Dev & Engineering ✓ NVIDIA · Official

DOCA Device Management Development Skill

Programmatically manage BlueField and ConnectX state through the DOCA C API.

53/ 100
Use with care

Useful, but reliability, evidence or controls still have material gaps.

See how it was scored ↓
Works as-is in
Codex · Claude Code
Stars
★ 3.8k
Last updated
today
License
Apache-2.0
nvidia-docabluefieldconnectxdevice-management
+3firmware-controlc-apifleet-orchestration

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

This skill is for developers building fleet-management, orchestration, and device-administration tools with the DOCA Management C library. It covers management and representor contexts, capability queries, congestion-control status, diagnostics data, ICM quotas, and scoped raw firmware commands. It serves as a loader for companion workflows covering installation, configuration, building, modification, execution, testing, debugging, and use. It does not install DOCA, provide live telemetry, perform benchmarking, or ship application source code.

Guides agents through doca_mgmt_dev_ctx and doca_mgmt_dev_rep_ctx setup; querying or setting capabilities such as data-direct with doca_mgmt_device_caps_general_*; managing global congestion-control status, diagnostics data, and ICM quotas; issuing doca_mgmt_raw_cmd with configuration or debug scopes; and diagnosing DOCA_ERROR_* across configuration, lifecycle, capability, fwctl ioctl, and firmware layers. Its modification workflow includes pre-state capture, post-write verification, and rollback preparation.

Good fit
  • Building a data-center fleet inventory tool that reads device capabilities and state from each BlueField.
  • Querying or setting data-direct and related attributes for a specific VF representor.
  • Setting per-device or per-representor ICM quotas and reading allocation status.
  • Issuing a vendor-documented raw firmware-control command with the appropriate scope.
  • Investigating `DOCA_ERROR_IO_FAILED` or fwctl ioctl failures from a `doca_mgmt_*` call.

How do you install this skill?

Before you use it
  • This is a static text-only review; DOCA, compilation, device operations, and benchmark trials were not executed.
  • Any write may change BlueField/ConnectX device state; verify the installed version, capabilities, target device, privileges, maintenance window, out-of-band access, and rollback path in the real environment.
  • The BENCHMARK.md dataset is unavailable, so its percentages are not independent validation.
  • SKILLCARD.yaml still contains placeholder signature, version, and scan fields and has source-path and license-metadata inconsistencies.
  • Do not treat the documented APIs, error mappings, or version assumptions as verified against the current DOCA installation.
Before you start
Your agent needs
  • Shell / CLI
  • Network access
  • Local filesystem
Install first
  • DOCA SDK installed at /opt/mellanox/doca
  • Linux
  • BlueField DPU or ConnectX NIC
  • root or device-administration capability
  • /dev/fwctl* character device
  • npx skills CLI for installation

Use a Linux host with the DOCA SDK already installed at /opt/mellanox/doca, plus an attached BlueField DPU or ConnectX NIC. Install the NVIDIA skills collection with the default skills CLI: npx skills add nvidia/skills. To install this known skill without prompts, use npx skills add nvidia/skills --skill doca-mgmt --yes. The source does not document a standalone manual-copy installation procedure for this skill folder.

Generic route: install into Claude Code manually (macOS / Linux)
tmp="$(mktemp -d)"
git clone --depth 1 https://github.com/NVIDIA/skills.git "$tmp"
mkdir -p ~/.claude/skills
cp -R "$tmp/skills/doca-mgmt" ~/.claude/skills/
rm -rf "$tmp"

Generated from the source repository and skill path; it copies only this skill's folder. If the author's install steps above differ, follow those first. To scope it to one project, replace ~/.claude/skills with that project's .claude/skills.

How do you use this skill?

Try saying

Once installed, send your agent any of these to trigger it:

  • Using the C API, query data-direct capability for a specified VF representor and verify the result.

On a host with DOCA installed, give the agent a concrete DOCA Management request such as: “Using the C API, query data-direct capability for a specified VF representor and verify the result.” For install, configure, build, modify, run, test, debug, or use tasks, load TASKS.md; for capability boundaries, command scopes, error taxonomy, or safety policy, load CAPABILITIES.md. The source does not provide a directly compilable example application.

What are this skill's strengths and limitations?

Pros
  • Covers clearly defined management-plane operations across contexts, representors, capabilities, congestion control, diagnostics, quotas, and raw commands.
  • Provides a command-scope ladder covering configuration and multiple debug read/write levels.
  • Requires pre-state capture, post-write verification, and rollback preparation for modifications.
  • Targets C and C++ while preserving the public C ABI as the authority for FFI and bindings.
Limitations
  • Assumes DOCA is already installed and does not provide DOCA installation guidance.
  • Runtime management operations generally require root or equivalent device-admin privileges and `/dev/fwctl*`.
  • All public `doca_mgmt_*` symbols are marked EXPERIMENTAL, so interfaces may change between releases.
  • Ships no application source, build manifests, bindings, samples, or raw-command opcode catalog.
  • The supplied source does not include companion-file contents, test results, or broader platform coverage evidence.

