louisedesadeleer

Find compelling moments in a video — funny dialogue OR repeated impact actions like axe chops, hits, throws, drumbeats — cut them as standalone clips, optionally reformat 16:9 ↔ 9:16, time-warp pans for tighter reveals, and burn opus-style word-by-word…

Source b-roll for a video edit — classify each moment, scope the search, return vetted candidates, place on the word. Use when the user says "find b-roll", "/find-broll", "source clips for this edit", or wants footage/memes/screenshots to lay over a…

Tighten a long recording aggressively — remove silences, fillers, hedges, false starts, and repetitions while preserving laughs and comedic pauses. Cuts are driven by Montreal Forced Aligner (MFA) word boundaries (auto-installs on first run), not raw Whisper…

Grade a video file with your AI agent as the colorist — it looks at frames, diagnoses casts/exposure/saturation, authors a readable ffmpeg grade, previews side-by-side, iterates, renders. Non-destructive. Nine named looks (Golden Hour, Honey, Linen, Super 8,…

File any asset the user drops in chat (image, video, audio, YouTube link, image URL) into their organized local asset library (~/assets by default) — classified by type, auto-named by content, optionally tagged to a project. Use when the user sends a file or…

Add emphasis motion to a flat talking-head video file — dramatic hard-cut punch-zooms on emphasised words + listicles, and subtle Ken Burns slow-pushes on insightful lines. Transcript-driven, ffmpeg-based (zoompan), non-destructive. Use when the user says…