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Get Started Free →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 → init → start → use → stop → destroy lifecycle, validating a spec before commit, or decoding a DOCA_ERROR_* return with doca_error_get_descr(). Trigger even when the user does not say "DOCA programm
| Test case | Without → With | Effect | Δ tokens | Δ turns |
|---|---|---|---|---|
| case-04 | ✗→✓ | ▲ Improved | 120% | 0% |
| case-15 | ✗→✓ | ▲ Improved | 103% | 0% |
| case-19 | ✗→✓ | ▲ Improved | 87% | 0% |
| case-22 | ✗→✓ | ▲ Improved | 101% | 0% |
| case-17 | ✓→✗ | ▼ Worse | 129% | 0% |
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.
worked example: "I want to write my first DOCA Flow application." Answered by the modify-a-shipped-sample workflow in TASKS.md ## modify plus the canonical build pattern in TASKS.md ## build.
example: "How do I compile a program that calls `doca_rdma_?"* Answered by the pkg-config doca-<library> pattern in [TASKS.md ## build](TASKS.md#build) (C/C++ Track 1) and the FFI/bindings pattern in Track 2.
example: "What's the right order of `doca_flow_pipe_ calls in my program?"* Answered by the cfg-create / init / start / use / stop / destroy template in [CAPABILITIES.md ## Capabilities and modes](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 + the program-class debug order in TASKS.md ## debug.
worked example: "My Flow program runs cleanly but no traffic is matched." Answered by the validate-before-commit rule in CAPABILITIES.md ## Safety policy and the layered program-class debug ladder in TASKS.md ## debug.
bindings)?" — worked example: "How do I call DOCA Comch from Rust without writing C?" Answered by Track 2 of TASKS.md ## build (FFI against the public C ABI) and the language-neutral lifecycle in CAPABILITIES.md ## Capabilities and modes.
applications? What's the difference between a sample and an application?" — worked example: "I tried to build all DOCA apps and 20/159 failed — which ones are real regressions vs missing optional stacks?" Answered by the sample-vs-application model and the category / dependency / skip-vs-fail taxonomy in 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/`](https://docs.nvidia.com/doca/sdk/), the public catalog at [`catalog.ngc.nvidia.com`](https://catalog.ngc.nvidia.com/), the public GitHub repos under [`github.com/NVIDIA`](https://github.com/NVIDIA) / [`github.com/NVIDIA-DOCA`](https://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:
tools) and which side of the wire they run on.
pkg-config + meson build pattern any DOCA applicationfollows, regardless of which library it consumes.
sample workflow that every library skill extends with library-specific overrides — moved here from doca-setup because it is a programming verb, not an env verb.
stop → destroy) and how it manifests across libraries.
DOCA_ERROR_* pattern, doca_error_t, anddoca_error_get_descr() — the cross-library shape, not Flow- or RDMA-specific overlays.
that every library skill inherits.
(C/C++ directly, FFI / bindings for Rust / Go / Python / …) — the skill keeps the patterns language-neutral and points the agent at the public C ABI as the authoritative surface.
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`](../doca-setup/SKILL.md), 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.
do I install?" — routing / orientation questions belong in doca-public-knowledge-map.
to send a message?" — library-internal API questions belong in the matching library skill (e.g. 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 theabstract: 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 programmingverbs: 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:
includes C / C++ files, Rust crates, Go packages, Python modules, and wrapper code for any other language. The DOCA API surface evolves between releases and code written from documentation prose cannot be verified without compiling / linking / FFI-loading it against the live library on a real install. The verified DOCA application source code is the shipped C samples on the user's installed system; the agent's job is to route the user to that file and prescribe a minimum-diff modification on it (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 aprogramming-class question (not env, not routing, not library-API).
error taxonomy, the program-side observability surface, and the safety policy that every library skill inherits, see CAPABILITIES.md.
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, installverification, 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.
Other measured skills in the registry, with their headline benchmark lift.