How does this skill compare with similar options?

Side by side with related skills; every score comes from the same FSRS standard.

Skill FS score Stars Last updated License
DOCA Device Management Development Skill this page ✓ NVIDIA · Official 53 · Use with care ★ 3.8k today Apache-2.0
DOCA SHA Acceleration ✓ NVIDIA · Official 56 · Use with care ★ 3.8k today Apache-2.0
DOCA Compress Hardware Offload ✓ NVIDIA · Official 58 · Recommended ★ 3.8k today Apache-2.0
DOCA AES-GCM Acceleration ✓ NVIDIA · Official 57 · Use with care ★ 3.8k today Apache-2.0
DOCA Erasure Coding Development Skill ✓ NVIDIA · Official 49 · Use with care ★ 3.8k today Apache-2.0

The skill defines itself as a management-plane C API guide. Use doca-telemetry or doca-telemetry-exporter for streaming observability, doca-caps for interactive read-only capability snapshots, doca-setup for DOCA installation, and doca-bench for live performance benchmarking. It also excludes direct mlxconfig operation, BFB or firmware reflashing, and DOCA installation.

How did FollowSkills review this skill?

FollowSkills review · FSRS-2.0
Use with care
53/ 100 5-point scale 2.7 / 5
The upstream repository has new commits since this review. The score still applies to the reviewed revision shown and may not cover the latest changes.
1Trust18 / 25 · 3.6/5

The documentation explicitly requires least privilege, user confirmation, capability checks, pre-write state capture, narrowest command scope, maintenance windows, out-of-band access, replica-first validation, post-write verification, and rollback. Deducted 7 points because it provides no implemented permission isolation, confirmation mechanism, rollback executor, or detailed sensitive-data handling, and dependencies and external sources are not independently verified in the supplied material.

2Reliability8 / 20 · 2.0/5

SKILL.md, CAPABILITIES.md, and TASKS.md give substantial guidance on prerequisites, context lifecycles, error taxonomy, failure routing, and abnormal-input feedback; BENCHMARK.md reports evaluation results. Deducted 12 points because nothing was executed here, the benchmark dataset is unavailable, there is no committed test suite covering key paths, and no reproducible CI evidence; several paths depend on omitted skills or an installed runtime environment.

3Adaptability10 / 15 · 3.3/5

The audience, scenarios, implicit trigger phrases, capability boundaries, and routing to telemetry, caps, bench, and setup skills are clearly described. Deducted 5 points because Chinese-language interaction, non-Linux or device-absent environments, and mainland-China network fit are not addressed; the core function does rely mainly on a local SDK and device rather than entirely on unreachable overseas services.

4Convention8 / 15 · 2.7/5

The skill uses a thin-loader plus CAPABILITIES.md/TASKS.md progressive-disclosure structure and documents examples, dependencies, limitations, error handling, version compatibility, and maintenance routing; SKILL.md declares Apache-2.0. Deducted 7 points because author, formal version, changelog, and explicit maintenance ownership are incomplete; SKILLCARD.yaml contains unsigned placeholders and conflicts with the target-path metadata on source path and licensing; BENCHMARK.md also records schema findings.

5Effectiveness6 / 15 · 2.0/5

The supplied material covers context creation, capability queries, state modification, ICM quotas, raw_cmd, debugging, and safe change workflows, while the benchmark report claims strong skill-assisted correctness and effectiveness. Deducted 9 points because the evaluation dataset is unavailable and results cannot be independently checked; the skill supplies no compilable samples or templates, and usable output still depends on local installation, device state, version matching, and other skills.

6Verifiability3 / 10 · 1.5/5

The files provide concrete API names, error codes, command scopes, paths, and verification procedures, with cross-references among the skill files. Deducted 7 points because there is no executable test evidence, complete CI coverage, or independently reproducible benchmark dataset; the skill card's signature, version, and scan fields remain placeholders, limiting auditability.

1 2 3 4 5 6

Open a dimension to read why it scored that way

Reviewed Jul 20, 2026 Reviewed revision 55f18499943e Review evidence[1][2][3][4][5][6][7][8][9]

Evidence confidence:Low — Mostly static review, author material or a limited demo; useful for discovery, not high-risk decisions.

See the full review method →

FAQ

What environment does it require?
It requires Linux, the DOCA SDK installed at `/opt/mellanox/doca`, an attached BlueField DPU or ConnectX NIC, and—at runtime—an exposed `/dev/fwctl*` device. Administrative privileges are generally required for management operations.
Can I use it before installing DOCA?
No. The skill assumes DOCA is installed and routes installation work to `doca-setup`.
Does it generate a complete DOCA Management application?
No. It deliberately avoids shipping pre-written management application code and directs users toward verified samples from the installed DOCA package.
How does it handle risky device changes?
It recommends capturing pre-state, selecting the correct command scope, re-querying after writes, and preparing rollback, while still requiring version, capability, privilege, and device-specific validation.

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