Video & audio transcripts (YouTube and beyond)

Paste a link to a video, talk, stream or podcast episode in Chat and the model can read its captions and summarise, quote or fact-check it. It calls a media_transcript tool; Quartermaster fetches the captions server-side (yt-dlp) and hands them back as [m:ss] paragraphs, so the model can point at a moment ("at 14:32 they claim ...") and, on YouTube, link it back with &t=872s.

Not just YouTube. yt-dlp extracts from around 1800 sites, so Vimeo, TED, Dailymotion, Twitch VODs, Rumble, PeerTube, SoundCloud, conference players and most podcast episode pages work the same way - anywhere subtitles are published. Pages with no captions at all come back saying so, and the model should tell you that rather than guess.

Finding videos. The model can also search YouTube (youtube_search) and list a channel's or playlist's videos, so "find me a recent video about X and tell me what it says" works without you pasting a link first.

Comments. With youtube_comments the model can read a video's top comments - useful for "what do people say about this?", spotting corrections the creator never made, or gauging whether a tutorial actually worked for anyone. Comments are presented to the model as audience opinions, explicitly not as the video's own claims, so it shouldn't quote a comment as fact.

Requirements

• The model must support tool calling.
• yt-dlp must be present. Easiest: install it from Settings -> Backends (the Tools tab), which keeps it updatable. A copy on PATH, or the one the Windows installer drops in bin/yt-dlp when you tick the yt-dlp helper, also works. Without it the tools answer with an install hint instead of a transcript.

Limits

• Transcripts only exist for videos that actually have captions (manual or auto-generated). If captions are off, the tool says so rather than inventing content - there is no audio-transcription fallback.
• A long video is truncated to fit the context window; the result is marked INCOMPLETE with the timestamp it stopped at, and the model is told to say so.
• Comment fetching returns the top comments, not the whole thread.
• Per-turn call counts and result caching are capped server-side so a looping model can't grind through videos; repeated fetches of the same video are served from cache.
• Non-English captions: ask for them by language (e.g. "get the German transcript").

This page is generated from the help wiki that ships inside the app: the same text you get from the Help button, and the same text the playground assistant searches. Corrections go to wiki_articles.json.