Use this skill when the user is writing their first DOCA app or asking a library-agnostic programming question — picking a shipped sample to copy and modify, wiring the canonical pkg-config doca-{library} + meson build (or FFI from Rust / Go / Python against the public C ABI), walking the cfg-create…
npx -y skills add NVIDIA/skills --skill doca-programming-guide --agent claude-codeInstalls into .claude/skills of the current project.
Where to start: Read ## Audience to confirm the user
is consuming DOCA, not contributing to it. Then jump to the H2
that matches the verb (## modify for first-app derivation,
## build for the canonical build pattern, ## test for the test
loop, ## debug for the program-class debug ladder).
These are the CLASSES of program-class questions the skill is built to answer, each with one worked example. Library-specific overlays (Flow / DMS / Caps / …) live in the matching library skill; this skill answers the library-agnostic shape.
TASKS.md ## modify plus the canonical build
pattern in TASKS.md ## build.doca_rdma_*?"
Answered by the pkg-config doca-<library> pattern in
TASKS.md ## build (C/C++ Track 1) and the
FFI/bindings pattern in Track 2.doca_flow_pipe_* calls in my
program?" Answered by the cfg-create / init / start / use / stop /
destroy template in CAPABILITIES.md ## Capabilities and modes.DOCA_ERROR_* came back — what does it mean and what do I do?"
— worked example: "My code got DOCA_ERROR_BAD_STATE." Answered
by the cross-library doca_error_get_descr() rule in
CAPABILITIES.md ## Error taxonomy
TASKS.md ## debug.CAPABILITIES.md ## Safety policy
and the layered program-class debug ladder in
TASKS.md ## debug.TASKS.md ## build (FFI against the public C
ABI) and the language-neutral lifecycle in
CAPABILITIES.md ## Capabilities and modes.TASKS.md ## sample-and-app-categorization,
which separates "the SDK is broken" from "the optional GPU /
RMAX / MPI stack is not on this BlueField".If the question is env-class (install / build env / hugepages /
devices), route to doca-setup. If it is
library-specific (Flow pipe topology, RDMA QP setup, DMS service
deploy), layer the matching library skill on top.
This skill serves external developers building applications that
consume DOCA libraries — i.e., users whose code calls one or more
doca_<library>_* symbols (directly in C/C++, or through FFI /
bindings from another language). It is programming with DOCA,
not programming of DOCA: it is not for NVIDIA developers
contributing to DOCA itself, and it does not assume access to the
DOCA source tree, internal NVIDIA tooling, or any non-public
information. The only inputs it ever points the agent at are the
ones any external user has: the public docs at
docs.nvidia.com/doca/sdk/,
the public catalog at
catalog.ngc.nvidia.com, the
public GitHub repos under
github.com/NVIDIA /
github.com/NVIDIA-DOCA, the
public developer forum, and the on-disk /opt/mellanox/doca tree
that the public DOCA install (or the public NGC DOCA container,
nvcr.io/nvidia/doca/doca) puts on the user's host. Where to find
and how to install questions are routed elsewhere — see Related
skills below.
Language scope. DOCA itself is a C library family; every shipped
sample in /opt/mellanox/doca/samples/ and every shipped reference
application in /opt/mellanox/doca/applications/ is C. C and C++
consumers are the canonical case for every prescriptive workflow in
this skill. Other-language consumers (Rust, Go, Python, …) consume the
same *.so libraries through FFI or language-specific bindings against
the public C ABI; the skill keeps the lifecycle, capability, error,
observability, and safety guidance language-neutral, and routes the
language-specific build / FFI work back to the consumer's own toolchain
without authoring wrappers.
Load this skill when the user has DOCA installed and the env-class
preconditions are already satisfied (i.e.,
doca-setup has produced a clean install
where pkg-config doca-<library> resolves, hugepages are mounted, and
devices are visible), and is now asking a question about how to
actually program against DOCA in a library-agnostic way:
pkg-config + meson build pattern any DOCA application
follows, regardless of which library it consumes.doca-setup because it
is a programming verb, not an env verb.cfg-create → init → start → use → stop → destroy) and how it manifests across libraries.DOCA_ERROR_* pattern, doca_error_t, and
doca_error_get_descr() — the cross-library shape, not Flow- or
RDMA-specific overlays.Do not load this skill for:
pkg-config not find doca-flow?
How do I mount hugepages? I don't have DOCA installed yet — can I
use a container?" — env-class questions belong in
doca-setup, which owns install
verification, env preparation, env-class debugging, and the
no-install → NGC container fallback path for any user on macOS,
Windows, or Linux without DOCA.doca-public-knowledge-map.doca-flow).This is a thin loader. The body keeps only the orientation needed to pick the right next file. The substantive material lives in two companion files:
CAPABILITIES.md — what every DOCA program looks like in the
abstract: the shape of DOCA (host / DPU / switch, libraries / apps /
services / tools, build flavor selection rationale), the universal
program lifecycle, the unified version-compat rule that applies to
any program linking DOCA, the cross-library DOCA_ERROR_* taxonomy,
the program-side observability surface (DOCA logging, capability
snapshots), and the program-side safety policy that every library
skill inherits.TASKS.md — step-by-step workflows for the six in-scope programming
verbs: configure, build, modify, run, test, debug. The
## modify verb owns the universal derive a custom first app from
a sample pattern that every DOCA library skill extends with
library-specific overrides; the ## build verb owns the canonical
pkg-config doca-<library> build pattern in two language tracks
(C/C++ direct, non-C via FFI).This skill assumes doca-setup has already
produced a clean install. It does not cover env preparation; that
is doca-setup's job, including the no-install → NGC container
(nvcr.io/nvidia/doca/doca) fallback for users on macOS, Windows, or
Linux without DOCA.
This skill is agent guidance, not a samples or templates bundle. It deliberately does not contain — and pull requests should not add:
TASKS.md ## modify) — for C/C++ users — or to
route non-C users to the public C ABI surface that their bindings
will call (TASKS.md ## build Track 2), not to
author the wrapper.meson.build, CMakeLists.txt,
Cargo.toml, setup.py, go.mod, …) 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-<library> 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.SKILL.md first to confirm the user's question is a
programming-class question (not env, not routing, not library-API).configure, build,
modify, run, test, debug — see TASKS.md.If the user is asking for a first app in a specific library, walk
through TASKS.md ## modify for the universal
copy-and-edit pattern, then hand off to the library skill (e.g.
doca-flow) for the library-specific values
to swap.
doca-public-knowledge-map
— public DOCA documentation routing and the on-disk layout of an
installed DOCA package. This skill defers all "where is X
documented", "where on disk is Y", and "how do I check the
installed version" questions to the knowledge-map.doca-setup — env preparation, install
verification, env-class debugging, and the I have no install yet
procedure with the NGC container (nvcr.io/nvidia/doca/doca) as
the universal Stage-1 fallback for any user on macOS, Windows, or
Linux without DOCA. This skill assumes doca-setup's preconditions
are already satisfied.doca-flow — DOCA Flow on BlueField.
Extends this skill's ## modify (universal first-app derivation)
with the Flow-specific list of fields to swap.prisma/skills
firebase/agent-skills
Dexploarer/hyper-forge
itsmostafa/aws-agent-skills