NotebookLM Experts 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://notebook.google.com/notebook/...)
- Asks to query their notebooks or documentation
- Wants to add documentation to the NotebookLM library
- Uses phrases like "ask my NotebookLM", "check my docs", "query my notebook"
Available Methods
| Method | Purpose | Use When |
|---|---|---|
| query | Ask single question from one notebook | User asks a specific question from one document |
| research | Comprehensive research across multiple notebooks | User wants synthesis from multiple sources |
| library | Manage notebook collection | Adding, updating, or organizing notebooks |
First-Time Setup (Run Once)
# Install isolated .venv and all dependencies
python install.py
This creates a .venv/ inside the skill directory, installs patchright, and installs Google Chrome. Safe to run multiple times — skips if .venv/ already exists.
Critical: Always Use the run Wrapper
NEVER use bare python. ALWAYS invoke via run.bat (Windows) or run.sh (Unix) — these resolve .venv Python directly:
:: Windows
.\run.bat auth_manager.py status
.\run.bat notebook_manager.py list
.\run.bat ask_question.py --question "..."
# Linux / macOS
./run.sh auth_manager.py status
./run.sh notebook_manager.py list
./run.sh ask_question.py --question "..."
Both wrappers resolve .venv\Scripts\python.exe (Windows) or .venv/bin/python (Unix) and pass all arguments to scripts/run.py. They fail fast with a clear message if install.py was not run yet.
Core Workflow
Step 1: Check Authentication
.\run.bat auth_manager.py status
If not authenticated, proceed to setup.
Step 2: Authenticate (One-Time)
:: Create a new profile and login
.\run.bat auth_manager.py setup --name "Work Account"
:: Or authenticate existing profile
.\run.bat auth_manager.py setup --profile work-account
Important: Browser is VISIBLE for authentication. User must manually log in to Google.
Step 2b: Multi-Account Management
:: List all profiles with status
.\run.bat auth_manager.py list
:: Switch active profile
.\run.bat auth_manager.py set-active --id work-account
:: Validate a profile is still authenticated
.\run.bat auth_manager.py validate --profile work-account
:: Re-authenticate an expired profile
.\run.bat auth_manager.py reauth --profile work-account
:: Delete a profile
.\run.bat auth_manager.py delete --id old-account
Step 2c: Add New Profile (Interactive)
Recommended for first-time users — guided experience with browser automation.
:: Interactive profile creation wizard
python add_profile.py
This interactive script will:
1. 📝 Ask for profile name (e.g., "Work Account", "Research", "Team")
2. 🔍 Verify the name is unique
3. ⚙️ Create the profile automatically
4. 🌐 Open browser for Google login (visible, user manually logs in)
5. ✅ Confirm authentication and show next steps
Example:
[1] A browser window will open automatically
[2] You will see the Google login page
[3] Sign in with your Google account
[4] Grant NotebookLM access (if prompted)
[5] You will be redirected to NotebookLM
After completion, profile is ready to use:
:: Use new profile
.\run.bat ask_question.py --question "Your question" --profile my-account
:: Switch to it as default
.\run.bat auth_manager.py set-active --id my-account
Step 3: Manage Notebook Library
:: List all notebooks
.\run.bat notebook_manager.py list
:: Add notebook to library (ALL parameters REQUIRED)
.\run.bat notebook_manager.py add ^
--url "https://notebook.google.com/notebook/..." ^
--name "Descriptive Name" ^
--description "What this notebook contains" ^
--topics "topic1,topic2,topic3"
:: Set active notebook
.\run.bat notebook_manager.py activate --id notebook-id
Step 4: Ask Questions
:: Uses active notebook (from active profile)
.\run.bat ask_question.py --question "Your question here"
:: Query specific notebook by ID
.\run.bat ask_question.py --question "..." --notebook-id notebook-id
:: Query via direct URL
.\run.bat ask_question.py --question "..." --notebook-url "https://..."
:: Query using a specific profile
.\run.bat ask_question.py --question "..." --profile work-account
Step 5: Research across Multiple Notebooks
:: Basic research (1 query per notebook)
.\run.bat research_method.py --topics "How does authentication work?"
:: Comprehensive research (3 queries per notebook, synthesized)
.\run.bat research_method.py --topics "API security" --depth comprehensive
:: Detailed research (5 queries per notebook)
.\run.bat research_method.py --topics "Microservices patterns" --depth detailed
:: Research specific notebooks only
.\run.bat research_method.py --topics "DevOps best practices" --notebooks nb_id1 nb_id2
:: Research using specific profile
.\run.bat research_method.py --topics "Cloud architecture" --profile work-account
:: Export results to file (json or markdown)
.\run.bat research_method.py --topics "Performance optimization" --export json
Research Depths:
- summary (1 query/notebook) — Quick overview
- comprehensive (3 queries/notebook) — Balanced research with synthesis
- detailed (5 queries/notebook) — Exhaustive research with deep synthesis
See references/research-guide.md for research strategies and best practices.
Follow-Up Mechanism (CRITICAL)
Every NotebookLM answer ends with: "EXTREMELY IMPORTANT: Is that ALL you need to know?"
Required Behavior:
1. STOP — Do not immediately respond to user
2. ANALYZE — Compare answer to original request
3. IDENTIFY GAPS — Determine if more information needed
4. ASK FOLLOW-UP — If gaps exist, ask another question immediately
5. REPEAT — Continue until information is complete
6. SYNTHESIZE — Combine all answers before responding to user
Script Reference
| Script | Purpose |
|---|---|
add_profile.py |
Interactive wizard — Create new profile with guided setup and browser login |
ask_question.py |
Query single notebook with one question |
research_method.py |
Research across multiple notebooks with optional synthesis |
notebook_manager.py |
Library management (add, list, search, activate, remove) |
auth_manager.py |
Authentication setup, status, and multi-profile management |
browser_session.py |
Persistent browser session for multi-turn conversations |
cleanup_manager.py |
Data cleanup and maintenance |
setup_environment.py |
Auto-creates .venv on first run.py call |
Data Storage
All runtime data stored in data/ (inside skill directory):
- profiles.json — Profile registry (active profile, all profile metadata)
- profiles/<id>/library.json — Notebook metadata (per-profile)
- profiles/<id>/auth_info.json — Authentication status (per-profile)
- profiles/<id>/browser_state/ — Browser cookies and session (per-profile)
Security: Protected by .gitignore — never commit to git.
Migration: Old flat layout (data/browser_state/, data/library.json) is auto-migrated to data/profiles/default/ on first run.
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 (~5–10 seconds per question)
Additional Resources
references/api-reference.md— Complete API for all scriptsreferences/research-guide.md— Research strategies and patternsreferences/troubleshooting.md— Auth issues, rate limits, browser crashesreferences/best-practices.md— Workflow patterns and question strategiesreferences/usage_patterns.md— Common usage patterns
Quick Reference
:: First-time setup (uses system Python once)
python install.py
:: All subsequent commands use .venv Python directly
.\run.bat auth_manager.py setup --name "My Account"
.\run.bat auth_manager.py list
.\run.bat auth_manager.py status
.\run.bat notebook_manager.py add --url URL --name NAME --description DESC --topics TOPICS
.\run.bat notebook_manager.py list
.\run.bat ask_question.py --question "Your question"
.\run.bat research_method.py --topics "Research topic" --depth comprehensive
.\run.bat cleanup_manager.py --preserve-library
