rag-perf
Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).
npx skills add NVIDIA/skills --skill rag-perf --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.
# RAG-Perf — config-driven perf benchmark CLI ## Purpose Drive a deployed NVIDIA RAG Blueprint server with a YAML config, run a server-side **profiling pass** (per-stage timing, citation quality, bottleneck inference) and an optional **aiperf load test** (TTFT / E2E / token & request throughput / error rate), and write a unified report. The CLI is intentionally minimal: `rag-perf -c <config>` plus
What does the rag-perf skill do?
Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. Not for accuracy / RAGAS scoring (use rag-eval) or for deploying / repairing services (use rag-blueprint).
How do I install it?
Run `npx skills add NVIDIA/skills --skill rag-perf --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/skills, a repository with 2,789 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.