NotebookLM Quick Commands

Query Google NotebookLM for source-grounded, citation-backed answers.

Environment

All dependencies and authentication are handled automatically by run.py:

• First run creates .venv and installs Python/Node.js dependencies
• If Google auth is missing or expired, a browser window opens automatically
• No manual pre-flight steps required

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Usage

/nblm <command> [args]

Commands

Notebook Management

Command Description login Authenticate with Google status Show auth and library status accounts List all Google accounts accounts add Add a new Google account accounts switch <id> Switch active account (by index or email) accounts remove <id> Remove a Google account accounts use <id> Set agent-specific active account (OpenClaw isolation) accounts clear Clear agent-specific account override local List notebooks in local library remote List all notebooks from NotebookLM API create <name> Create a new notebook delete [--id ID] Delete a notebook rename <name> [--id ID] Rename a notebook summary [--id ID] Get AI-generated summary describe [--id ID] Get description and suggested topics add <url-or-id> Add notebook to local library (auto-detects URL vs notebook ID) activate <id> Set active notebook

Source Management

Command Description sources [--id ID] List sources in notebook upload <file> Upload a single file upload <folder> Sync a folder of files to NotebookLM upload-zlib <url> Download from Z-Library and upload upload-url <url> Add URL as source upload-youtube <url> Add YouTube video as source upload-text <title> [--content TEXT] Add text as source source-text <source-id> Get full indexed text source-guide <source-id> Get AI summary and keywords source-rename <source-id> <name> Rename a source source-refresh <source-id> Re-fetch URL content source-delete <source-id> Delete a source Upload options:

• --use-active - Upload to the currently active notebook
• --create-new - Create a new notebook named after the file/folder
• --notebook-id <id> - Upload to a specific notebook
• --dry-run - Show sync plan without executing (folder sync)
• --rebuild - Force rebuild tracking file (folder sync) Important: When user runs upload without specifying a target, ASK them first:

"Would you like to upload to the active notebook, or create a new notebook?" Then pass the appropriate flag (--use-active or --create-new).

Chat & Audio/Media

Command Description ask <question> Query NotebookLM podcast [--instructions TEXT] Generate audio podcast podcast-status <task-id> Check podcast generation status podcast-download [output-path] Download latest podcast briefing [--instructions TEXT] Generate brief audio summary debate [--instructions TEXT] Generate debate-style audio slides [--instructions TEXT] Generate slide deck slides-download [output-path] Download slide deck as PDF infographic [--instructions TEXT] Generate infographic infographic-download [output-path] Download infographic media-list [--type TYPE] List generated media (audio/video/slides/infographic) media-delete <id> Delete a generated media item

Command Routing

Based on $ARGUMENTS, execute the appropriate command: $IF($ARGUMENTS, Parse the command from: "$ARGUMENTS" login → python scripts/run.py auth_manager.py setup --service google accounts → python scripts/run.py auth_manager.py accounts list accounts add → python scripts/run.py auth_manager.py accounts add accounts switch → python scripts/run.py auth_manager.py accounts switch "<id>" accounts remove → python scripts/run.py auth_manager.py accounts remove "<id>" accounts use → python scripts/run.py auth_manager.py accounts use "<id>" accounts clear → python scripts/run.py auth_manager.py accounts clear status → Run both:

