notebooklm

name	notebooklm
description	Complete API for Google NotebookLM - full programmatic access including features not in the web UI. Create notebooks, add sources, generate all artifact types, download in multiple formats. Activates on explicit /notebooklm or intent like "create a podcast about X", "install notebooklm", "add notebooklm to cowork"
metadata	{"version":"1.0.0","author":"[e-mail]"}

NotebookLM Automation

Complete programmatic access to Google NotebookLM—including capabilities not exposed in the web UI. Create notebooks, add sources (URLs, YouTube, PDFs, audio, video, images), chat with content, generate all artifact types, and download results in multiple formats.

This skill covers the local Claude Code path: install the notebooklm-py CLI on your Mac and authenticate. Fast, direct, no network overhead.

Roadmap (not yet implemented): a Cowork integration — wrapping the CLI in an MCP server, tunneling it via Cloudflare, and connecting Cowork to the public HTTPS endpoint — is planned but not part of this skill yet. Until then, NotebookLM access is only available in local terminal sessions.

---

Step 0: Local Setup (Run Automatically on First Use)

When this skill is triggered and notebooklm is not yet installed or authenticated, complete setup first.

Pre-flight: Check Python Version

notebooklm-py requires Python 3.10+. Check the available version before installing:

python3 --version

If Python is below 3.10 (e.g. 3.9.x which is the macOS default), install a compatible version:

macOS (Homebrew):

brew install python@3.12

Then use /opt/homebrew/bin/python3.12 (Apple Silicon) or /usr/local/bin/python3.12 (Intel) for the venv below.

Linux (apt):

sudo apt update && sudo apt install -y python3.12 python3.12-venv

Install the CLI

Always use a virtual environment to avoid "externally-managed-environment" errors and PATH issues.

Determine which Python to use — if the system python3 is 3.10+, use it directly. Otherwise use the one you just installed (e.g. python3.12):

# Set PYTHON to the correct binary (adjust if needed)
PYTHON=$(command -v python3.12 2>/dev/null || command -v python3.11 2>/dev/null || command -v python3.10 2>/dev/null || command -v python3)

# Verify it's 3.10+
$PYTHON -c "import sys; assert sys.version_info >= (3,10), f'Python {sys.version} is too old — need 3.10+'; print(f'Using Python {sys.version}')"

# Create venv and install
$PYTHON -m venv ~/.notebooklm-venv
source ~/.notebooklm-venv/bin/activate
pip install "notebooklm-py[browser]"
playwright install chromium

Then symlink so it's always on PATH:

mkdir -p ~/bin
ln -sf ~/.notebooklm-venv/bin/notebooklm ~/bin/notebooklm
export PATH="$HOME/bin:$PATH"

# The export above only lasts for this shell session — make it persistent,
# otherwise `notebooklm` won't be found in future sessions:
grep -q 'HOME/bin' ~/.zshrc 2>/dev/null || echo 'export PATH="$HOME/bin:$PATH"' >> ~/.zshrc

Verify the CLI works:

notebooklm --help

Authenticate

IMPORTANT: The built-in notebooklm login command requires interactive terminal input (pressing Enter after sign-in). Claude Code's bash tool does NOT support interactive input, so notebooklm login will fail — the browser opens and closes instantly. Instead, use this custom login script.

Tell the user:

I'm going to open a browser window — just sign into your Google account and navigate to notebooklm.google.com. Take your time, I'll wait for you to confirm before closing it.

Then write and run this login script:

cat > /tmp/nlm_login.py << 'PYEOF'
import json, os, time
from pathlib import Path
from playwright.sync_api import sync_playwright

STORAGE_PATH = Path.home() / ".notebooklm" / "storage_state.json"
PROFILE_PATH = Path.home() / ".notebooklm" / "browser_profile"
SIGNAL_FILE = Path("/tmp/nlm_save_signal")
TIMEOUT_SECONDS = 300

SIGNAL_FILE.unlink(missing_ok=True)
STORAGE_PATH.parent.mkdir(parents=True, exist_ok=True)
os.chmod(STORAGE_PATH.parent, 0o700)

print("Opening browser for Google login...")
print("Sign in to Google and navigate to notebooklm.google.com")

with sync_playwright() as p:
    browser = p.chromium.launch_persistent_context(
        user_data_dir=str(PROFILE_PATH),
        headless=False,
        args=["--disable-blink-features=AutomationControlled"],
    )
    page = browser.pages[0] if browser.pages else browser.new_page()
    page.goto("https://notebooklm.google.com/")

