Agent skill · NVIDIA
vss-deploy-detection-tracking-2d
Use this skill when the user wants to deploy, run, debug, tear down, or call the REST API of the RTVI-CV 2D detection / tracking microservice. Trigger when the user says things like 'deploy rtvi-cv', 'start warehouse 2d', 'add a stream', 'check rtvi-cv health', or 'stop the perception container'. Not for VLM, embedding, or analytics — use the matching vss-* skill.
What it needs
About 10k tokens when loaded.
What this skill does
Purpose Deploy, debug, and operate the RTVI-CV detection / tracking 2D microservice and drive its REST API. Prerequisites Active VSS deployment reachable on $HOSTIP (see vss-deploy-profile and references/). NGC credentials in $NGCCLIAPIKEY and $NVIDIAAPIKEY for any image pulls. curl, jq, and Docker available on the caller. Instructions Follow the routing tables and step-by-step workflows below. Each section that ends in workflow, quick start, or flow is intended to be executed top-to-bottom. Detailed reference material lives in references/ and helper scripts live in scripts/ — call them via runscript when the skill points to a script by name. Examples Worked end-to-end examples are kept under evals/ (each .json manifest contains a runnable scenario) and inline in the per-workflow curl blocks below. Run a Tier-3 evaluation with nv-base validate <this-skill-dir> --agent-eval to replay them. Limitations Requires the matching VSS profile / microservice to be deployed and reachable from the caller. NGC-hosted models and NIMs may be subject to rate-limits, GPU memory requirements, and license restrictions. Concurrency, GPU memory, and storage limits depend on the host hardware and the profile's compose file. Troubleshooting Error: REST call returns connection refused. Cause: target microservice not running. Solution: probe /docs or /health; redeploy via vss-deploy-profile or the matching vss-deploy- skill. Error: HTTP 401/403 from NGC pulls. Cause: missing/expired NGCCLIAPIKEY. Solution: docker login nvcr.io and re-export the key before retrying. Error: container OOM or model fails to load. Cause: insufficient GPU memory for the selected profile. Solution: switch to a smaller variant or free GPUs via docker compose down. RTVI-CV — Detection & Tracking (Unified Skill) Unified skill for the Real Time Video Intelligence CV (RTVI-CV) microservice. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/vss-deploy-detection-tracking-2d