• python scripts/run.py auth_manager.py status
• python scripts/run.py notebook_manager.py list local → python scripts/run.py notebook_manager.py list remote → python scripts/run.py nblm_cli.py notebooks create → python scripts/run.py nblm_cli.py create "<name>" delete [--id ID] → python scripts/run.py nblm_cli.py delete <args> rename [--id ID] → python scripts/run.py nblm_cli.py rename "<name>" <args> summary [--id ID] → python scripts/run.py nblm_cli.py summary <args> describe [--id ID] → python scripts/run.py nblm_cli.py describe <args> add → Smart add workflow (auto-detects URL vs notebook ID) activate → python scripts/run.py notebook_manager.py activate --id "<id>" sources [--id ID] → python scripts/run.py nblm_cli.py sources <args> upload → First ASK user: "Upload to active notebook or create new?" Then: - Active: python scripts/run.py source_manager.py add --file "<file>" --use-active - New: python scripts/run.py source_manager.py add --file "<file>" --create-new upload → Sync a folder: - First ASK user: "Sync to active notebook, create new, or specify notebook?" - Active: python scripts/run.py source_manager.py sync "<folder>" --use-active - New: python scripts/run.py source_manager.py sync "<folder>" --create-new - Specific: python scripts/run.py source_manager.py sync "<folder>" --notebook-id ID - Dry-run: python scripts/run.py source_manager.py sync "<folder>" --dry-run - Rebuild: python scripts/run.py source_manager.py sync "<folder>" --rebuild upload-zlib → First ASK user: "Upload to active notebook or create new?" Then: - Active: python scripts/run.py source_manager.py add --url "<url>" --use-active - New: python scripts/run.py source_manager.py add --url "<url>" --create-new upload-url → python scripts/run.py nblm_cli.py upload-url "<url>" upload-youtube → python scripts/run.py nblm_cli.py upload-youtube "<url>" upload-text → python scripts/run.py nblm_cli.py upload-text "<title>" <args> source-text → python scripts/run.py nblm_cli.py source-text "<id>" source-guide → python scripts/run.py nblm_cli.py source-guide "<id>" source-rename → python scripts/run.py nblm_cli.py source-rename "<id>" "<name>" source-refresh → python scripts/run.py nblm_cli.py source-refresh "<id>" source-delete → python scripts/run.py nblm_cli.py source-delete "<id>" ask → python scripts/run.py nblm_cli.py ask "<question>" podcast → python scripts/run.py artifact_manager.py generate --format DEEP_DIVE <args> podcast-status → python scripts/run.py artifact_manager.py status --task-id "<task-id>" podcast-download [output-path] → python scripts/run.py artifact_manager.py download "<output-path>" briefing → python scripts/run.py artifact_manager.py generate --format BRIEF <args> debate → python scripts/run.py artifact_manager.py generate --format DEBATE <args> slides → python scripts/run.py artifact_manager.py generate-slides <args> slides-download [output-path] → python scripts/run.py artifact_manager.py download "<output-path>" --type slide-deck infographic → python scripts/run.py artifact_manager.py generate-infographic <args> infographic-download [output-path] → python scripts/run.py artifact_manager.py download "<output-path>" --type infographic media-list [--type TYPE] → python scripts/run.py artifact_manager.py list <args> media-delete → python scripts/run.py artifact_manager.py delete "<id>" If command not recognized, show usage help., Show available commands with /nblm (no arguments) )

Podcast Options

/nblm podcast --length DEFAULT --wait --output ./podcast.mp3
/nblm podcast --instructions "Focus on the key findings"
/nblm briefing --wait --output ./summary.mp3
/nblm debate --instructions "Compare the two approaches"

Option Values --length SHORT, DEFAULT, LONG --instructions Custom instructions for the content --wait Wait for generation to complete --output Download path (requires --wait)

Slide Deck Options

/nblm slides --format DETAILED_DECK --wait --output ./presentation.pdf
/nblm slides --instructions "Focus on key diagrams" --format PRESENTER_SLIDES

Option Values --format DETAILED_DECK, PRESENTER_SLIDES --length SHORT, DEFAULT --instructions Custom instructions for the content --wait Wait for generation to complete --output Download path (requires --wait)

Infographic Options

/nblm infographic --orientation LANDSCAPE --wait --output ./visual.png
/nblm infographic --instructions "Highlight comparison" --detail-level DETAILED

Option Values --orientation LANDSCAPE, PORTRAIT, SQUARE --detail-level CONCISE, STANDARD, DETAILED --instructions Custom instructions for the content --wait Wait for generation to complete --output Download path (requires --wait)

Media Generation

Command Description Output /nblm podcast Deep-dive audio discussion MP3 /nblm briefing Brief audio summary MP3 /nblm debate Debate-style audio MP3 /nblm slides Slide deck presentation PDF /nblm infographic Visual infographic PNG

