media-processing
FeaturedIngest and process media files (video, audio, image)
Install
Quality Score: 92/100
Skill Content
Details
- Author
- vellum-ai
- Repository
- vellum-ai/vellum-assistant
- Created
- 5 months ago
- Last Updated
- today
- Language
- TypeScript
- License
- MIT
Integrates with
Similar Skills
Semantically similar based on skill content — not just same category
ai-generated-media-pipeline
Turn AI-generated clips and stills into production web hero assets — generate via Higgsfield/Runway/Sora/Veo/Kling (video) and Nano Banana/Flux/Seedream (image), ideally through an MCP so the agent produces assets in-loop, then encode them web-ready (AV1/H.264, faststart, poster extraction, frame sequences) within a weight and licensing budget. Use when sourcing a hero video/background loop/scroll frame-sequence from AI tools, or preparing any generated media for the web. Feeds cinematic-hero-sections (which consumes the assets). Triggers on "Higgsfield", "Nano Banana", "AI hero video", "generate a background video", "Runway/Sora/Veo/Kling", "encode video for web", "ffmpeg hero", "loopable clip", "poster frame".
full-pipeline
Run the complete end-to-end production pipeline — parse, match, compose, copy, preview, review, finalize.
video-ingest
Ingests a video's content (YouTube and similar) for agent context, routing by capability, task need, and video length — a natively multimodal engine (Gemini via agy or the Gemini API) for direct-URL and long video, Claude vision over ffmpeg-extracted frames when no such engine is present, yt-dlp captions when the transcript alone suffices, and the logged-in claude-in-chrome session for auth-gated videos. The governor cross-checks any multimodal comprehensive-read. Triggered by "ingest this video", "what does this video show", "get the transcript from this YouTube video", "video-ingest".