Add agent-ready vision capabilities — dense captioning, detection, search, alerting, summarization — to an agent or application through a customizable, self-contained vision stack built on the NVIDIA VSS Blueprint. Use this skill when a developer or agent…
Benchmark a deployed LVS instance — set up test media, run single-file latency and burst-throughput tests, analyze GPU and latency metrics, and get configuration recommendations to improve performance.
Benchmark video Q&A accuracy and latency of a deployed RT-VLM (Cosmos Reason 3) via vss vlm run, using questions and videos from the DSS vss-devx-base dataset. Replaces the deprecated nat eval / vss-agent QA path. Not for tool-calling or trajectory…
Measure whether an RT-VLM configuration change altered caption quality — capture paired baseline and candidate captions for a set of videos, score both against a ground truth with an LLM judge, and emit an accuracy and processing-time table. Use when changing…
Use this skill when deploying standalone RT-VLM dense captioning or calling its REST API (uploads, captions, streams, chat-completions, Kafka). Not for VSS profile deploy or video-search ingestion.
Use this skill when deploying, operating, integrating, or customizing the VSS RT-Embed Video Embedding microservice. Covers standalone Docker Compose deployment, the `/v1` REST API for text/video embeddings and live streams, Redis/Kafka/OTel integration,…
Use when the user asks to deploy, upgrade, or size the VSS warehouse blueprint (2D / 3D / MV3DT) on Kubernetes via Helm — as opposed to Docker Compose, which is covered by vss-build-vision-ai's warehouse reference. Handles GPU-aware NUM_STREAMS capping so the…
Use this skill to deploy the vss-behavior-analytics service standalone (entrypoint, config-source, optional calibration). Not for the full warehouse deploy.