Examples

/nblm podcast --wait --output ./deep-dive.mp3
/nblm briefing --instructions "Focus on chapter 3" --wait
/nblm debate --length LONG --wait --output ./debate.mp3
/nblm slides --instructions "Include key diagrams" --format DETAILED_DECK --wait --output ./presentation.pdf
/nblm infographic --orientation LANDSCAPE --detail-level DETAILED --wait --output ./summary.png

Download & Manage

/nblm podcast-download ./my-podcast.mp3
/nblm slides-download ./presentation.pdf
/nblm infographic-download ./visual.png
/nblm media-list                     # List all generated media
/nblm media-list --type audio        # List only audio
/nblm media-delete <id>              # Delete a media item

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Extended Documentation

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

The add command now automatically discovers metadata from the notebook:

# Smart Add (auto-discovers name, description, topics)
python scripts/run.py notebook_manager.py add <notebook-id-or-url>
# With optional overrides
python scripts/run.py notebook_manager.py add <id> --name "Custom Name" --topics "custom,topics"

What Smart Add does:

1. Fetches notebook title from NotebookLM API
2. Queries the notebook content to generate description and topics
3. Adds to local library with discovered metadata Supported input formats:

• Notebook ID: 5fd9f36b-8000-401d-a7a0-7aa3f7832644
• Full URL: https://notebooklm.google.com/notebook/5fd9f36b-8000-401d-a7a0-7aa3f7832644 NEVER manually specify --name, --description, or --topics unless the user explicitly provides 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:

1. Creates .venv if needed
2. Installs all dependencies
3. Activates environment
4. 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

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

# 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:

   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

Z-Library Integration

Triggers

• User provides Z-Library URL (zlib.li, z-lib.org, zh.zlib.li)
• User says "download this book to NotebookLM"
• User says "add this book from Z-Library"

Setup (One-Time)

# Authenticate with Z-Library
python scripts/run.py auth_manager.py setup --service zlibrary

Commands

# Add book from Z-Library
python scripts/run.py source_manager.py add --url "https://zh.zlib.li/book/..."
# Check Z-Library auth status
python scripts/run.py auth_manager.py status --service zlibrary

Script Reference

Authentication Management (auth_manager.py)

python scripts/run.py auth_manager.py setup                    # Default: Google
python scripts/run.py auth_manager.py setup --service google
python scripts/run.py auth_manager.py setup --service zlibrary
python scripts/run.py auth_manager.py status                   # Show all services
python scripts/run.py auth_manager.py status --service zlibrary
python scripts/run.py auth_manager.py clear --service zlibrary # Clear auth
# Multi-Account Management (Google)
python scripts/run.py auth_manager.py accounts list             # List all accounts
python scripts/run.py auth_manager.py accounts add              # Add new account
python scripts/run.py auth_manager.py accounts switch 1         # Switch by index
python scripts/run.py auth_manager.py accounts switch user@gmail.com  # Switch by email
python scripts/run.py auth_manager.py accounts remove 2         # Remove account

Notebook Management (notebook_manager.py)

python scripts/run.py notebook_manager.py add --url URL --name NAME --description DESC --topics TOPICS
# OR use notebook ID directly:
python scripts/run.py notebook_manager.py add --notebook-id ID --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)

python scripts/run.py ask_question.py --question "..." [--notebook-id ID] [--notebook-url URL] [--show-browser]

Source Manager (source_manager.py)

# Upload to active notebook
python scripts/run.py source_manager.py add --file "/path/to/book.pdf" --use-active
# Create new notebook for upload
python scripts/run.py source_manager.py add --file "/path/to/book.pdf" --create-new
# Upload to specific notebook
python scripts/run.py source_manager.py add --file "/path/to/book.pdf" --notebook-id NOTEBOOK_ID
# Z-Library download and upload
python scripts/run.py source_manager.py add --url "https://zh.zlib.li/book/..." --use-active
python scripts/run.py source_manager.py add --url "https://zh.zlib.li/book/..." --create-new
# Sync a folder (new!)
python scripts/run.py source_manager.py sync "/path/to/docs" --use-active
python scripts/run.py source_manager.py sync "/path/to/docs" --create-new
python scripts/run.py source_manager.py sync "/path/to/docs" --notebook-id NOTEBOOK_ID
# Sync options (new!)
python scripts/run.py source_manager.py sync "/path/to/docs" --dry-run    # Preview only
python scripts/run.py source_manager.py sync "/path/to/docs" --rebuild   # Force re-hash all files

