vss-deploy-profile
Use to select, configure, deploy, verify, debug, or tear down a VSS profile (base, search, lvs, warehouse, edge). Not for standalone microservices — use the vss-deploy-* skill.
npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-profile --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# VSS Deploy ## Available Scripts | Script | Purpose | Arguments | |---|---|---| | `scripts/normalize_resolved_yml.py` | Strip optional `depends_on` entries for services filtered out of `resolved.yml` before deploy. | Path to `resolved.yml` | | `scripts/probe_remote_models.sh` | Probe an OpenAI-compatible remote LLM/VLM endpoint and verify the selected model id. | Base URL, optional expected model
What does the vss-deploy-profile skill do?
Use to select, configure, deploy, verify, debug, or tear down a VSS profile (base, search, lvs, warehouse, edge). Not for standalone microservices — use the vss-deploy-* skill.
How do I install it?
Run `npx skills add NVIDIA-AI-Blueprints/video-search-and-summarization --skill vss-deploy-profile --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From NVIDIA-AI-Blueprints/video-search-and-summarization, a repository with 1,773 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.