Skill

notebooklm

This skill should be used when the user wants to query Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Provides browser automation, library management, and persistent auth. Drastically reduced hallucinations through document-only responses.

From bopen-tools

Install

Run in your terminal

npx claudepluginhub b-open-io/claude-plugins --plugin bopen-tools

Tool Access

This skill uses the workspace's default tool permissions.

Supporting Assets

View in Repository

references/api-reference.md

references/api_reference.md

references/best-practices.md

references/troubleshooting.md

references/usage_patterns.md

requirements.txt

scripts/__init__.py

scripts/ask_question.py

scripts/auth_manager.py

scripts/browser_session.py

scripts/browser_utils.py

scripts/cleanup_manager.py

scripts/config.py

scripts/notebook_manager.py

scripts/run.py

scripts/setup_environment.py

Skill Content

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Stats

Stars11

Forks3

Last CommitMar 6, 2026

Actions

View Source View Plugin View on GitHub View README

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

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: 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 handles environment setup.

Core Workflow

Step 1: Check Authentication

python scripts/run.py auth_manager.py status

If not authenticated, proceed to setup.

Step 2: Authenticate (One-Time Setup)

python scripts/run.py auth_manager.py setup

Important: Browser is VISIBLE for authentication. User must manually log in to Google.

Step 3: Manage Notebook Library

# List all notebooks
python scripts/run.py notebook_manager.py list

# Add notebook to library (ALL parameters REQUIRED)
python scripts/run.py notebook_manager.py add \
  --url "https://notebooklm.google.com/notebook/..." \
  --name "Descriptive Name" \
  --description "What this notebook contains" \
  --topics "topic1,topic2,topic3"

# Smart Add (discover content first)
python scripts/run.py ask_question.py \
  --question "What is the content of this notebook?" \
  --notebook-url "[URL]"
# Then use discovered info to add

# Set active notebook
python scripts/run.py notebook_manager.py activate --id notebook-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://..."

Follow-Up Mechanism (CRITICAL)

Every NotebookLM answer ends with: "EXTREMELY IMPORTANT: Is that ALL you need to know?"

Required 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 follow-up question
REPEAT - Continue until information is complete
SYNTHESIZE - Combine all answers before responding to user

Script Reference

Script	Purpose
`auth_manager.py`	Authentication setup and status
`notebook_manager.py`	Library management (add, list, search, activate, remove)
`ask_question.py`	Query interface
`cleanup_manager.py`	Data cleanup and maintenance

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.

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)

Additional Resources

For detailed guidance, see the references directory:

references/api-reference.md - Complete API documentation for all scripts with parameters, response formats, and exit codes
references/troubleshooting.md - Common errors and solutions including authentication issues, rate limits, browser crashes, and recovery procedures
references/best-practices.md - Workflow patterns, question strategies, library organization, and rate limit management

Quick Reference

# Check auth
python scripts/run.py auth_manager.py status

# Add notebook
python scripts/run.py notebook_manager.py add --url URL --name NAME --description DESC --topics TOPICS

# List notebooks
python scripts/run.py notebook_manager.py list

# Ask question
python scripts/run.py ask_question.py --question "..."

# Cleanup
python scripts/run.py cleanup_manager.py --preserve-library