Folder Sync:

• Scans folder for supported types: PDF, TXT, MD, DOCX, HTML, EPUB
• Tracks sync state internally (no per-folder tracking file to manage)
• Sync strategy: add new, update modified (delete + re-upload), skip unchanged
• Multi-account aware (tracks which Google account was used) Note: One of --use-active, --create-new, or --notebook-id is REQUIRED. Uploads wait for NotebookLM processing and print progress as Ready: N/T. Press Ctrl+C to stop waiting. Local file uploads use browser automation and require Google authentication. If browser automation is unavailable, set NOTEBOOKLM_UPLOAD_MODE=text to upload extracted text instead (PDFs require pypdf).

Data Cleanup (cleanup_manager.py)

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

Watchdog Status (auth_manager.py)

python scripts/run.py auth_manager.py watchdog-status

Environment Management

The virtual environment is automatically managed:

• First run creates .venv automatically
• Dependencies install automatically
• Node.js dependencies install automatically
• agent-browser daemon starts on demand and keeps browser state in memory
• daemon stops after 10 minutes of inactivity (any agent-browser command resets the timer)
• set AGENT_BROWSER_OWNER_PID to auto-stop when the agent process exits
• scripts/run.py sets AGENT_BROWSER_OWNER_PID to its parent PID by default
• 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
npm install
npm run install-browsers

Data Storage

All data stored in ~/.claude/skills/notebooklm/data/:

• library.json - Notebook metadata (with account associations)
• auth/google/ - Multi-account Google auth
  • index.json - Account index (active account, list)
  • <n>-<email>.json - Per-account credentials
• auth/zlibrary.json - Z-Library auth state
• agent_browser/session_id - Current daemon session ID
• agent_browser/last_activity.json - Last activity timestamp for idle shutdown
• agent_browser/watchdog.pid - Idle watchdog process ID 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 run.py wrapper Authentication fails Browser must be visible for setup! --show-browser DAEMON_UNAVAILABLE Ensure Node.js/npm installed, run npm install, retry AUTH_REQUIRED Run python scripts/run.py auth_manager.py setup ELEMENT_NOT_FOUND Verify notebook URL and re-run with fresh page load Rate limit (50/day) Wait or add another Google account with accounts add Browser crashes python scripts/run.py cleanup_manager.py --preserve-library Notebook not found Check with notebook_manager.py list

Best Practices

1. Always use run.py - Handles environment automatically
2. Check auth first - Before any operations
3. Follow-up questions - Don't stop at first answer
4. Browser visible for auth - Required for manual login
5. Include context - Each question is independent
6. Synthesize answers - Combine multiple responses

Limitations

• No session persistence (each question = new browser)
• Rate limits on free Google accounts (50 queries/day per account; use multiple accounts to increase)
• Manual upload required (user must add docs to NotebookLM)
• Browser overhead (few seconds per question)

Resources (Skill Structure)

Important directories and files:

• scripts/ - All automation scripts (ask_question.py, notebook_manager.py, etc.)
• data/ - Local storage for authentication and notebook library
• references/ - Extended documentation:
  • api_reference.md - Detailed API documentation for all scripts
  • troubleshooting.md - Common issues and solutions
  • usage_patterns.md - Best practices and workflow examples
• .venv/ - Isolated Python environment (auto-created on first run)
• .gitignore - Protects sensitive data from being committed

GitHub Owner

Owner: magicseek

SKILL.md

---

name: nblm description: 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.

NotebookLM Quick Commands

Query Google NotebookLM for source-grounded, citation-backed answers.

