notebooklm

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"

When user wants to add a notebook without providing details:

SMART ADD (Recommended): Query the notebook first to discover its content:

```bash

# 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.

NEVER call scripts directly. ALWAYS use python scripts/run.py [script]:

```bash

# ✅ 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

Step 1: Check Authentication Status

```bash

python scripts/run.py auth_manager.py status

```

If not authenticated, proceed to setup.

Step 2: Authenticate (One-Time Setup)

```bash

# 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

```bash

# 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

```bash

# 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

```

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:

```bash

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

```

1. REPEAT - Continue until information is complete
2. SYNTHESIZE - Combine all answers before responding to user

Authentication Management (`auth_manager.py`)

```bash

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`)

```bash

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`)

```bash

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

```

Data Cleanup (`cleanup_manager.py`)

```bash

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

```

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):

```bash

python -m venv .venv

source .venv/bin/activate # Linux/Mac

pip install -r requirements.txt

python -m patchright install chromium

```

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.

Optional .env file in skill directory:

```env

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

```

```

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

```

| 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 |

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

• 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)

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