Dev & Engineering ✓ NVIDIA · Official docac-cppmesonpkg-configffibluefieldgpu-programming

DOCA Programming Guide

Guides developers through building, testing, and debugging library-agnostic DOCA applications from shipped samples.

FollowSkills review · FSRS-2.0
Not recommended
54/ 100 5-point scale 2.7 / 5
Trust18 / 25 · 3.6/5

The skill defines scope boundaries, validation-before-commit, staged execution, smallest-scope operation, install-tree protection, and routing between environment and program failures. This supports a strong but incomplete trust score. Points were deducted because hardware-affecting commands, containers, file copying, and runtime actions lack a consistent user-confirmation gate, rollback procedure, and explicit external-effect confirmation; license metadata is also inconsistent across files.

Reliability8 / 20 · 2.0/5

SKILL.md, CAPABILITIES.md, and TASKS.md provide structured loading order, prerequisites, lifecycle guidance, error taxonomy, and diagnostic routing, with frequent stop-and-route behavior on failure. Points were deducted because key paths were not executed during this static review, many API and cross-library claims lack committed tests, and the benchmark dataset is unavailable, so the reported benchmark cannot establish full reproduction.

Adaptability10 / 15 · 3.3/5

The audience, trigger phrases, use cases, and non-fit boundaries are unusually explicit, and the skill addresses both C/C++ and FFI consumers. Points were deducted because it depends on an installed DOCA environment, Linux or a container, and often real hardware; Chinese-language interaction is not addressed, nor is reachability of public documentation, forums, or NGC from mainland-China networks.

Convention8 / 15 · 2.7/5

The documentation is layered into a loader, capability reference, and task workflows, with dependency notes, related-skill routing, examples, version rules, and stated limitations. Points were deducted for the missing author field, missing recommended Instructions/Examples sections, lack of a clear maintenance owner and update path, no formal changelog, and inconsistent licensing: Apache-2.0 in SKILL.md versus Apache 2.0 AND CC-BY-4.0 in skill-card.md.

Effectiveness6 / 15 · 2.0/5

The skill covers first-app derivation, pkg-config/Meson builds, lifecycle management, error interpretation, testing, and debugging with concrete workflows; BENCHMARK.md reports a pass and strong assisted metrics. Points were deducted because it ships no directly buildable sample or template, depends on the user's installation, version, hardware, and library-specific overlays, and the unavailable evaluation dataset plus lack of execution prevents confirming directly usable results.

Verifiability4 / 10 · 2.0/5

Most documented workflows, commands, paths, and symbols are auditable from the supplied files, with references to public documentation, samples, and repositories; BENCHMARK.md adds limited evaluation-summary evidence. Points were deducted because this review performed no execution, the benchmark dataset and raw trial records are missing, and independent corroboration is thin.

Evidence confidence:Low Reviewed Jul 20, 2026 Reviewed revision 55f18499943e
Before you use it
  • Running or modifying DOCA programs may affect real NICs, DPUs, representors, queues, or network traffic; obtain explicit user confirmation and define a recoverable rollback before execution.
  • The skill depends on a version-compatible DOCA installation, Linux or container access, and sometimes real hardware; it provides no Chinese-language or mainland-China network reachability guarantee.
  • Do not treat the BENCHMARK.md summary as independent test proof; the raw dataset is unavailable and this review executed nothing.
  • Before publication, reconcile the license, author, and maintenance metadata between SKILL.md and skill-card.md.
Review evidence [1][2][3][4][5][6][7][8]
See the full review method →

What does this skill do, and when should you use it?

This skill is for external developers who consume DOCA libraries in applications. It covers first-application derivation, the canonical pkg-config and Meson build pattern, the common DOCA object lifecycle, cross-library error handling, observability, validation, and debugging. C and C++ are the canonical paths, while Rust, Go, and Python are addressed through FFI or bindings against the public C ABI. It assumes the DOCA environment is already prepared and routes installation, version lookup, and library-internal API questions elsewhere.

Reads the skill guidance and its CAPABILITIES.md and TASKS.md companion materials; directs users to C samples installed under /opt/mellanox/doca for minimal-diff customization; describes the pkg-config doca-{library} plus Meson build pattern and non-C FFI against the public C ABI; explains the cfg-create→init→start→use→stop→destroy lifecycle; and guides users through doca_error_get_descr() for DOCA_ERROR_* values, validation, testing, and the program-class debugging ladder.

  1. A developer writing a first application against any DOCA library and looking for a shipped sample to modify.
  2. A C or C++ developer choosing the standard pkg-config and Meson build line for APIs such as doca_rdma_*.
  3. A Rust, Go, or Python developer calling DOCA through the public C ABI without authoring a C wrapper.
  4. A developer diagnosing DOCA_ERROR_BAD_STATE or an application that starts successfully but produces no traffic.
  5. A developer classifying sample and application build failures, including missing optional GPU, RMAX, or MPI stacks.

What are this skill's strengths and limitations?

Pros
  • Covers the library-agnostic DOCA workflow from first sample through build, lifecycle, errors, observability, testing, and debugging.
  • Provides both direct C/C++ guidance and language-neutral FFI guidance for Rust, Go, Python, and similar consumers.
  • Clearly separates programming questions from setup, public-knowledge routing, and library-internal API questions.
  • Uses shipped, installed samples as the source for verified application code instead of supplying unverified implementations.
Limitations
  • The SKILL.md is a thin loader; substantive workflows are delegated to CAPABILITIES.md and TASKS.md.
  • It does not include application source, bindings, standalone build manifests, or samples/reference subtrees.
  • It does not handle DOCA installation, hugepages, device preparation, version lookup, or library-specific API construction.
  • Validation steps require a live DOCA installation at /opt/mellanox/doca.

How do you install this skill?

Use the installation flow documented in the repository README: npx skills add nvidia/skills --skill doca-programming-guide --yes. The CLI prompts for the installation destination; cloning the repository or manually copying the folder is not required. The source does not specify a fixed local installation path.

How do you use this skill?

After installation, prompt the agent with a programming request such as “I want to write my first DOCA Flow application” or “How do I call DOCA Comch from Rust without writing C?”. The DOCA environment should already be ready and pkg-config doca-{library} should resolve. Route installation, hugepages, device visibility, version lookup, and library-specific API construction to the related skills.

FAQ

Does this skill include a buildable DOCA sample?
No. It directs users to the official C samples installed under /opt/mellanox/doca and prescribes minimal modifications.
Can it be used without a DOCA installation?
The guidance can be read without an installation, but its validation steps require one. Installation and the no-install NGC container path belong to doca-setup.
Does it explain Flow pipe topology or RDMA queue construction?
Not as its primary scope. Those library-internal API questions should use the matching library skill layered on top of this guide.
Do I need to clone NVIDIA/skills to install it?
No. The README documents npx skills add nvidia/skills --skill doca-programming-guide --yes.

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