Environment

All dependencies and authentication are handled automatically by run.py:

• First run creates .venv and installs Python/Node.js dependencies
• If Google auth is missing or expired, a browser window opens automatically
• No manual pre-flight steps required

---

Usage

/nblm <command> [args]

Commands

Notebook Management

Command	Description
login	Authenticate with Google
status	Show auth and library status
accounts	List all Google accounts
accounts add	Add a new Google account
accounts switch <id>	Switch active account (by index or email)
accounts remove <id>	Remove a Google account
accounts use <id>	Set agent-specific active account (OpenClaw isolation)
accounts clear	Clear agent-specific account override
local	List notebooks in local library
remote	List all notebooks from NotebookLM API
create <name>	Create a new notebook
delete [--id ID]	Delete a notebook
rename <name> [--id ID]	Rename a notebook
summary [--id ID]	Get AI-generated summary
describe [--id ID]	Get description and suggested topics
add <url-or-id>	Add notebook to local library (auto-detects URL vs notebook ID)
activate <id>	Set active notebook

Source Management

Command	Description
sources [--id ID]	List sources in notebook
upload <file>	Upload a single file
upload <folder>	Sync a folder of files to NotebookLM
upload-zlib <url>	Download from Z-Library and upload
upload-url <url>	Add URL as source
upload-youtube <url>	Add YouTube video as source
upload-text <title> [--content TEXT]	Add text as source
source-text <source-id>	Get full indexed text
source-guide <source-id>	Get AI summary and keywords
source-rename <source-id> <name>	Rename a source
source-refresh <source-id>	Re-fetch URL content
source-delete <source-id>	Delete a source
Upload options:

• --use-active - Upload to the currently active notebook
• --create-new - Create a new notebook named after the file/folder
• --notebook-id <id> - Upload to a specific notebook
• --dry-run - Show sync plan without executing (folder sync)
• --rebuild - Force rebuild tracking file (folder sync) Important: When user runs upload without specifying a target, ASK them first:

"Would you like to upload to the active notebook, or create a new notebook?" Then pass the appropriate flag (--use-active or --create-new).

Chat & Audio/Media

Command	Description
ask <question>	Query NotebookLM
podcast [--instructions TEXT]	Generate audio podcast
podcast-status <task-id>	Check podcast generation status
podcast-download [output-path]	Download latest podcast
briefing [--instructions TEXT]	Generate brief audio summary
debate [--instructions TEXT]	Generate debate-style audio
slides [--instructions TEXT]	Generate slide deck
slides-download [output-path]	Download slide deck as PDF
infographic [--instructions TEXT]	Generate infographic
infographic-download [output-path]	Download infographic
media-list [--type TYPE]	List generated media (audio/video/slides/infographic)
media-delete <id>	Delete a generated media item

Command Routing

Based on $ARGUMENTS, execute the appropriate command: $IF($ARGUMENTS, Parse the command from: "$ARGUMENTS" login → python scripts/run.py auth_manager.py setup --service google accounts → python scripts/run.py auth_manager.py accounts list accounts add → python scripts/run.py auth_manager.py accounts add accounts switch → python scripts/run.py auth_manager.py accounts switch "<id>" accounts remove → python scripts/run.py auth_manager.py accounts remove "<id>" accounts use → python scripts/run.py auth_manager.py accounts use "<id>" accounts clear → python scripts/run.py auth_manager.py accounts clear status → Run both:

