What problem does it solve? Getting full text from YouTube videos for research is tedious and fragile — captions APIs get IP-blocked, URLs come in many formats, and duplicate fetches waste effort. This Skill automates transcript retrieval with a multi-backend fallback chain so videos reliably end up as clean markdown files. ## Core Features & Use Cases - Multi-backend fallback chain: Tries youtube-transcript-api, Playwright automation, yt-dlp subtitle download, and a headed Chrome browser pull in sequence, with manual HTML paste parsing as a last resort. - Automatic deduplication: Normalizes YouTube URL formats (watch, youtu.be, shorts, raw IDs), skips already-fetched videos, and dedupes within a batch. - Batch probing: Estimates duration, upload date, and token cost per video before fetching so you can size research batches. - Use Case: During a research-loop Pass 2, you have five high-value YouTube sources. Run the fetcher with all five URLs; it probes the batch, fetches transcripts with metadata headers (title, channel, duration), and flags any blocked videos for later retry. ## Quick Start Fetch transcripts for these YouTube URLs and save them as markdown files: https://www.youtube.com/watch?v=VIDEO_ID