Agent skill · nvidia
jetson-video-benchmark
Use when measuring Jetson Video Codec SDK or PyNvVideoCodec encode/decode throughput, comparing presets or surfaces, testing codec-worker capacity with authenticated samples and user media, or producing a documented clock-scaled or clock-and-resolution-scaled planning estimate when representative content is unavailable. Also use for Jetson video requests asking only for PSNR or SSIM results, to apply this performance skill's scope-only response.
What it needs
About 8k tokens when loaded.
What this skill does
Jetson Video Benchmark Purpose Measure codec-stage FPS and megapixels/second on the current Jetson. Use this skill for encode or decode throughput, P4/P5 comparisons, native-versus-Python comparisons, and increasing-worker capacity tests. When content is unavailable, it can instead produce a clearly labeled SDK-documentation estimate for an exact supported 1080p table row and target maximum video clock. For another requested resolution, it may additionally apply the bounded pixel-area heuristic defined in the estimate reference. Never present either estimate as a target measurement. Prerequisites For a live measurement: Run on the target Jetson with direct GPU access. A fresh validated nvcodec-environment identity from jetson-video-setup is optional; when supplied, it is authoritative and any invalid or stale identity fails without local fallback. The agent may obtain that identity from setup's public read-only probe; it need not be present in the customer's prompt. Without that identity, native routes inspect only the installed nvidia-video-codec-sdk APT package and its package-owned official sample sources. PyNvVideoCodec routes require an authenticated setup environment or the caller's exact absolute pynvcinterpreter; never scan for a venv. Before asking the customer for that path, invoke setup's public probe when that skill is installed and inspect its typed result. These read-only checks install, repair, register, and smoke-test nothing. Only when neither authority is usable does an explicit pynvc or both request return inputrequired; local auto records PyNvVideoCodec as notevaluated and may continue an eligible native branch. A PyNvVideoCodec decode-only performance route can use a validated default pynvc-smoke environment. A Python encode or compare route uses official samples that import Torch and therefore requires a separately provisioned full-samples venv; never upgrade the smoke venv in place. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/jetson-video-benchmark