• python scripts/run.py auth_manager.py status
• python scripts/run.py notebook_manager.py list local → python scripts/run.py notebook_manager.py list remote → python scripts/run.py nblm_cli.py notebooks create → python scripts/run.py nblm_cli.py create "<name>" delete [--id ID] → python scripts/run.py nblm_cli.py delete <args> rename [--id ID] → python scripts/run.py nblm_cli.py rename "<name>" <args> summary [--id ID] → python scripts/run.py nblm_cli.py summary <args> describe [--id ID] → python scripts/run.py nblm_cli.py describe <args> add → Smart add workflow (auto-detects URL vs notebook ID) activate → python scripts/run.py notebook_manager.py activate --id "<id>" sources [--id ID] → python scripts/run.py nblm_cli.py sources <args> upload → First ASK user: "Upload to active notebook or create new?" Then:
  • Active: python scripts/run.py source_manager.py add --file "<file>" --use-active
  • New: python scripts/run.py source_manager.py add --file "<file>" --create-new upload → Sync a folder:
  • First ASK user: "Sync to active notebook, create new, or specify notebook?"
  • Active: python scripts/run.py source_manager.py sync "<folder>" --use-active
  • New: python scripts/run.py source_manager.py sync "<folder>" --create-new
  • Specific: python scripts/run.py source_manager.py sync "<folder>" --notebook-id ID
  • Dry-run: python scripts/run.py source_manager.py sync "<folder>" --dry-run
  • Rebuild: python scripts/run.py source_manager.py sync "<folder>" --rebuild upload-zlib → First ASK user: "Upload to active notebook or create new?" Then:
  • Active: python scripts/run.py source_manager.py add --url "<url>" --use-active
  • New: python scripts/run.py source_manager.py add --url "<url>" --create-new upload-url → python scripts/run.py nblm_cli.py upload-url "<url>" upload-youtube → python scripts/run.py nblm_cli.py upload-youtube "<url>" upload-text → python scripts/run.py nblm_cli.py upload-text "<title>" <args> source-text → python scripts/run.py nblm_cli.py source-text "<id>" source-guide → python scripts/run.py nblm_cli.py source-guide "<id>" source-rename → python scripts/run.py nblm_cli.py source-rename "<id>" "<name>" source-refresh → python scripts/run.py nblm_cli.py source-refresh "<id>" source-delete → python scripts/run.py nblm_cli.py source-delete "<id>" ask → python scripts/run.py nblm_cli.py ask "<question>" podcast → python scripts/run.py artifact_manager.py generate --format DEEP_DIVE <args> podcast-status → python scripts/run.py artifact_manager.py status --task-id "<task-id>" podcast-download [output-path] → python scripts/run.py artifact_manager.py download "<output-path>" briefing → python scripts/run.py artifact_manager.py generate --format BRIEF <args> debate → python scripts/run.py artifact_manager.py generate --format DEBATE <args> slides → python scripts/run.py artifact_manager.py generate-slides <args> slides-download [output-path] → python scripts/run.py artifact_manager.py download "<output-path>" --type slide-deck infographic → python scripts/run.py artifact_manager.py generate-infographic <args> infographic-download [output-path] → python scripts/run.py artifact_manager.py download "<output-path>" --type infographic media-list [--type TYPE] → python scripts/run.py artifact_manager.py list <args> media-delete → python scripts/run.py artifact_manager.py delete "<id>" If command not recognized, show usage help., Show available commands with /nblm (no arguments) )

Podcast Options

/nblm podcast --length DEFAULT --wait --output ./podcast.mp3
/nblm podcast --instructions "Focus on the key findings"
/nblm briefing --wait --output ./summary.mp3
/nblm debate --instructions "Compare the two approaches"

Option	Values
--length	SHORT, DEFAULT, LONG
--instructions	Custom instructions for the content
--wait	Wait for generation to complete
--output	Download path (requires --wait)

Slide Deck Options

/nblm slides --format DETAILED_DECK --wait --output ./presentation.pdf
/nblm slides --instructions "Focus on key diagrams" --format PRESENTER_SLIDES

Option	Values
--format	DETAILED_DECK, PRESENTER_SLIDES
--length	SHORT, DEFAULT
--instructions	Custom instructions for the content
--wait	Wait for generation to complete
--output	Download path (requires --wait)

Infographic Options

/nblm infographic --orientation LANDSCAPE --wait --output ./visual.png
/nblm infographic --instructions "Highlight comparison" --detail-level DETAILED

Option	Values
--orientation	LANDSCAPE, PORTRAIT, SQUARE
--detail-level	CONCISE, STANDARD, DETAILED
--instructions	Custom instructions for the content
--wait	Wait for generation to complete
--output	Download path (requires --wait)

