Run srt-slurm (srtctl) inference benchmarks on a Slurm cluster. Use when setting up a checkout, writing or migrating a recipe, submitting a job, or reading its results.
NVIDIA/srt-slurm
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Install with an AI assistant
Copy this prompt into the AI assistant you're using.
Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/NVIDIA/srt-slurm.Loading the repository README…
Skills in this repository
Showing 7 of 7 collected skills.
Write or refine a ready-to-use /goal prompt for a performance benchmark, regression investigation or optimization campaign. Define measurable targets, a matched baseline, change boundaries, diagnostic evidence and completion criteria. Use for drafting the…
Add, rename, or re-type a recipe or srtslurm.yaml field in srt-slurm so that it ships complete (schema, resolver, dry-run, docs, example, tests).
Analyze existing DSight reports through the read-only SQLite-backed CLI, Python or MCP query interface. Use when inspecting request latency, lifecycle, metrics, Nsight ranges or CPU samples, comparing runs, or gathering evidence for a dashboard view.
Size Slurm allocations, warmup and traffic for short debugging jobs or full srt-slurm benchmarks.
Periodic cleanup of srt-slurm drift - shrink the Design Rule baselines, fix stale agent docs, and open small focused PRs.
Verify an srt-slurm change end to end without SLURM or GPUs, using dry-run, the mock orchestrator, and the launch snapshots.