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/doca-socket-relay

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

Use this skill when the operator is driving the DOCA Socket Relay to bridge a socket-oriented host application onto a BlueField DPU peer without rewriting it — picking the deployment shape (in-process, sidecar, or BlueField service container), configuring the host-side socket and the DPU-side forwarding endpoint, walking the bind → connect → round-trip → admit-fleet smoke, or diagnosing a stuck/silent relay. Trigger even when the user does not explicitly mention "DOCA Socket Relay" — typical implicit phrasings include "move my socket app onto the BlueField without rewriting it", "host app gets ECONNREFUSED on the relay", "relay accepts the connection but bytes never arrive on the DPU side", "first round-trip works, the rest hang", "bridge an AF_UNIX (UDS) socket to a DPU peer over Comch", or "I want a sidecar that forwards my socket to the BlueField". Refuse and route elsewhere for the comch programming API, line-rate raw packet I/O via doca-eth, and DOCA install/bring-up — those belong to other skills.

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

This session only. Nothing lands on disk.

skill-card.md

≈1.2k tokens on demand. Your agent reads this file only when SKILL.md points to it.

Description: <br>

Guides an AI agent through deploying the DOCA Socket Relay to bridge a socket-oriented host application onto a BlueField DPU peer without rewriting it — covering deployment-shape selection, host-side socket and DPU-side forwarding-endpoint configuration, the bind-connect-roundtrip-admit-fleet smoke workflow, and layered diagnosis of stuck or silent relays. <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>

External operators, application owners, and AI agents who need to bridge a socket-oriented host application onto a BlueField DPU without rewriting the application against the DOCA programming surface — picking the relay deployment shape, configuring the socket and forwarding endpoint, running the smoke workflow, and diagnosing relay failures. <br>

Deployment Geography for Use: <br>

Global <br>

Requirements / Dependencies: <br>

Requires API Key or External Credential: [Not Specified] <br> Credential Type(s): [None identified] <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): [Configuration instructions, Shell commands, Analysis] <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 internal skill tasks (3 positive activation, 1 negative activation). <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% (+50%) 100% (+20%)
Discoverability 4 100% (+25%) 95% (+34%)
Effectiveness 4 81% (+62%) 92% (+52%)
Efficiency 4 94% (+33%) 93% (+55%)

Skill Version(s): <br>

18a69be (source: git SHA, committed 2026-07-26) <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

No alerts2mo3 checks · Risk SAFE
  • Gen Agent Trust Hub2mo

    The skill is a configuration and operational guide for the NVIDIA DOCA Socket Relay. It provides structured workflows for deploying the relay in different environments, conducting smoke tests, and diagnosing connection issues. The analysis found no evidence of malicious patterns, obfuscation, or unauthorized data exfiltration. All external resources and commands are consistent with the vendor's documented infrastructure.

  • Socket2mo

    No alerts

  • Snyk2mo

    Risk: LOW · No issues

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": "tool"
}
Other metadata
compatibility
Requires DOCA SDK installed at /opt/mellanox/doca on Linux (Ubuntu 22.04/24.04 or RHEL/SLES) with a BlueField DPU attached, plus the socket-oriented host application that will be migrated onto the fabric. Container-shape deployment additionally relies on the BlueField kubelet-standalone runtime per doca-container-deployment.

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