Convert YouTube videos into structured transcripts and audio summaries.
npx skills add https://github.com/Glour/ai-office-v2 --skill tubescribe-glour
Please help me install this Agent Skill. Skill: TubeScribe Source: https://github.com/Glour/ai-office-v2/tree/main/skills/tubescribe Command: npx skills add https://github.com/Glour/ai-office-v2 --skill tubescribe-glour
TubeScribe reduces the manual effort of turning YouTube videos into structured transcripts and audio summaries, enabling easy review and documentation of video content.
Drop a YouTube URL to start processing; TubeScribe will process in the background and notify you when the results are ready.
High-intent search queries and answers about installing and using this skill.
You can convert YouTube videos to transcripts with speaker detection by providing a URL to automatically extract dialogue, label speakers, and output a formatted DOCX, HTML, or Markdown document with clickable timestamps. It processes multi-speaker interviews and lectures in the background.
You can generate audio summaries from YouTube videos by processing the URL to extract key points and convert them into MP3 or WAV files using on-device text-to-speech via mlx-audio or Kokoro. This creates concise audio files for quick on-the-go consumption.
yt-dlp works for extracting YouTube transcripts and video metadata by downloading the necessary audio and subtitle streams, which are then processed with speaker labeling and timestamp generation to produce structured DOCX or HTML documents.
The best way to analyze YouTube comments for viewer sentiment is to process the video URL, which automatically extracts and evaluates comments to surface viewer sentiment and highlight the most relevant discussions alongside the transcript and summary.
You can batch process multiple YouTube videos into transcripts and summaries by adding URLs to the processing queue. The system handles batched videos with background processing and notifies you when the transcripts and audio summaries are ready.
You need ffmpeg and torch installed to generate YouTube audio summaries because they handle audio processing and machine learning tasks required for on-device text-to-speech generation via mlx-audio or Kokoro to produce MP3 and WAV files.
marchattonDownload video, audio, subtitles, and transcripts from YouTube and yt-dlp supported sites.
balic-AI-ML-R-D-ResourcesTranscribe audio files locally using the Whisper CLI.
AlekseiULConvert YouTube videos into structured transcripts, documents, and audio summaries.
TikTzukiConvert text to speech and transcribe audio via cloud APIs.
