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What is qiaomu-anything-to-notebooklm?

joeseesun/qiaomu-anything-to-notebooklm — explained in plain English

Analysis updated 2026-05-18

3,625PythonAudience · generalComplexity · 2/5LicenseSetup · moderate

In one sentence

A Claude Code skill that converts articles, videos, PDFs, and other content into podcasts, slides, or reports using Google NotebookLM.

Mindmap

mindmap
  root((qiaomu))
    What it does
      Fetches content
      Uploads to NotebookLM
      Generates new format
    Inputs
      Web pages and paywalled news
      YouTube and podcasts
      PDF EPUB Word Excel
    Outputs
      Podcasts and slides
      Mind maps and quizzes
      Reports and flashcards
    Audience
      Researchers
      Content creators

Code map

Detail Auto

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filefunction / class

What do people build with it?

USE CASE 1

Turn a paywalled news article into a podcast or report

USE CASE 2

Convert a YouTube video into a slide deck or mind map

USE CASE 3

Combine several sources like a PDF and a Twitter thread into one summary report

What is it built with?

PythonClaude CodeNotebookLM

How does it compare?

joeseesun/qiaomu-anything-to-notebooklmhkuds/paper2slidescity96/comfyui-gguf
Stars3,6253,6253,624
LanguagePythonPythonPython
Setup difficultymoderatemoderatemoderate
Complexity2/53/53/5
Audiencegeneralresearchervibe coder

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · moderate Time to first run · 30min

Requires a Google NotebookLM account and Claude Code installed.

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

So what is it?

This is a Claude Code skill, a plugin for Claude's AI coding assistant, that takes any piece of content and converts it into a new format using Google NotebookLM as the generation engine. You describe what you want in plain language, and the skill handles the pipeline automatically: fetching the content, uploading it to NotebookLM, triggering generation, and downloading the output file. The skill accepts over 15 types of input: WeChat articles (fetched via MCP browser simulation), web pages including 300+ paywalled news sites such as the New York Times, Wall Street Journal, Financial Times, and The Economist, YouTube videos (by auto-extracting subtitles), podcasts, Twitter/X threads, search queries (which aggregate results automatically), PDF files with OCR for scanned documents, EPUB ebooks, Markdown, plain text, Word (.docx), PowerPoint (.pptx), Excel (.xlsx), images with OCR, and audio files (WAV/MP3). For paywalled sites, the skill applies a six-level bypass strategy, trying proxy services, search engine bot user agents, archive sites like archive.today, and other techniques in sequence before giving up. Content can be converted into podcasts, slide decks, mind maps, quizzes, videos, reports, info charts, or flashcards. Multiple content sources can be combined into a single output, for example mixing a paywalled article, a YouTube video, and an EPUB into one report. The skill is written in Python and licensed under MIT. The full README is longer than what was provided.

Copy-paste prompts

Prompt 1
Convert this YouTube video into a podcast using the qiaomu skill
Prompt 2
Turn this paywalled New York Times article into a report
Prompt 3
Combine this PDF and this EPUB into a single mind map
Prompt 4
Generate flashcards from this podcast episode

Frequently asked questions

What is qiaomu-anything-to-notebooklm?

A Claude Code skill that converts articles, videos, PDFs, and other content into podcasts, slides, or reports using Google NotebookLM.

What language is qiaomu-anything-to-notebooklm written in?

Mainly Python. The stack also includes Python, Claude Code, NotebookLM.

What license does qiaomu-anything-to-notebooklm use?

Use freely for any purpose, including commercial use, as long as you keep the copyright notice.

How hard is qiaomu-anything-to-notebooklm to set up?

Setup difficulty is rated moderate, with roughly 30min to a first successful run.

Who is qiaomu-anything-to-notebooklm for?

Mainly general.

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