OpenClaw-Awesome-Skills notebooklm
Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.
git clone https://github.com/roadsidedev/OpenClaw-Awesome-Skills
T=$(mktemp -d) && git clone --depth=1 https://github.com/roadsidedev/OpenClaw-Awesome-Skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/notebooklm" ~/.claude/skills/roadsidedev-openclaw-awesome-skills-notebooklm && rm -rf "$T"
T=$(mktemp -d) && git clone --depth=1 https://github.com/roadsidedev/OpenClaw-Awesome-Skills "$T" && mkdir -p ~/.openclaw/skills && cp -r "$T/skills/notebooklm" ~/.openclaw/skills/roadsidedev-openclaw-awesome-skills-notebooklm && rm -rf "$T"
skills/notebooklm/SKILL.mdNotebookLM 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:
- The NotebookLM URL--url
- A descriptive name--name
- What the notebook contains (REQUIRED!)--description
- Comma-separated topics (REQUIRED!)--topics
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:
- Creates
if needed.venv - Installs all dependencies
- Activates environment
- 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
- Check library:
python scripts/run.py notebook_manager.py list - 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:
- 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:
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
)
auth_manager.pypython 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
)
notebook_manager.pypython 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
)
ask_question.pypython scripts/run.py ask_question.py --question "..." [--notebook-id ID] [--notebook-url URL] [--show-browser]
Data Cleanup (cleanup_manager.py
)
cleanup_manager.pypython 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
automatically.venv - 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
/home/me/clawd/skills/notebooklm/data/:
- Notebook metadatalibrary.json
- Authentication statusauth_info.json
- Browser cookies and sessionbrowser_state/
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 wrapper |
| Authentication fails | Browser must be visible for setup! --show-browser |
| Rate limit (50/day) | Wait or switch Google account |
| Browser crashes | |
| Notebook not found | Check with |
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 (Skill Structure)
Important directories and files:
- All automation scripts (ask_question.py, notebook_manager.py, etc.)scripts/
- Local storage for authentication and notebook librarydata/
- Extended documentation:references/
- Detailed API documentation for all scriptsapi_reference.md
- Common issues and solutionstroubleshooting.md
- Best practices and workflow examplesusage_patterns.md
- Isolated Python environment (auto-created on first run).venv/
- Protects sensitive data from being committed.gitignore