    print("Browser is open. Waiting for save signal...")
    waited = 0
    while not SIGNAL_FILE.exists():
        if waited >= TIMEOUT_SECONDS:
            browser.close()
            print(f"ERROR: no save signal within {TIMEOUT_SECONDS}s — browser closed, nothing saved.")
            print("Re-run the login script and confirm sign-in before the timeout.")
            raise SystemExit(1)
        time.sleep(1)
        waited += 1

    print("Save signal received! Capturing session...")
    storage = browser.storage_state()
    with open(STORAGE_PATH, "w") as f:
        json.dump(storage, f)
    os.chmod(STORAGE_PATH, 0o600)

    cookie_names = [c["name"] for c in storage.get("cookies", [])]
    print(f"Saved {len(cookie_names)} cookies: {cookie_names}")
    if not any(n in ("SID", "__Secure-1PSID") for n in cookie_names):
        print("WARNING: no Google session cookie (SID / __Secure-1PSID) captured — login likely incomplete.")
        print("Delete ~/.notebooklm/storage_state.json and ~/.notebooklm/browser_profile, then retry.")
    browser.close()

SIGNAL_FILE.unlink(missing_ok=True)
print(f"Authentication saved to: {STORAGE_PATH}")
PYEOF

# Run the login script in the background
source ~/.notebooklm-venv/bin/activate
python3 /tmp/nlm_login.py > /tmp/nlm_login_output.txt 2>&1 &
echo "Login started (PID=$!). Browser should open in a few seconds..."

Wait ~10 seconds for the browser to open, then ask the user if they can see the browser and are signed in.

Once the user confirms they are on the NotebookLM homepage, save the session:

touch /tmp/nlm_save_signal
sleep 8
cat /tmp/nlm_login_output.txt

Then verify authentication:

export PATH="$HOME/bin:$PATH"
notebooklm auth check
notebooklm list

If auth passes (SID cookie present), confirm to the user that NotebookLM is set up and ready. Clean up the temp script:

rm -f /tmp/nlm_login.py /tmp/nlm_login_output.txt /tmp/nlm_save_signal

If auth fails (SID cookie missing), the user may not have fully signed in. Delete the browser profile and retry:

rm -rf ~/.notebooklm/browser_profile ~/.notebooklm/storage_state.json

Then run the login script again from the top.

---

When This Skill Activates

Explicit: User says "/notebooklm", "use notebooklm", "install notebooklm", or mentions the tool by name.

Intent detection: Recognize requests like:

• "Create a podcast about [topic]"
• "Summarize these URLs/documents"
• "Generate a quiz from my research"
• "Turn this into an audio overview"
• "Create flashcards for studying"
• "Generate a video explainer"
• "Make an infographic"
• "Create a mind map of the concepts"
• "Download the quiz as markdown"
• "Add these sources to NotebookLM"

Autonomy Rules

Run automatically (no confirmation):

• notebooklm status - check context
• notebooklm auth check - diagnose auth issues
• notebooklm list - list notebooks
• notebooklm source list - list sources
• notebooklm artifact list - list artifacts
• notebooklm language list - list supported languages
• notebooklm language get - get current language
• notebooklm language set - set language (global setting)
• notebooklm artifact wait - wait for artifact completion
• notebooklm source wait - wait for source processing
• notebooklm research status - check research status
• notebooklm research wait - wait for research
• notebooklm use <id> - set context
• notebooklm create - create notebook
• notebooklm ask "..." - chat queries (without --save-as-note)
• notebooklm history - display conversation history (read-only)
• notebooklm source add - add sources

Ask before running:

• notebooklm delete - destructive
• notebooklm generate * - long-running, may fail
• notebooklm download * - writes to filesystem
• notebooklm ask "..." --save-as-note - writes a note
• notebooklm history --save - writes a note

