NotebookLM Research Assistant Skill

Interact with Google NotebookLM to query documentation with Gemini's zero-hallucination answers. Each question opens a fresh browser session, retrieves the answer, 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 Requirements

When adding a notebook, these parameters are ALL REQUIRED:

•--url - The NotebookLM URL
•--name - A descriptive name
•--description - What the notebook contains (CANNOT BE OMITTED!)
•--topics - Comma-separated topics (CANNOT BE OMITTED!)

If you don't know what's in the notebook, ASK THE USER FIRST:

code

"What does this notebook contain and what topics does it cover?"
"Please describe what's in this notebook so I can add it to the library."

NEVER guess or use generic descriptions like "notebook" or "documentation"!

Critical: Always Use run.py Wrapper

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:

•Creates .venv if needed
•Installs all dependencies
•Activates environment
•Executes script properly

Core Workflow

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:

•NEVER use --headless 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

Step 4: Ask Questions

bash

# Basic query
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:

bash

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

Script Reference

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

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):

bash

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:

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

Decision Flow

code

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, no `--headless`
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

•Always use run.py - Handles environment automatically
•Check auth first - Before any operations
•Follow-up questions - Don't stop at first answer
•Browser visible for auth - Required for manual login
•Include context - Each question is independent
•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

•scripts/ - All automation scripts
•data/ - Local storage (auth, notebooks)
•references/ - Extended documentation
•.venv/ - Isolated Python environment
•.gitignore - Protects sensitive data

Based on notebooklm-mcp adapted for local execution.

NotebookLM Research Assistant Skill

When to Use This Skill

⚠️ CRITICAL: Add Command Requirements

Critical: Always Use run.py Wrapper

Core Workflow

Step 1: Check Authentication Status

Step 2: Authenticate (One-Time Setup)

Step 3: Manage Notebook Library

Step 4: Ask Questions

Follow-Up Mechanism (CRITICAL)

Script Reference

Authentication Management (auth_manager.py)

Notebook Management (notebook_manager.py)

Question Interface (ask_question.py)

Data Cleanup (cleanup_manager.py)

Environment Management

Data Storage

Configuration

Decision Flow

Troubleshooting

Best Practices

Limitations

Resources

Authentication Management (`auth_manager.py`)

Notebook Management (`notebook_manager.py`)

Question Interface (`ask_question.py`)

Data Cleanup (`cleanup_manager.py`)