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    Notebooklm Research Automation

    2

    Automate Google NotebookLM research workflows, source ingestion, and study material generation via CLI and Python.

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    See it in action

    You say

    I have 8 academic papers as PDFs I want to ingest into a new NotebookLM notebook called "AI Safety Research Q2". Generate a workflow plan, produce an audio overview brief, and create a study guide covering key themes and open questions across all sources.

    Your agent does

    The skill produces a structured workflow plan for the notebook creation and source ingestion, followed by an audio overview brief formatted for NotebookLM's generation interface. A study guide is produced covering key themes, cross-source connections, and open research questions identified across the 8 papers. An artifact validation register records each generated output with status and quality check notes. Runtime setup verification steps are included to confirm the Python environment is ready before execution.

    What you get

    Automate the creation of audio overview scripts from multiple source URLs.Build repeatable research pipelines for complex PDF and YouTube datasets.Generate structured study materials like quizzes and briefings programmatically.Troubleshoot and manage NotebookLM authentication and source logs via CLI.

    About this skill

    Automate Research with NotebookLM

    Transform how you interact with Google NotebookLM by automating the tedious parts of the research process. This skill provides a structured framework for managing notebooks, ingesting diverse source material, and generating high-quality research artifacts without the manual overhead of the web interface.

    What it does

    Designed for developers and researchers, this skill acts as a bridge between your CLI/Python environment and NotebookLM. It helps you:

    • Plan and execute complex research pipelines using URLs, PDFs, and YouTube transcripts.
    • Generate study materials, audio overview plans, quiz questions, and flashcards programmatically.
    • Manage notebook lifecycles, from creation and source ingestion to artifact export.
    • Automate authentication workflows using secure browser cookie extraction methods.

    Why use this skill

    While prompting an AI can help you write a summary, this skill provides operational logic. It ensures runtime readiness, validates authentication boundaries, and follows a strict "plan-before-execute" pattern. It includes dedicated templates for run logs and artifact registers, making your research reproducible and auditable. It handles the underlying complexity of the notebooklm-py library, allowing you to focus on the research objective rather than the command-line syntax.

    Supported Tools

    The skill is optimized for environments running Python 3.9+, the notebooklm-py CLI, and supports cookie-based authentication via Firefox or Chrome.

    How to install

    Drop the file into your AI Agent. Works with Claude, Cursor, ChatGPT, and 20+ more.

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