NVIDIA/skills is a catalogue of portable instruction sets that teach coding agents how to use NVIDIA software for robotics, simulation, CUDA, retrieval-augmented generation, and related workflows. Developers install these skills in agents such as Claude Code or Codex, while the catalogue mirrors skills maintained in separate NVIDIA product repositories.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add NVIDIA/skills --skill doca-gpunetio-ib-write-bwgit clone --depth 1 https://github.com/NVIDIA/skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/nvidia/skills/doca-gpunetio-ib-write-bw)<a href="https://agentmods.dev/skills/nvidia/skills/doca-gpunetio-ib-write-bw"><img src="https://agentmods.dev/badge/skills/nvidia/skills/doca-gpunetio-ib-write-bw/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/nvidia/skills/doca-gpunetio-ib-write-bw"><img src="https://agentmods.dev/badge/skills/nvidia/skills/doca-gpunetio-ib-write-bw.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00249 | $0.04578 |
| Opus 5 | $0.00125 | $0.02289 |
| Sonnet 5 | $0.00050 | $0.00916 |
| Haiku 4.5 | $0.00025 | $0.00458 |
Grade A, and why
doca-gpunetio-ib-write-bw scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 6d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 354 lines — stays where its author put it; the contents beside it link to each section on GitHub.
DOCA GPUNetIO ib_write_bw
Where to start: This is a tool skill for the GPUNetIO-
flavored ib_write_bw benchmark shipped under
doca/tools/gpunetio_ib_write_bw/ (a client + server pair,
built from source against the installed DOCA via meson).
It measures sustained RDMA WRITE bandwidth when the WRs are
posted from a CUDA kernel through the doca-gpunetio
device-side surface, with the GPU on the data path. Open
TASKS.md and start at
## configure for the GPU-NIC
pairing precondition and the build pattern; jump to
## run for the smoke-before-bulk flow.
Open CAPABILITIES.md when the question
is what this tool actually measures, how the result
decomposes (GPU occupancy vs NIC issue rate vs link
saturation), or how the result reads against the GPI
sister tool and the upstream CPU-initiated perftest
ib_write_bw. If DOCA is not installed yet, route to
doca-setup first; if the
user is still deciding between the GPI and GPUNetIO
programming surfaces, the picture in
../../libs/doca-gpunetio/CAPABILITIES.md#capabilities-and-modes
and
../../libs/doca-gpi/CAPABILITIES.md#capabilities-and-modes
is the first stop.
Example questions this skill answers well
The CLASSES of doca-gpunetio-ib-write-bw questions this
skill is built to answer, each with one worked example. The
class is the load-bearing piece; the worked example is one
instance.
- "What sustained RDMA-WRITE bandwidth can the GPUNetIO
path deliver on this GPU-NIC pair?" — worked example:
"measure sustained WRITE BW between two hosts with an
H100 + ConnectX-7 on each side". Answered by the
GPU-NIC pairing precondition in
CAPABILITIES.md ## Capabilities and modes- the bring-up flow in
TASKS.md ## configure+TASKS.md ## run. The same shape answers "measure GPUNetIO-driven WRITE BW between a host GPU and a BlueField DPU".
- the bring-up flow in
- "Where is the bottleneck — GPU compute occupancy, NIC
issue rate, or link saturation?" — worked example:
"I see 120 Gbit/s on a 200 Gbit/s link; is the NIC
saturated, am I CPU-bound on the client, or is the CUDA
kernel not driving enough WRs in flight?". Answered by
the throughput-decomposition rules in
CAPABILITIES.md ## Observability- the eval-loop overlay in
TASKS.md ## test.
- the eval-loop overlay in
- "How does the result differ from the classic CPU-
initiated
perftestib_write_bw?" — worked example: "my team has a CPU-initiated WRITE BW number on this same NIC; should I expect the GPUNetIO number to match or be different?". Answered by the "GPU-initiated path adds (or removes) overhead vs the CPU-initiated path" rule inCAPABILITIES.md ## Capabilities and modes. - "Is the doca-gpunetio path the right surface for my
sustained-throughput workload class?" — worked example:
"my application streams sensor data from GPU memory at
line rate to a remote consumer". Answered by the
"when GPUNetIO is the right surface vs GPI vs CPU-
initiated" rule in
CAPABILITIES.md ## Capabilities and modes- the use-side decision in
TASKS.md ## use.
- the use-side decision in
- "My BW number swings between runs. What do I check
before quoting it?" — worked example: "three runs at
the same flags gave 145, 187, and 160 Gbit/s; is the
benchmark noisy or is my platform inconsistent?".
Answered by the measurement-soundness rules in
CAPABILITIES.md ## Error taxonomylayer 5 + the steady-state guidance inTASKS.md ## test. - "What version of DOCA + CUDA Toolkit do I need for this
binary to build and run?" — worked example: "my
install has DOCA at one semver and CUDA at another; will
the ToT-shipped
gpunetio_ib_write_bweven link?". Answered by the version overlay inCAPABILITIES.md ## Version compatibilitywhich cross-links the canonical detection chain indoca-version.
What ships with it
7 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 6d ago First seen · 354 lines · 249 tokens per session scan A d8c93fa1d19b
doca-gpunetio-ib-write-bw is a skill published in the GitHub repository NVIDIA/skills (3,244 stars, last pushed yesterday), licensed Apache-2.0. It adds 249 tokens to every session and 4,578 once invoked, about $0.0012 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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