Everything in the free claude-real-video, plus a --motion pass that turns cinematography into data any LLM can reason about.
The free tool already gives a model scene-aware frames and a transcript — enough to know what a video is about. But a stack of stills drops the two things that make video video: motion and pacing. A model can't tell a slow push-in from a frantic handheld chase, or a snappy edit from a lingering one, when all it sees is disconnected images.
crv Pro closes that gap by measuring it directly.
--motion addsEvery shot labelled — static, pan left/right, tilt up/down, zoom in/out, or handheld — classified automatically and verified against ground-truth footage.
Full shot list with durations, cuts per minute, and how the pacing shifts across the open, middle and close. Ask your AI why an edit feels fast, and it answers with numbers.
High-motion shots automatically get 0.2s-apart frame sequences, so the model reads movement as a progression instead of guessing what happened between two keyframes.
It all lands in the same MANIFEST.txt your LLM already reads — as plain text:
--- motion analysis (crv Pro) --- editing rhythm: 14 shots | 21.0 cuts/min | avg 2.8s (median 2.1s, range 0.8-9.4s) cuts by thirds (open/middle/close): 7 / 4 / 3 shots: #01 0.00-2.10s (2.10s) camera: pan-right motion: high (12.3%W/s) burst: burst_shot01_1..4 #02 2.10-4.80s (2.70s) camera: zoom-in motion: medium (3.1%W/s) #03 4.80-9.20s (4.40s) camera: static motion: low (0.2%W/s) ...
Everything runs locally with ffmpeg + OpenCV. No ML models to download, no cloud uploads — your footage never leaves your machine. After purchase you get the install package and your license key; one license, use it on all your machines.