Quick Reference

Task	Command
List notebooks	notebooklm list
Create notebook	notebooklm create "Title"
Set context	notebooklm use <notebook_id>
Show context	notebooklm status
Add URL source	notebooklm source add "https://..."
Add file	notebooklm source add ./file.pdf
Add YouTube	notebooklm source add "https://youtube.com/..."
List sources	notebooklm source list
Wait for source processing	notebooklm source wait <source_id>
Web research (fast)	notebooklm source add-research "query"
Web research (deep)	notebooklm source add-research "query" --mode deep --no-wait
Check research status	notebooklm research status
Wait for research	notebooklm research wait --import-all
Chat	notebooklm ask "question"
Chat (specific sources)	notebooklm ask "question" -s src_id1 -s src_id2
Chat (with references)	notebooklm ask "question" --json
Chat (save answer as note)	notebooklm ask "question" --save-as-note
Show conversation history	notebooklm history
Save all history as note	notebooklm history --save
Get source fulltext	notebooklm source fulltext <source_id>
Generate podcast	notebooklm generate audio "instructions"
Generate video	notebooklm generate video "instructions"
Generate report	notebooklm generate report --format briefing-doc
Generate quiz	notebooklm generate quiz
Generate flashcards	notebooklm generate flashcards
Generate infographic	notebooklm generate infographic
Generate mind map	notebooklm generate mind-map
Generate slide deck	notebooklm generate slide-deck
Revise a slide	notebooklm generate revise-slide "prompt" --artifact <id> --slide 0
Check artifact status	notebooklm artifact list
Wait for completion	notebooklm artifact wait <artifact_id>
Download audio	notebooklm download audio ./output.mp3
Download video	notebooklm download video ./output.mp4
Download slide deck (PDF)	notebooklm download slide-deck ./slides.pdf
Download slide deck (PPTX)	notebooklm download slide-deck ./slides.pptx --format pptx
Download report	notebooklm download report ./report.md
Download mind map	notebooklm download mind-map ./map.json
Download data table	notebooklm download data-table ./data.csv
Download quiz	notebooklm download quiz quiz.json
Download flashcards	notebooklm download flashcards cards.json
List languages	notebooklm language list
Set language	notebooklm language set zh_Hans

Generation Types

All generate commands support:

• -s, --source to use specific source(s) instead of all sources
• --language to set output language (defaults to 'en')
• --json for machine-readable output
• --retry N to automatically retry on rate limits

Type	Command	Options	Download
Podcast	generate audio	--format [deep-dive|brief|critique|debate], --length [short|default|long]	.mp3
Video	generate video	--format [explainer|brief], --style [auto|classic|whiteboard|kawaii|anime|watercolor|retro-print|heritage|paper-craft]	.mp4
Slide Deck	generate slide-deck	--format [detailed|presenter], --length [default|short]	.pdf / .pptx
Slide Revision	generate revise-slide "prompt" --artifact <id> --slide N	--wait, --notebook	(re-downloads parent deck)
Infographic	generate infographic	--orientation [landscape|portrait|square], --detail [concise|standard|detailed]	.png
Report	generate report	--format [briefing-doc|study-guide|blog-post|custom], --append "extra instructions"	.md
Mind Map	generate mind-map	(sync, instant)	.json
Data Table	generate data-table	description required	.csv
Quiz	generate quiz	--difficulty [easy|medium|hard], --quantity [fewer|standard|more]	.json/.md/.html
Flashcards	generate flashcards	--difficulty [easy|medium|hard], --quantity [fewer|standard|more]	.json/.md/.html

Common Workflows

Research to Podcast

1. notebooklm create "Research: [topic]"
2. notebooklm source add for each URL/document
3. Wait for sources: notebooklm source list --json until all status=READY
4. notebooklm generate audio "Focus on [specific angle]"
5. Check notebooklm artifact list for status
6. notebooklm download audio ./podcast.mp3 when complete

Document Analysis

1. notebooklm create "Analysis: [project]"
2. notebooklm source add ./doc.pdf (or URLs)
3. notebooklm ask "Summarize the key points"
4. Continue chatting as needed

Second-Brain Pattern (the "AI Brain" workflow)

1. Create one permanent notebook called something like "AI Brain"
2. After every working session, append a summary as a new source
3. Add a project instruction: "Whenever answering questions about strategy, business context, or project history, always consult my NotebookLM AI Brain notebook first."
4. Claude now checks your second brain before answering — perfect recall of everything you've ever worked on

Output Formats (--json)

// notebooklm list --json
{"notebooks": [{"id": "...", "title": "...", "created_at": "..."}]}

// notebooklm source list --json
{"sources": [{"id": "...", "title": "...", "status": "ready|processing|error"}]}

// notebooklm artifact list --json
{"artifacts": [{"id": "...", "title": "...", "type": "Audio Overview", "status": "in_progress|pending|completed|unknown"}]}

Error Handling

Error	Cause	Action
Auth/cookie error	Session expired	Re-run the login script from Step 0
"No notebook context"	Context not set	Run notebooklm use <id>
Rate limiting	Google throttle	Wait 5-10 min, retry
Download fails	Generation incomplete	Check artifact list for status

Known Limitations

• Audio, video, quiz, flashcard, infographic, and slide deck generation may fail due to Google rate limits
• Generation times: audio 10-20 min, video 15-45 min, quiz/flashcards 5-15 min
• This is an unofficial API — Google can change things without warning
• The CLI binary is at ~/bin/notebooklm — ensure ~/bin is in PATH or call with full path