts/run.py notebook_manager.py add --url URL --name NAME --description DESC --topics TOPICS
python scripts/run.py notebook_manager.py list
python scripts/run.py notebook_manager.py search --query QUERY
python scripts/run.py notebook_manager.py activate --id ID
python scripts/run.py notebook_manager.py remove --id ID
python scripts/run.py notebook_manager.py stats

Question Interface (ask_question.py)

python scripts/run.py ask_question.py --question "..." [--notebook-id ID] [--notebook-url URL] [--show-browser]

Data Cleanup (cleanup_manager.py)

python scripts/run.py cleanup_manager.py                    # Preview cleanup
python scripts/run.py cleanup_manager.py --confirm          # Execute cleanup
python scripts/run.py cleanup_manager.py --preserve-library # Keep notebooks

Environment Management

The virtual environment is automatically managed:

• -First run creates .venv automatically
• -Dependencies install automatically
• -Chromium browser installs automatically
• -Everything isolated in skill directory

Manual setup (only if automatic fails):

python -m venv .venv
source .venv/bin/activate  # Linux/Mac
pip install -r requirements.txt
python -m patchright install chromium

Data Storage

All data stored in ~/.claude/skills/notebooklm/data/:

• -library.json - Notebook metadata
• -auth_info.json - Authentication status
• -browser_state/ - Browser cookies and session

Security: Protected by .gitignore, never commit to git.

Configuration

Optional .env file in skill directory:

HEADLESS=false           # Browser visibility
SHOW_BROWSER=false       # Default browser display
STEALTH_ENABLED=true     # Human-like behavior
TYPING_WPM_MIN=160       # Typing speed
TYPING_WPM_MAX=240
DEFAULT_NOTEBOOK_ID=     # Default notebook

Decision Flow

User mentions NotebookLM
    ↓
Check auth → python scripts/run.py auth_manager.py status
    ↓
If not authenticated → python scripts/run.py auth_manager.py setup
    ↓
Check/Add notebook → python scripts/run.py notebook_manager.py list/add (with --description)
    ↓
Activate notebook → python scripts/run.py notebook_manager.py activate --id ID
    ↓
Ask question → python scripts/run.py ask_question.py --question "..."
    ↓
See "Is that ALL you need?" → Ask follow-ups until complete
    ↓
Synthesize and respond to user

Troubleshooting

| Problem | Solution |

|---------|----------|

| ModuleNotFoundError | Use run.py wrapper |

| Authentication fails | Browser must be visible for setup! --show-browser |

| Rate limit (50/day) | Wait or switch Google account |

| Browser crashes | python scripts/run.py cleanup_manager.py --preserve-library |

| Notebook not found | Check with notebook_manager.py list |

Best Practices

1. Always use run.py - Handles environment automatically

2. Check auth first - Before any operations

3. Follow-up questions - Don't stop at first answer

4. Browser visible for auth - Required for manual login

5. Include context - Each question is independent

6. Synthesize answers - Combine multiple responses

Limitations

• -No session persistence (each question = new browser)
• -Rate limits on free Google accounts (50 queries/day)
• -Manual upload required (user must add docs to NotebookLM)
• -Browser overhead (few seconds per question)

Resources (Skill Structure)

Important directories and files:

• -scripts/ - All automation scripts (ask_question.py, notebook_manager.py, etc.)
• -data/ - Local storage for authentication and notebook library
• -references/ - Extended documentation:

- api_reference.md - Detailed API documentation for all scripts

- troubleshooting.md - Common issues and solutions

- usage_patterns.md - Best practices and workflow examples

• -.venv/ - Isolated Python environment (auto-created on first run)
• -.gitignore - Protects sensitive data from being committed