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:

• 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