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Query incidents, alerts, sensor counts and metrics from a VA-MCP Elasticsearch backend (port 9901) to answer questions about violations, occupancy, speeds, and
Queries incidents, alerts, sensor IDs, places, and aggregated metrics stored in Elasticsearch via the VA-MCP JSON-RPC endpoint (default port 9901). It provides a two-step CLI pattern to initialize an MCP session and then call tools such as get_incidents, get_sensor_ids, get_places, fov_histogram, and analysis helpers to return recent incidents or aggregated statistics.
Use this skill when you need authoritative, recorded-event data from a video analytics stack: incident reports, alert history, object counts (people, vehicles), occupancy, average speeds, or sensor/place listings. It is intended for operational queries where the agent should run the provided curl commands against a reachable VA-MCP endpoint and relay actual results rather than guessing.
Likely compatible with agent tooling that can run shell commands and HTTP requests (CLI-enabled agents such as Copilot/Codex/Gemini CLI or Claude Code).
NVIDIA video-analytics skill for querying incidents/alerts/metrics from a VA-MCP Elasticsearch backend. The source_url is 404 (the path video-search-and-summarization/video-analytics does not exist in the NVIDIA/skills repo — the actual skills are under vss-setup-video-analytics-api, vss-ask-video, etc.). skill_md_body was null, so static analysis is limited to the DB metadata. Based on related NVIDIA VSS skills, this is a deployment/operational skill requiring Docker, Elasticsearch, NGC credentials, and GPU hardware. No scripts were bundled. The skill appears to be a stale/broken discovery entry with a dead source URL.
skill_md_body is null and the source_url (https://github.com/nvidia/skills/blob/main/skills/video-search-and-summarization/video-analytics/SKILL.md) returns 404. The NVIDIA/skills repo has similar skills under vss-setup-video-analytics-api, vss-ask-video, vss-summarize-video, etc. This appears to be a broken discovery entry. Security score: no scripts to audit, no curl|bash or hardcoded creds visible in metadata, but the short_description mentions connecting to Elasticsearch on port 9901 which implies network access to a potentially sensitive backend. Code quality: 42 — the SKILL.md content is missing (null body), making the skill essentially non-functional as authored. Architecture: 35 — frontmatter was partially captured by the discovery system but the core content is absent. Usefulness: 40 — querying video analytics from Elasticsearch is a real use case, but requires heavy NVIDIA/ES/Docker infrastructure and this specific skill entry is broken.
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