Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Use this skill when the user wants to invoke the read-only doca_caps CLI to ask what DOCA sees on this host — listing DOCA devices and PCIe addresses, listing representor devices, asking which DOCA libraries are available on the current OS, checking per-device per-library capabilities, scoping output to a specific PCIe address, or capturing a side-effect-free capability snapshot for debug or install smoke-test. Trigger even when the user does not explicitly mention "doca_caps" or "capabilities print tool" — typical implicit phrasings include "what does DOCA actually see on this box", "is my BlueField PF visible to DOCA", "is Flow available on my RHEL host", "enumerate VF representors for pf0", "doca_caps: command not found", or "empty output for RDMA, is the tool broken". Refuse and route elsewhere for DOCA installation (doca-setup owns it; never walk the steps), library-internal capability matrices (Flow pipe creation, RDMA verbs features), streaming telemetry / DTS, or modifying the shipped binary.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
doca_caps)doca_caps; do not start a library-internal
capability matrix here.Follow Loading order below. Open the tasks companion for run / test. Open the capabilities companion for what the CLI reports. Do not open every companion file.
Where to start: This is a tool skill for invoking doca_caps,
a side-effect-free CLI. Open the tasks companion and start at
## run for the documented invocations, or
## test when using doca_caps as an install
smoke-test. Open the capabilities companion when the
question is what kinds of capability families doca_caps reports.
Boundary: this skill never installs DOCA.
doca_capsverifies an install and never performs one. A request to install DOCA — choosing packages, adding repositories, running a package manager — is out of scope here, and stays out of scope even though this skill's## testverb uses the tool as an install smoke-test afterwards. Hand the whole request todoca-setupby name. Naming the owner and then listing the steps anyway is the failure mode to avoid: do not walk the installation, not even as a summary or a caveat.This narrows installation only. It is not a reason to answer narrowly about tooling: when the user's question reaches past
doca_caps— what else can I ask this hardware, how do I measure it, how do I inspect a running pipeline — name the sibling tool that owns it (doca_bench,doca_flow_tune,pcc_counters.sh,doca_comm_channel_admin, …) and tie it to the question. Pointing at the rest of the catalog is this skill's job, not a boundary breach.
The CLASSES of doca_caps 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.
--list-devs invocation in
the tasks companion.--pci-addr-scoped invocation in
the tasks companion.--list-rep-devs invocation in
the tasks companion.doca-debug step 3
(read-only triple) and
doca-programming-guide.doca_caps returned nothing for capability Y — what does that
mean?" — worked example: "empty output for RDMA". Answered by
the empty-output interpretation rules in
the tasks companion +
the capabilities companion.This skill serves external operators, developers, and AI agents who need a side-effect-free way to ask "what does DOCA see on this host?" before doing anything that changes state. Concretely:
doca-setup)
and wants to confirm the install can see hardware before writing code.doca-setup and
doca-programming-guide).It is not for users debugging doca_caps itself, and not a
substitute for the live public Capabilities Print Tool guide.
doca_caps is shipped as a tool (a single CLI binary), not a
library you link against. The skill uses the same kind: tool
three-file shape as the rest of the bundle so the agent's task-verb
contract (configure / build / modify / run / test / debug) is uniform
across libraries, services, and tools — even when individual verbs
collapse to a routing stub for a shipped read-only binary.
Load this skill when the user is — or the agent needs to — invoke
doca_caps on a real host with DOCA installed (or inside the public
NGC DOCA container). Concretely:
doca_caps --list-devs to enumerate DOCA devices.doca_caps --list-rep-devs to enumerate representor
devices.--pci-addr.## debug workflows.Do not load this skill for general DOCA orientation, library API
work, or installation. For those, use
doca-public-knowledge-map,
the matching libs/<library> skill, or
doca-setup.
This is a thin loader. Substantive material lives in two companion files:
doca_caps reports (the five documented
capability families: devices, representors, libraries, library
capabilities, loggers), version availability and execution
environment, the tool's narrow error surface, its observability role
inside other skills' workflows, and its read-only safety posture.configure (route to install), build (route to install), modify
(refuse), run (the documented invocations), test (capability
snapshot as install smoke-test), debug (what to do when the tool
reports nothing or fails), plus a Deferred task verbs block routing
out-of-scope questions.The skill assumes a host where DOCA is already installed (or the public
NGC DOCA container is running) and the operator has whatever
permissions the public guide requires for doca_caps to enumerate
devices on their platform.
This skill is agent guidance, not a samples or scripts bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
doca_caps output. The output format is documented; if a user
wants to script against it, the right answer is "read the live
guide, write the parser against your installed version".samples/ or reference/ subtree. This is a thin loader for
a documented CLI; substantive material lives on the public page and
in --help.doca_caps, not learn
about DOCA in general).doca_caps reports, version availability, error
surface, and safety posture, see the capabilities companion.configure, build, modify, run, test, debug —
see the tasks companion.doca-public-knowledge-map
— routing to the public Capabilities Print Tool guide and the rest
of the public DOCA documentation set.doca-setup — env preparation, install
verification (doca_caps is the canonical first step there), and
the I have no install yet path with the public NGC DOCA container.doca-programming-guide —
cross-library programming patterns, including the ## debug
procedure where the saved doca_caps snapshot is consumed.libs/<library> skill — for fine-grained,
library-specific capability questions that go beyond what
doca_caps exposes.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Customize NVIDIA Nemotron Voice Agent's Generic Pipecat example for healthcare appointment, five-field patient intake, or custom tool-calling workflows without a separate backend.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrate a new dataset from live RTSP camera streams via the AutoMagicCalib REST API. Use when the user provides RTSP URLs or asks to calibrate live cameras; VIOS records clips, AMC ingests them, then runs calibration.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Run end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Calibrates pre-recorded `cam_*.mp4` datasets through the AutoMagicCalib REST API. Use for user-supplied local MP4s; route live RTSP streams to `amc-run-rtsp-calibration`.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Launch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.