nvidia
v1.0.2Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.
by NVIDIAApache-2.0 AND CC-BY-4.05kupdated 3 weeks ago
Source
git clone https://github.com/openai/pluginsClone the source, then follow the repository's marketplace instructions for your runtime. The plugin root is plugins/nvidia/ inside the repository.
Layout
├── .codex-plugin/plugin.json├── skills/aiq-deploy/SKILL.md├── skills/aiq-research/SKILL.md├── skills/cuopt-user-rules/SKILL.md├── skills/dynamo-interconnect-check/SKILL.md├── skills/dynamo-router-starter/SKILL.md├── skills/nemoclaw-user-get-started/SKILL.md├── skills/omniverse-cad-to-simready/SKILL.md├── skills/omniverse-realtime-viewer/SKILL.md├── skills/omniverse-usd-performance-tuning/SKILL.md├── skills/physical-ai-infrastructure-setup-and-resilient-scaling/SKILL.md└── skills/physical-ai-neural-reconstruction/SKILL.md
Skills11
Use when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure.
Use when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend.
Base rules for end users calling NVIDIA cuOpt (routing/LP/MILP/QP/install/server). Not for cuOpt internals — use cuopt-developer for those.
Validate that a Dynamo deployment's NIXL/UCX/NCCL interconnect is ready for disaggregated serving over RDMA/NVLink. Use after recipe-runner brings a deployment up (especially disagg/multi-node) to confirm the KV transport is correct; use troubleshoot for diagnosing already-failed pods.
Start or patch Dynamo router modes and run router endpoint smoke checks. Use for round-robin, KV-aware, least-loaded, or device-aware routing setup; use recipe-runner for recipe deployment and troubleshoot for failure diagnosis.
Installs NemoClaw, launches a sandbox, and runs the first agent prompt. Use when onboarding, installing, or launching a NemoClaw sandbox for the first time. Trigger keywords - nemoclaw quickstart, install nemoclaw openclaw sandbox, nemohermes quickstart, hermes agent nemoclaw, run hermes openshell sandbox, nemoclaw prerequisites, nemoclaw supported platforms, nemoclaw hardware software, nemoclaw windows wsl2 setup, nemoclaw install windows docker desktop.
Coordinate the end-to-end CAD/source-asset to SimReady workflow. Use for broad requests such as CAD to SimReady, source asset to simulation-ready USD, or prop packaging that require conversion, material/physics assignment, SimReady conformance, validation, and optional package creation; deploy or verify Content Agents services first when property assignment is enabled; route single-stage work through nested references.
Use as the top-level router for Omniverse Realtime Viewer USD app requests and focused viewer reference documents.
Top-level workflow skill for USD performance diagnosis and optimization. Use for slow loading, high memory, low FPS, or 'optimize my scene' requests; delegates auth/runtime setup to Phase 0 owners.
Use when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS, including Kubernetes clusters, inference endpoint deployment, OSMO deployment, workload submission readiness, and infrastructure failure recovery. Trigger keywords: physical ai infrastructure, resilient scaling, SDG infrastructure, microk8s, azure aks, NVCF deployment, NIM Operator, OSMO deploy, workflow scaling. Don't trigger for: OSMO log summarization or workload-only operations unless infrastructure setup, scaling, validation, or recovery is requested.
Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, PhysicalAI HF datasets. Do NOT use for SimReady or infra setup.
Manifests1
{
"name": "nvidia",
"version": "1.0.2",
"description": "Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.",
"author": {
"name": "NVIDIA",
"url": "https://github.com/NVIDIA/skills"
},
"homepage": "https://build.nvidia.com/skills/",
"repository": "https://github.com/NVIDIA/skills",
"license": "Apache-2.0 AND CC-BY-4.0",
"keywords": [
"nvidia",
"gpu",
"cuda",
"ai-agents",
"inference",
"llm-serving",
"robotics",
"simulation",
"omniverse",
"openusd",
"digital-twin",
"physical-ai",
"cad"
],
"skills": "./skills/",
"interface": {
"displayName": "NVIDIA",
"shortDescription": "Guided help for NVIDIA AI, GPU, robotics, simulation, and 3D workflows.",
"longDescription": "NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.",
"developerName": "NVIDIA",
"category": "Developer Tools",
"capabilities": [
"Interactive",
"Write"
],
"logo": "./assets/nvidia.png",
"composerIcon": "./assets/nvidia.png",
"brandColor": "#76b900",
"defaultPrompt": [
"Research NVIDIA CUDA-X for me and explain which libraries matter for simulation and robotics",
"How I could turn real-world driving footage into a 3D neural scene for simulation",
"Help me deploy a secure OpenClaw agent"
],
"websiteURL": "https://www.nvidia.com/",
"privacyPolicyURL": "https://www.nvidia.com/en-us/about-nvidia/privacy-policy/",
"termsOfServiceURL": "https://www.nvidia.com/en-us/about-nvidia/terms-of-service/"
}
}