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.
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Use this skill for hands-on DOCA Arg Parser CLI work on a shipped sample or new DOCA-using app — adding / removing / renaming flags; wiring `doca_argp_init` → register params → `doca_argp_start` → `doca_argp_destroy` in order; picking a parameter type from the full public enum (`DOCA_ARGP_TYPE_STRING`, `_INT`, `_BOOLEAN`, `_DEVICE`, `_DEVICE_REP`, `_DOUBLE` — six values, not three); preserving the standard `--device` / `--representor` / `--json` (`-j`; real flag is `--json`, NOT `--json-config`) / `--sdk-log-level` surface; or debugging `DOCA_ERROR_BAD_STATE` / `INVALID_VALUE` / `NOT_SUPPORTED` / `IO_FAILED` from `doca_argp_*`. Trigger on implicit phrasings: "add a custom flag to a DOCA sample", "should I use getopt here", "BAD_STATE registering a new param", "my JSON config key is rejected", or "my sample's --json is ignored". Refuse and route elsewhere for variadic-flag / subcommand / shell-completion features, DOCA Core context, or DOCA Log internals.
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查看安装方法安装前可以查看交给 AI 代理的指令内容。
doca_argp param; do not drop to
getopt.Follow Loading order below. Open the tasks companion for configure / register / debug. Open the capabilities companion for the public param types. Do not open every companion file.
Where to start: This skill assumes DOCA is already installed
and the user is doing hands-on CLI work on a DOCA sample or
new DOCA-using app. Open the tasks companion if the user wants
to do something (configure / build / modify / run / test /
debug); open the capabilities companion when the
question is what can the Arg Parser express on this version. If
the user has not installed DOCA yet, route to
doca-setup/SKILL.md first. If the user is
about to rewrite a sample's CLI with getopt / argparse /
custom parsing instead of reusing the Arg Parser, read the
load-bearing rule in
the capabilities companion
before any code change.
The CLASSES of Arg Parser questions this skill is built to answer, each with one worked example. The agent should treat the class as the load-bearing piece — the worked example is a single instance.
--my-flag to
/opt/mellanox/doca/samples/doca_dma/dma_local_copy/ so the
sample still accepts --device <PCI> and --sdk-log-level <level> the same way it did before". Answered by the
reuse-the-Arg-Parser rule in
the capabilities companion
doca_argp_param_set_* return BAD_STATE on my
second call?" — worked example: "registering a new param
after doca_argp_start has already parsed argv". Answered by
the lifecycle order in
the capabilities companion
DOCA_ERROR_BAD_STATE../my-config.json so the operator does not have to type out
ten flags every time". Answered by the --json <path>
integration in
the capabilities companion
--my-flag X value is rejected as INVALID_VALUE — why?" —
worked example: "declared the param as int but passed
--my-flag 0x40". Answered by the parameter-type table in
the capabilities companion
doca-argp even on my installed DOCA?" — worked
example: "a colleague's sample mentions doca-argp but I want
to confirm before I depend on it". Answered by the presence
doca-version/SKILL.md.doca_* symbol". Answered by the
path-selection rule in
the capabilities companion
Use doca-argp when … / Do not use doca-argp when … bullets.This skill serves external developers building or modifying
DOCA-using applications — i.e., users whose code already calls
doca_* (directly in C/C++, or through FFI/bindings from
another language) and who need the standard DOCA CLI surface so
operators of the resulting binary do not have to relearn how to
invoke each sample. It is not for NVIDIA developers
contributing to the Arg Parser library itself.
Language scope. DOCA Arg Parser ships as a C library with
pkg-config module name doca-argp. The shipped samples are
written in C. C and C++ consumers are the canonical case; the
worked examples in the tasks companion assume that path. Other-language
consumers (Rust, Go, Python, …) consume the same *.so through
FFI or language-specific bindings; the skill's contribution in
that case is to keep the lifecycle, parameter-type, JSON-config,
standard-flag-surface, and error-taxonomy guidance
language-neutral, and to route the agent to the public C ABI as
the authoritative surface that any wrapper will eventually call.
