toolsai/notebooklm-studio-skill — explained in plain English
Analysis updated 2026-05-18
Ask an AI agent to build a NotebookLM notebook and generate summaries or study guides from a set of sources.
Turn research documents into a slide deck, report, or audio overview with one prompt.
Run pre-built workflows like an executive briefing package or a learning study pack.
Manage NotebookLM notebooks and track generated outputs through a local dashboard.
| toolsai/notebooklm-studio-skill | huta0kj/skill-scanner-agent | kkdai/linebot-multimodal-rag | |
|---|---|---|---|
| Stars | 31 | 31 | 31 |
| Language | Python | Python | Python |
| Setup difficulty | easy | moderate | hard |
| Complexity | 2/5 | 3/5 | 4/5 |
| Audience | researcher | developer | developer |
Figures from each repo's GitHub metadata at analysis time.
Requires Google login to NotebookLM and an agent that supports Skills, such as Codex or Claude Code.
NotebookLM Studio Skill is a plugin for AI coding agents, particularly Codex and Claude Code, that connects them to NotebookLM, Google's research tool. On its own, NotebookLM lets you feed it documents, web pages, PDFs, audio, and video, and it generates useful outputs like summaries, study guides, mind maps, slide decks, quizzes, and audio overviews. The problem is that doing this manually is slow: you add sources one by one, click to generate each artifact, and then copy results somewhere useful. This Skill adds an automation layer. Instead of doing that manually, you describe what you want in plain language to your AI agent, and it handles creating or reusing notebooks, adding sources in bulk, triggering the generation of outputs, downloading them to a local folder, and creating handoff files so the agent can read and analyze the results directly. There are also pre-built one-click workflows for common research goals, like building an executive briefing package or a learning study pack, and a local web dashboard where you can manage notebooks and track what has been generated. You would use this if you regularly do research-heavy work and want an AI agent to run the full pipeline from raw sources to finished deliverable.
A Skill that lets AI coding agents like Codex or Claude Code automate NotebookLM research tasks.
Mainly Python. The stack also includes Python, NotebookLM.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.