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notebooklm

Automate Google NotebookLM notebook creation, source ingestion, chat, and artifact generation via CLI and Python API.

69|7|Updated Feb 8, 2026
Search Tags:#automation#workflow#research#api#python#cli#notebooklm
One-click install
npx skills add https://github.com/jmagar/claude-homelab --skill notebooklm-jmagar
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: notebooklm
Source: https://github.com/jmagar/claude-homelab/tree/main/skills/notebooklm
Command: npx skills add https://github.com/jmagar/claude-homelab --skill notebooklm-jmagar

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

High-friction manual workflows are common when using NotebookLM's UI; this skill provides programmatic control to automate notebook creation, source ingestion, chat, artifact generation, and downloads via CLI and Python API.

Core Features & Use Cases

  • Create and manage notebooks programmatically via Python API and CLI, including adding URLs, YouTube content, PDFs, audio, video, and image sources.
  • Chat with your notebook content to ask questions, retrieve references, and generate artifacts such as podcasts, videos, mind maps, infographics, reports, quizzes, flashcards, and data tables, with downloadable outputs.
  • Enable end-to-end automation workflows (e.g., research → podcast) and cross-notebook pipelines, including batch exports and agent integrations.

Quick Start

Install the notebooklm-py client, authenticate with notebooklm login, then create notebooks, add sources, chat, generate artifacts, and download results.

Frequently Asked Questions about notebooklm

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate Google NotebookLM workflows using Python?▼

Automate Google NotebookLM workflows using Python by installing the notebooklm-py client, authenticating via CLI, and programmatically creating notebooks, ingesting sources, and generating artifacts. This enables end-to-end automation with status monitoring and batch downloads.

Can I generate podcasts and videos from PDFs and YouTube links in NotebookLM?▼

Yes, you can generate podcasts and videos from PDFs and YouTube links in NotebookLM by programmatically adding these URLs as sources and triggering artifact generation via the Python API, which then downloads the resulting media files automatically.

How does programmatic NotebookLM source ingestion work for research automation?▼

Programmatic NotebookLM source ingestion works for research automation by using the Python API to add URLs, YouTube content, PDFs, and images to notebooks, enabling cross-notebook pipelines and chat queries without manual UI interaction.

What is the best way to batch download reports and quizzes from NotebookLM?▼

The best way to batch download reports and quizzes from NotebookLM is using the CLI and Python API, which automates artifact generation across multiple notebooks and handles batch exports with integrated status monitoring.

Does the NotebookLM Python API support cross-notebook pipelines and agent integrations?▼

Yes, the NotebookLM Python API supports cross-notebook pipelines and agent integrations, allowing you to automate end-to-end workflows from research to podcast generation and facilitate batch exports across multiple notebooks.

Why should I use a Python API for NotebookLM instead of the web UI?▼

Use a Python API for NotebookLM instead of the web UI to eliminate high-friction manual workflows, enabling automated notebook creation, source ingestion, chat, artifact generation, and batch downloads with programmatic status monitoring.

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