Load this skill when the user is doing hands-on DOCA Arg Parser work, in any language. Concretely:
--device <PCI>, --representor <name>,
--rep-list, --json <path>, --sdk-log-level <level>).doca_argp_init / doca_argp_start /
doca_argp_destroy into a main(), including the
register-before-start lifecycle and the cleanup-on-exit
contract.doca_argp_param (short name, long name, value
callback, description for --help) with a parameter type
drawn from the six-value public enum: string, int, boolean,
device, device representor, or double. A JSON config file is an
input surface for those parameters, not a parameter type.--json <path> flag instead of expanding the command
line.pkg-config --exists doca-argp,
pkg-config --modversion doca-argp) before depending on it.DOCA_ERROR_* returned from a doca_argp_* call
(lifecycle vs. type-mismatch vs. unknown JSON key vs.
unreadable file).Do not load this skill for general DOCA orientation, install
of DOCA itself, or non-Arg-Parser library questions. For those,
use
doca-public-knowledge-map/SKILL.md.
This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive Arg-Parser-specific material lives in two companion files:
--json <path> file integration,
the register-before-start lifecycle, the Arg Parser error
taxonomy (mapped onto the cross-library DOCA_ERROR_* set),
the observability surface (the --help output and the
DOCA Log channel), and the safety / path-selection policy
(when reusing doca-argp is mandatory; when a language-native
parser is the right answer).configure, build, modify, run, test,
debug. Plus a Deferred task verbs block that points
out-of-scope questions at the right next skill.The skill assumes a host or BlueField where DOCA is already
installed at the standard location. It does not cover installing
DOCA — that path goes through
doca-setup/SKILL.md.
This skill is agent guidance, not a samples or templates bundle. To keep the boundary clean, it deliberately does not contain — and pull requests should not add:
*_main.c file in every
shipped DOCA sample at
/opt/mellanox/doca/samples/<library>/<sample>/. The agent's
job is to route the user to that file and prescribe a
minimum-diff modification on it via the universal
modify-a-sample workflow in
doca-programming-guide/SKILL.md,
layered with the Arg-Parser-specific overrides in
the tasks companion.meson.build,
CMakeLists.txt, Cargo.toml, …) parked inside the skill.
The agent constructs the build manifest in the user's
project directory against the user's installed DOCA, where
pkg-config --modversion doca-argp is the source of truth.samples/, bindings/, or reference/ subtree of any
kind. A mock or incomplete artifact in this skill's tree,
even one labeled "reference", is misleading: users will read
it as buildable.--json <path> rule,
the register-before-start lifecycle, error taxonomy,
observability, and the path-selection / safety policy, see
the capabilities companion.Both companion files cross-link to each other,
doca-version/SKILL.md for the canonical
version-handling rules, and
doca-public-knowledge-map/SKILL.md
whenever the right answer is "look it up in the public docs or
the installed package layout" rather than "Arg-Parser-specific
guidance".
doca-public-knowledge-map/SKILL.md —
the routing table for every public DOCA documentation source
and the on-disk layout of an installed DOCA package. The Arg
Parser URL is
https://docs.nvidia.com/doca/sdk/DOCA-Arg-Parser/index.html;
the canonical on-disk usage example is any sample's
*_main.c under /opt/mellanox/doca/samples/.doca-setup/SKILL.md — env preparation,
install verification, and the I have no install yet path
with the public NGC DOCA container. This skill assumes its
preconditions are satisfied.doca-version/SKILL.md — canonical
DOCA version-handling rules. This skill's ## Version compatibility cross-links the four-way match rule and adds
the Arg-Parser-specific presence-check overlay.doca-structured-tools-contract/SKILL.md —
the bundle's structured-tools precedence rule (detect / prefer
/ fall back / report). The Command appendix in
the tasks companion honors this contract.doca-programming-guide/SKILL.md —
general DOCA programming patterns shared by every library:
the canonical pkg-config + meson build pattern, the
universal modify-a-shipped-sample first-app workflow, the
universal lifecycle, the cross-library DOCA_ERROR_*
taxonomy, and the program-side debug order. This skill layers
Arg-Parser specifics on top.doca-debug/SKILL.md — the cross-cutting
debug ladder (install / version / build / link / runtime /
program / driver). Arg-Parser-specific debug (lifecycle
violations, type-mismatch on a registered param, unknown JSON
key) overlays on top of that ladder.还没有评价。欢迎分享你的使用感受。
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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.
中文简介正在准备中。当前显示原文说明。
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.
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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.
中文简介正在准备中。当前显示原文说明。
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'.
中文简介正在准备中。当前显示原文说明。
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`.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。