warp-eval
warp-eval is an agent skill published by nvidia, listed under deploy & operate. It lives in the NVIDIA/skills repository, which has 3,735 GitHub stars and is licensed under Apache-2.0; we last read it on 2026-09-16.
Evaluates if an existing hot path is suitable for NVIDIA Warp, applicable to irregular or spatial queries, particle or geometry simulation, branch-heavy loops, many small launches, host fallbacks, or large intermediates. Requires NVIDIA GPU support unless prohibited.
Install
skills is a generic installer for any repository of Claude agent skills -- it reads NVIDIA/skills’s own structure rather than assuming one, the same way this page reads the skill’s own SKILL.md rather than assuming a format.
npx skills add NVIDIA/skills
What it connects to
Unverified means a mention in the skill’s own description, not a citation. A wrong claim here costs nothing to correct and nothing to trust yet.
Maintenance
Evaluate whether an existing hot path is a credible NVIDIA Warp candidate. Use for irregular or spatial queries, particle or geometry simulation, branch-heavy loops, many small launches, host fallbacks, or large intermediates. CPU-only code and absent GPU dependencies are normal unless NVIDIA is prohibited. Exclude required cross-vendor or CPU-only deployment, vendor-lowered dense or NN layers, general Warp API questions, and already-selected Warp kernels. Contribution policy alone is not exclusion.
warp-eval compared with similar skills
| Skill | Publisher | What it does | Repo stars | Last update |
|---|---|---|---|---|
| warp-eval (this page) | nvidia | Evaluate whether an existing hot path is a credible NVIDIA Warp candidate. Use for irregular or spatial queri… | 3,735 | 2026-10-26 |
| amc-setup-calibration-stack(same repository) | nvidia | Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says… | 3,735 | 2026-10-26 |
| cuopt-install(same repository) | nvidia | Install cuOpt for Python, C, or server via pip, conda, or Docker; verify the install. For building cuOpt from… | 3,735 | 2026-10-26 |
| cupynumeric-hdf5(same repository) | nvidia | Read and write large cuPyNumeric arrays to HDF5 with Legate's parallel, distributed HDF5 I/O (legate.io.hdf5:… | 3,735 | 2026-10-26 |
| data-designer(same repository) | nvidia | Use when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline. | 3,735 | 2026-10-26 |
| deepstream-generate-pipeline(same repository) | nvidia | Build DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image in… | 3,735 | 2026-10-26 |
| deepstream-import-vision-model(same repository) | nvidia | Use this skill to bring a supported object-detection vision model from HuggingFace or NVIDIA NGC into an NVID… | 3,735 | 2026-10-26 |
Skills from the same repository first, then others for this job by repository stars. Figures are from each repository when we last read it.
Common questions about warp-eval
- What does warp-eval do?
- Evaluates if an existing hot path is suitable for NVIDIA Warp, applicable to irregular or spatial queries, particle or geometry simulation, branch-heavy loops, many small launches, host fallbacks, or large intermediates. Requires NVIDIA GPU support unless prohibited.
- How do I install warp-eval?
- Run npx skills add NVIDIA/skills. The skills installer reads the repository’s own structure, so it works for any repository of agent skills.
- Who publishes warp-eval?
- nvidia.
- Is warp-eval maintained, and what licence does it use?
- Its repository has 3,735 GitHub stars and its state in our directory is listed. Its last commit we recorded was on 2026-10-26. The repository declares the Apache-2.0 licence.
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