Media Generation

Command	Description	Output
/nblm podcast	Deep-dive audio discussion	MP3
/nblm briefing	Brief audio summary	MP3
/nblm debate	Debate-style audio	MP3
/nblm slides	Slide deck presentation	PDF
/nblm infographic	Visual infographic	PNG

Examples

/nblm podcast --wait --output ./deep-dive.mp3
/nblm briefing --instructions "Focus on chapter 3" --wait
/nblm debate --length LONG --wait --output ./debate.mp3
/nblm slides --instructions "Include key diagrams" --format DETAILED_DECK --wait --output ./presentation.pdf
/nblm infographic --orientation LANDSCAPE --detail-level DETAILED --wait --output ./summary.png

Download & Manage

/nblm podcast-download ./my-podcast.mp3
/nblm slides-download ./presentation.pdf
/nblm infographic-download ./visual.png
/nblm media-list                     # List all generated media
/nblm media-list --type audio        # List only audio
/nblm media-delete <id>              # Delete a media item

---

Extended Documentation

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

The add command now automatically discovers metadata from the notebook:

# Smart Add (auto-discovers name, description, topics)
python scripts/run.py notebook_manager.py add <notebook-id-or-url>
# With optional overrides
python scripts/run.py notebook_manager.py add <id> --name "Custom Name" --topics "custom,topics"

What Smart Add does:

1. Fetches notebook title from NotebookLM API
2. Queries the notebook content to generate description and topics
3. Adds to local library with discovered metadata Supported input formats:

• Notebook ID: 5fd9f36b-8000-401d-a7a0-7aa3f7832644
• Full URL: https://notebooklm.google.com/notebook/5fd9f36b-8000-401d-a7a0-7aa3f7832644 NEVER manually specify --name, --description, or --topics unless the user explicitly provides 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:

1. Creates .venv if needed
2. Installs all dependencies
3. Activates environment
4. 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

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

# 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:

   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

Z-Library Integration

Triggers

• User provides Z-Library URL (zlib.li, z-lib.org, zh.zlib.li)
• User says "download this book to NotebookLM"
• User says "add this book from Z-Library"

Setup (One-Time)

# Authenticate with Z-Library
python scripts/run.py auth_manager.py setup --service zlibrary

Commands

# Add book from Z-Library
python scripts/run.py source_manager.py add --url "https://zh.zlib.li/book/..."
# Check Z-Library auth status
python scripts/run.py auth_manager.py status --service zlibrary

Script Reference

Authentication Management (auth_manager.py)

python scripts/run.py auth_manager.py setup                    # Default: Google
python scripts/run.py auth_manager.py setup --service google
python scripts/run.py auth_manager.py setup --service zlibrary
python scripts/run.py auth_manager.py status                   # Show all services
python scripts/run.py auth_manager.py status --service zlibrary
python scripts/run.py auth_manager.py clear --service zlibrary # Clear auth
# Multi-Account Management (Google)
python scripts/run.py auth_manager.py accounts list             # List all accounts
python scripts/run.py auth_manager.py accounts add              # Add new account
python scripts/run.py auth_manager.py accounts switch 1         # Switch by index
python scripts/run.py auth_manager.py accounts switch user@gmail.com  # Switch by email
python scripts/run.py auth_manager.py accounts remove 2         # Remove account

Notebook Management (notebook_manager.py)

python scripts/run.py notebook_manager.py add --url URL --name NAME --description DESC --topics TOPICS
# OR use notebook ID directly:
python scripts/run.py notebook_manager.py add --notebook-id ID --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)

python scripts/run.py ask_question.py --question "..." [--notebook-id ID] [--notebook-url URL] [--show-browser]

Source Manager (source_manager.py)

