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Notebooklm

Skill bg-szy/TOP-SKILLS/skills/claude-code-skills/notebooklm

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Install
npx -y skills add bg-szy/TOP-SKILLS --skill notebooklm

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Programmatic access to Google NotebookLM via the notebooklm-py CLI and Python API. Use this skill whenever the user wants to create notebooks, add sources (URLs, YouTube, PDFs, files), generate audio overviews/podcasts, videos, slide decks, quizzes, flashcards, infographics, reports, mind maps, or data tables from their research materials. Also use when the user mentions NotebookLM, wants to turn documents into podcasts, generate study materials, or automate any NotebookLM workflow — even if they don't explicitly say "NotebookLM". Triggers on: podcast from documents, audio overview, NotebookLM, notebook research, generate quiz from PDF, flashcards from notes, study materials, deep dive audio.

SKILL.md

9.7 KB, ~2.2k tokens by cl100k_base, as published. Nobody here has run it

NotebookLM Automation

Unofficial Python CLI and API for Google NotebookLM (notebooklm-py). Provides full programmatic access including capabilities the web UI doesn't expose.

Prerequisites

  • Python 3.10+
  • Google account with NotebookLM access
  • One-time browser login via Playwright

Installation

# Install with browser login support
pip install "notebooklm-py[browser]"
playwright install chromium

# Linux only: also run
playwright install-deps chromium

Authentication

First-time setup requires browser login:

notebooklm login
# Opens Chromium → sign into Google → press Enter when done
# Session saved to ~/.notebooklm/storage_state.json

Check auth status: notebooklm auth check --test

For headless/CI environments, copy storage_state.json from a local machine or set NOTEBOOKLM_AUTH_JSON env var.

Environment Variables

VariableDescriptionDefault
NOTEBOOKLM_HOMEConfig directory~/.notebooklm
NOTEBOOKLM_AUTH_JSONInline auth JSON (CI/CD)
NOTEBOOKLM_LOG_LEVELDEBUG/INFO/WARNING/ERRORWARNING
NOTEBOOKLM_DEBUG_RPCEnable RPC debug (1)false

Core Workflow

The typical workflow is: create notebook → add sources → generate content → download.

1. Notebook Management

notebooklm create "My Research"       # Create notebook
notebooklm list                        # List all notebooks
notebooklm use <id>                    # Set active notebook (supports partial ID)
notebooklm summary                     # AI summary of current notebook
notebooklm rename "New Title"          # Rename
notebooklm delete <id>                 # Delete

2. Adding Sources

Sources are auto-detected by type:

notebooklm source add "https://example.com/article"          # URL
notebooklm source add "https://youtube.com/watch?v=..."       # YouTube
notebooklm source add ./document.pdf                           # File (PDF, MD, DOCX, TXT, audio, video, images)
notebooklm source add-drive <drive-file-id> "Title"           # Google Drive
notebooklm source add-research "climate policy" --mode deep --import-all  # Research agent

Other source commands:

notebooklm source list                # List sources
notebooklm source fulltext <id>       # Get source full text
notebooklm source guide <id>          # AI-generated source guide
notebooklm source rename <id> "New"   # Rename
notebooklm source refresh <id>        # Re-fetch URL source
notebooklm source delete <id>         # Delete

3. Chat / Q&A

notebooklm ask "What are the key findings?" -s <source_id>
notebooklm ask "Compare sources" --json --save-as-note --note-title "Comparison"
notebooklm history                     # View chat history
notebooklm history --save              # Save history as note

4. Content Generation

All generate commands support: -s/--source (repeatable, limit to specific sources), --json, --language, --retry N.

Most are async — use --wait to block until complete.

Audio Overviews (Podcasts)

notebooklm generate audio "Focus on practical applications" \
  --format deep-dive \    # deep-dive | brief | critique | debate
  --length long \         # short | default | long
  --wait

Video Overviews

notebooklm generate video "Explain the architecture" \
  --format explainer \    # explainer | brief
  --style whiteboard \    # auto | classic | whiteboard | kawaii | anime | watercolor | retro-print | heritage | paper-craft
  --wait

Slide Decks

notebooklm generate slide-deck "Executive summary" \
  --format detailed \     # detailed | presenter
  --length default \      # default | short
  --wait

# Revise a specific slide
notebooklm generate revise-slide "Add more data points" \
  -a <artifact_id> --slide 2 --wait    # slide is zero-based

