Description: <br>
Operate the DOCA UROM Service container on BlueField Arm for remote memory operations (puts, gets, atomics, collectives) enqueued by a paired host using doca-urom: pull the NGC image, choose the UCX component, size queues, configure Comch pairing, and align host and service versions. <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 and platform teams who deploy and operate the DOCA UROM Service container on BlueField to receive and execute the remote memory operations that HPC, UCX, and MPI workloads on the host enqueue through doca-urom. <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>
- CAPABILITIES.md <br>
- TASKS.md <br>
- NVIDIA DOCA SDK Documentation <br>
- DOCA Samples <br>
- DOCA Platform Framework <br>
Skill Output: <br>
Output Type(s): [Configuration instructions, Analysis] <br> Output Format: [Markdown] <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 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% (+30%) |
| Discoverability | 4 | 100% (+25%) | 95% (+34%) |
| Effectiveness | 4 | 88% (+59%) | 94% (+59%) |
| Efficiency | 4 | 94% (+43%) | 83% (+55%) |
Skill Version(s): <br>
56cf891 (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>