# Upload to active notebook
python scripts/run.py source_manager.py add --file "/path/to/book.pdf" --use-active
# Create new notebook for upload
python scripts/run.py source_manager.py add --file "/path/to/book.pdf" --create-new
# Upload to specific notebook
python scripts/run.py source_manager.py add --file "/path/to/book.pdf" --notebook-id NOTEBOOK_ID
# Z-Library download and upload
python scripts/run.py source_manager.py add --url "https://zh.zlib.li/book/..." --use-active
python scripts/run.py source_manager.py add --url "https://zh.zlib.li/book/..." --create-new
# Sync a folder (new!)
python scripts/run.py source_manager.py sync "/path/to/docs" --use-active
python scripts/run.py source_manager.py sync "/path/to/docs" --create-new
python scripts/run.py source_manager.py sync "/path/to/docs" --notebook-id NOTEBOOK_ID
# Sync options (new!)
python scripts/run.py source_manager.py sync "/path/to/docs" --dry-run    # Preview only
python scripts/run.py source_manager.py sync "/path/to/docs" --rebuild   # Force re-hash all files

Folder Sync:

• Scans folder for supported types: PDF, TXT, MD, DOCX, HTML, EPUB
• Tracks sync state internally (no per-folder tracking file to manage)
• Sync strategy: add new, update modified (delete + re-upload), skip unchanged
• Multi-account aware (tracks which Google account was used) Note: One of --use-active, --create-new, or --notebook-id is REQUIRED. Uploads wait for NotebookLM processing and print progress as Ready: N/T. Press Ctrl+C to stop waiting. Local file uploads use browser automation and require Google authentication. If browser automation is unavailable, set NOTEBOOKLM_UPLOAD_MODE=text to upload extracted text instead (PDFs require pypdf).

Data Cleanup (cleanup_manager.py)

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

Watchdog Status (auth_manager.py)

python scripts/run.py auth_manager.py watchdog-status

Environment Management

The virtual environment is automatically managed:

• First run creates .venv automatically
• Dependencies install automatically
• Node.js dependencies install automatically
• agent-browser daemon starts on demand and keeps browser state in memory
• daemon stops after 10 minutes of inactivity (any agent-browser command resets the timer)
• set AGENT_BROWSER_OWNER_PID to auto-stop when the agent process exits
• scripts/run.py sets AGENT_BROWSER_OWNER_PID to its parent PID by default
• 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
npm install
npm run install-browsers

Data Storage

All data stored in ~/.claude/skills/notebooklm/data/:

• library.json - Notebook metadata (with account associations)
• auth/google/ - Multi-account Google auth
  • index.json - Account index (active account, list)
  • <n>-<email>.json - Per-account credentials
• auth/zlibrary.json - Z-Library auth state
• agent_browser/session_id - Current daemon session ID
• agent_browser/last_activity.json - Last activity timestamp for idle shutdown
• agent_browser/watchdog.pid - Idle watchdog process ID 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 run.py wrapper
Authentication fails	Browser must be visible for setup! --show-browser
DAEMON_UNAVAILABLE	Ensure Node.js/npm installed, run npm install, retry
AUTH_REQUIRED	Run python scripts/run.py auth_manager.py setup
ELEMENT_NOT_FOUND	Verify notebook URL and re-run with fresh page load
Rate limit (50/day)	Wait or add another Google account with accounts add
Browser crashes	python scripts/run.py cleanup_manager.py --preserve-library
Notebook not found	Check with notebook_manager.py list

Best Practices

1. Always use run.py - Handles environment automatically
2. Check auth first - Before any operations
3. Follow-up questions - Don't stop at first answer
4. Browser visible for auth - Required for manual login
5. Include context - Each question is independent
6. Synthesize answers - Combine multiple responses

Limitations

• No session persistence (each question = new browser)
• Rate limits on free Google accounts (50 queries/day per account; use multiple accounts to increase)
• Manual upload required (user must add docs to NotebookLM)
• Browser overhead (few seconds per question)

Resources (Skill Structure)

Important directories and files:

• scripts/ - All automation scripts (ask_question.py, notebook_manager.py, etc.)
• data/ - Local storage for authentication and notebook library
• references/ - Extended documentation:
  • api_reference.md - Detailed API documentation for all scripts
  • troubleshooting.md - Common issues and solutions
  • usage_patterns.md - Best practices and workflow examples
• .venv/ - Isolated Python environment (auto-created on first run)
• .gitignore - Protects sensitive data from being committed