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/doca-version

@f64fa0e
by NVIDIA Corporationnvidia/skills3.5k stars
424

Use this skill when the user is doing DOCA version handling — detecting the installed release, validating the four-way match across pkg-config doca-common, applications/VERSION, doca_caps --version, and bfver/mlnx-release on BlueField, reasoning about NGC container tags, looking up whether a capability is on the installed release, or diagnosing build-vs-runtime drift. Trigger even when the user does not explicitly say "DOCA version" or "four-way match" — typical implicit phrasings include "program built but does nothing on the wire", "undefined reference to a symbol the docs claim exists", "DOCA_ERROR_NOT_SUPPORTED at runtime", "counter didn't increment", "what does `latest` mean for this tag", or "is my LTS still supported". Refuse and route elsewhere for installing or choosing DOCA packages (doca-setup), per-library API/capability questions (matching library skill), the cross-library DOCA_ERROR_* taxonomy (doca-programming-guide), or the general debug ladder (doca-debug) — those belong to other skills.

Use this Skill: https://skilld.dev/gh/nvidia/skills/doca-version

This session only. Nothing lands on disk.

skill-card.md

≈1.1k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Description: <br>

Detects the installed DOCA release, validates the four-way version match across pkg-config, applications/VERSION, doca_caps, and bfver/mlnx-release on BlueField, reasons about NGC container tags, looks up capability availability per release, and diagnoses build-vs-runtime version drift. <br>

This skill is ready for commercial/non-commercial use. <br>

Owner

NVIDIA <br>

License/Terms of Use: <br>

Apache 2.0 AND CC-BY-4.0 <br>

Use Case: <br>

Developers and engineers working with NVIDIA DOCA SDK who need to detect installed versions, validate version consistency across host and BlueField components, reason about NGC container tags, or diagnose build-vs-runtime version mismatch. <br>

Deployment Geography for Use: <br>

Global <br>

Requirements / Dependencies: <br>

Requires API Key or External Credential: [No] <br> Credential Type(s): [None] <br>

Do not include secrets in prompts/logs/output; use least-privilege credentials; rotate keys as appropriate. <br>

Known Risks and Mitigations: <br>

Risk: Review before execution as proposals could introduce incorrect or misleading guidance into skills. <br> Mitigation: Review and scan skill before deployment. <br>

Reference(s): <br>

Skill Output: <br>

Output Type(s): [Shell commands, Analysis, Configuration instructions] <br> Output Format: [Markdown with inline bash code blocks] <br> Output Parameters: [1D] <br> Other Properties Related to Output: [None] <br>

Evaluation Agents Used: <br>

  • Claude Code (aws/anthropic/bedrock-claude-opus-4-8) <br>
  • Codex (openai/openai/gpt-5.5) <br>

Evaluation Tasks: <br>

Evaluated against 4 evaluation tasks (3 positive skill-activation, 1 negative) in k8s-sandbox environment with external Skill Evaluator profile. <br>

Evaluation Metrics Used: <br>

Reported benchmark dimensions: <br>

  • Security: Checks whether skill-assisted execution avoids unsafe behavior such as secret leakage, destructive commands, or unauthorized access. <br>
  • Correctness: Checks whether the agent follows the expected workflow and produces the correct final output. <br>
  • Discoverability: Checks whether the agent loads the skill when relevant and avoids using it when irrelevant. <br>
  • Effectiveness: Checks whether the agent performs measurably better with the skill than without it. <br>
  • Efficiency: Checks whether the agent uses fewer tokens and avoids redundant work. <br>

Underlying evaluation signals used in this run: <br>

  • security: Checks for unsafe operations, secret leakage, and unauthorized access. <br>
  • skill_execution: Verifies that the agent loaded the expected skill and workflow. <br>
  • skill_efficiency: Checks routing quality, decoy avoidance, and redundant tool usage. <br>
  • accuracy: Grades final-answer correctness against the reference answer. <br>
  • goal_accuracy: Checks whether the overall user task completed successfully. <br>
  • behavior_check: Verifies expected behavior steps, including safety expectations. <br>

Evaluation Results: <br>

Dimension Num Claude Code (aws/anthropic/bedrock-claude-opus-4-8) Codex (openai/openai/gpt-5.5)
Security 4 100% (+0%) 100% (+0%)
Correctness 4 100% (+60%) 100% (+50%)
Discoverability 4 98% (+36%) 94% (+31%)
Effectiveness 4 100% (+81%) 99% (+49%)
Efficiency 4 99% (+47%) 92% (+61%)

Skill Version(s): <br>

d53d861 (source: git SHA, committed 2026-07-23) <br>

Ethical Considerations: <br>

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their internal team to ensure this skill meets requirements for the relevant industry and use case and addresses unforeseen product misuse. <br>

(For Release on NVIDIA Platforms Only) <br> Please report quality, risk, security vulnerabilities or NVIDIA AI Concerns here. <br>

Source: SKILL.md on GitHub

1 warning2mo3 checks · Risk SAFE
  • Gen Agent Trust Hub2mo

    The skill provides comprehensive guidelines and workflows for NVIDIA DOCA version detection and validation. No security vulnerabilities or malicious patterns were detected.

  • Socket2mo

    No alerts

  • Snyk2mo

    Risk: MEDIUM · 1 issue

Signed by skilld at f64fa0e. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 3 months ago
metadata
{
  "kind": "library"
}
Other metadata
compatibility
No DOCA install required to read this skill (it is an overlay loaded against any DOCA artifact skill); the validation steps within DO require a live DOCA install at /opt/mellanox/doca.

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