Study Materials

# Quizzes
notebooklm generate quiz --difficulty hard --quantity more --wait

# Flashcards
notebooklm generate flashcards --difficulty medium --wait

Visual & Data

# Infographic
notebooklm generate infographic \
  --orientation landscape \   # landscape | portrait | square
  --detail detailed \         # concise | standard | detailed
  --wait

# Mind map (synchronous, no --wait needed)
notebooklm generate mind-map

# Data table
notebooklm generate data-table "Compare metrics across studies" --wait

Reports

notebooklm generate report "Security analysis" \
  --format briefing-doc \     # briefing-doc | study-guide | blog-post | custom
  --append "Include threat modeling" \
  --wait

5. Downloading Content

All download commands support: -a/--artifact, --all, --latest, --earliest, --name, --force, --no-clobber, --dry-run, --json.

notebooklm download audio ./podcast.mp3
notebooklm download video ./overview.mp4
notebooklm download slide-deck ./slides.pptx --format pptx   # or pdf (default)
notebooklm download infographic ./info.png
notebooklm download report ./report.md
notebooklm download mind-map ./map.json
notebooklm download data-table ./data.csv
notebooklm download quiz --format json ./quiz.json       # json | markdown | html
notebooklm download flashcards --format markdown ./cards.md

6. Sharing

notebooklm share status
notebooklm share public --enable           # Create public link
notebooklm share view-level full           # full | chat
notebooklm share add [email protected] --permission editor -m "Check this out"
notebooklm share remove [email protected]

7. Language

notebooklm language list                   # 80+ languages
notebooklm language get
notebooklm language set ja                 # Set to Japanese

Python API

Fully async API for programmatic workflows:

import asyncio
from notebooklm import NotebookLMClient

async def main():
    async with await NotebookLMClient.from_storage() as client:
        # Create notebook and add sources
        nb = await client.notebooks.create("Research")
        await client.sources.add_url(nb.id, "https://example.com")

        # Generate audio overview
        artifact = await client.artifacts.generate_audio(
            nb.id, description="Deep dive on findings",
            format=AudioFormat.DEEP_DIVE, length=AudioLength.LONG
        )

        # Wait and download
        await client.artifacts.wait(nb.id, artifact.id)
        await client.artifacts.download_audio(nb.id, artifact.id, "output.mp3")

        # Chat with sources
        result = await client.chat.ask(nb.id, "Summarize key points")
        print(result.answer)

asyncio.run(main())

API modules: client.notebooks, client.sources, client.artifacts, client.chat, client.research, client.notes, client.settings, client.sharing

Common Recipes

Research-to-Podcast Pipeline

notebooklm create "Climate Research"
notebooklm use <id>
notebooklm source add "https://en.wikipedia.org/wiki/Climate_change"
notebooklm source add-research "climate change solutions 2025" --mode deep --import-all
notebooklm generate audio "Focus on actionable solutions" --format debate --length long --wait
notebooklm download audio ./climate-debate.mp3

Document Analysis to Study Materials

notebooklm create "Exam Prep"
notebooklm use <id>
notebooklm source add ./textbook.pdf
notebooklm generate quiz --difficulty hard --quantity more --wait
notebooklm generate flashcards --wait
notebooklm download quiz --format markdown ./quiz.md
notebooklm download flashcards --format json ./cards.json

Batch Import + Full Report

notebooklm create "Literature Review"
notebooklm use <id>
for f in ./papers/*.pdf; do notebooklm source add "$f"; done
notebooklm generate report "Systematic review" --format briefing-doc --wait
notebooklm download report ./review.md

Troubleshooting

IssueFix
Auth expiredRun notebooklm login again
playwright not foundpip install "notebooklm-py[browser]" then playwright install chromium
Generation stuckUse notebooklm source wait <id> for pending sources, check --retry flag
Partial ID not matchingUse more characters of the notebook ID
Debug API callsSet NOTEBOOKLM_LOG_LEVEL=DEBUG or NOTEBOOKLM_DEBUG_RPC=1

Gotchas

  • Source upload >200MB silently fails after the request returns 200 — downstream shows "processing" forever. Pre-check file size before upload.
  • Concurrent audio/video generation per project is rate-limited — second concurrent gen fails with a generic "try again later". Serialize generation jobs.
  • gcloud auth vs notebooklm-account differ — a user logged into gcloud may not have notebooklm access; pass --account explicitly when they diverge.
  • Source ordering at upload affects citation precedence in generated content — re-uploading to fix order changes the output style.
  • Studio types have different timeout windows — audio ~5min, video ~15min, slides ~3min. CLI default of 60s drops mid-generation for the longer types.

Keep looking

Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.