notebooklm
NotebookLM is a skill that enables querying Google NotebookLM notebooks directly within Claude Code to retrieve source-grounded, citation-backed answers powered by Gemini. Use this skill when users explicitly mention NotebookLM, share notebook URLs, request documentation queries, or want to add documentation to their NotebookLM library. The skill reduces hallucinations by restricting responses exclusively to uploaded documents through automated browser sessions with persistent authentication management.
git clone --depth 1 https://github.com/guanyang/open-agent-hub /tmp/notebooklm && cp -r /tmp/notebooklm/skills/notebooklm ~/.claude/skills/notebooklmSKILL.md
# 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: ```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. ## 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: 1. Creates `.venv` if needed 2. Installs all dependencies 3. Activates environment 4. 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:** - 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 ``` ## 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: ```bash 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`) ```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
Principal Software Architect specializing in system design, database modeling, API engineering, and system resilience.
Principal Diagnostics Engineer specializing in root cause analysis, error troubleshooting, and hotfixes.
Principal Clean Code Specialist specializing in code simplification, performance tuning, and refactoring loops.
Senior Technical Lead and Security Auditor specializing in code quality, correctness, and security audits.
Senior QA Automation Engineer specializing in unit, integration, and E2E test suite creation.
Run when user calls /commit or asks to generate a commit message. Analyzes staged changes and writes a structured commit message.
Run when user calls /review. Analyzes local changes and runs a comprehensive code review using the agent-reviewer prompt.
Run when user calls /test-tdd. Scans modified files, locates their corresponding unit/integration test suites, and runs them.