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 an account
`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>"

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:

Fetches notebook title from NotebookLM API
Queries the notebook content to generate description and topics
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:

Creates .venv if needed
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

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

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 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

nblm

NotebookLM Quick Commands

Environment

Usage

Commands

Notebook Management

Source Management

Chat & Audio/Media

Command Routing

Podcast Options

Slide Deck Options

Infographic Options

Media Generation

Examples

Download & Manage

Extended Documentation

When to Use This Skill

⚠️ CRITICAL: Add Command - Smart Discovery

Critical: Always Use run.py Wrapper

Core Workflow

Step 1: Check Authentication Status

Step 2: Authenticate (One-Time Setup)

Step 3: Manage Notebook Library

Quick Workflow

Step 4: Ask Questions

Follow-Up Mechanism (CRITICAL)

Z-Library Integration

Triggers

Setup (One-Time)

Commands

Script Reference

Authentication Management (auth_manager.py)

Notebook Management (notebook_manager.py)

Question Interface (ask_question.py)

Source Manager (source_manager.py)

Data Cleanup (cleanup_manager.py)

Watchdog Status (auth_manager.py)

Environment Management

Data Storage

Configuration

Decision Flow

Troubleshooting

Best Practices

Limitations

Resources (Skill Structure)

Authentication Management (`auth_manager.py`)

Notebook Management (`notebook_manager.py`)

Question Interface (`ask_question.py`)

Source Manager (`source_manager.py`)

Data Cleanup (`cleanup_manager.py`)

Watchdog Status (`auth_manager.py`)