NVIDIA

NVIDIA/physicsnemo

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Cannot change return types of public methods in production models, as this breaks user code that depends on the existing return type structure.

NVIDIA/physicsnemo

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Every model must have CI tests verifying constructor instantiation and all public attributes (excluding buffers/parameters) using pytest parameterization.

NVIDIA/physicsnemo

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Every model must have non-regression tests comparing outputs against reference data saved in .pth files, using realistic tensor shapes and pytest parameterization.

NVIDIA/physicsnemo

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Every model must have tests that load from checkpoint files (.mdlus), verify attributes, and compare outputs against reference data to ensure serialization works correctly.

NVIDIA/physicsnemo

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Avoid string-based class selection with many options (>3 choices) in model constructors; prefer dependency injection with instances for better type safety and clearer APIs.

NVIDIA/physicsnemo

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Avoid splatted kwargs (kwargs) in model constructors; use explicit Dict parameters instead to prevent naming conflicts and make APIs clearer.

NVIDIA/physicsnemo

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Use checkminversion() to check optional dependencies without importing, and @requireversion decorator to protect version-specific features; pyproject.toml is the single source of truth for dependencies.

NVIDIA/physicsnemo

Skill Claude CodeCodex ✓ vendor

Official NVIDIA-authored guidance for navigating PhysicsNeMo — pick the model, datapipe, or example for a SciML/AI4Science task (surrogates, forecasting, downscaling, physics-informed, inverse, generative). Points at existing files via live repo search; never writes code. Do NOT use for installation or environment…

NVIDIA/physicsnemo

Skill Claude CodeCodex ✓ vendor

Official NVIDIA-authored guidance for PhysicsNeMo ShardTensor domain parallelism — integrate domain parallelism into training/inference scripts (new or existing) with DDP or FSDP2, write and register shard patches to enable new layers/ops, and bootstrap multi-GPU correctness tests. Use when working with ShardTensor…

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Prepare mirrors and transfer artifacts, configure DeepOps, deploy Slurm or Kubernetes GPU clusters without Internet access, and validate them with machine-readable gates. Use for disconnected, restricted-egress, offline, or air-gapped DeepOps installations and for diagnosing missing package, file, chart, or container…

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Deploy a Kubernetes GPU cluster with DeepOps (Kubespray + GPU Operator) and prove it schedules GPU pods. Use when asked to deploy or rebuild Kubernetes on GPU servers with this repository.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Deploy a Slurm GPU cluster with DeepOps and prove it works. Use when asked to deploy, install, or rebuild Slurm on one or more GPU servers with this repository.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Diagnose NVIDIA driver installation failures on DeepOps-managed nodes — nvidia-smi errors, "No devices were found", DKMS build failures, or GPU pods crash-looping. Use before reinstalling anything.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Provision or reinstall bare-metal servers and test VMs through Canonical MAAS, map deployed machines into DeepOps Ansible inventory with MAAS tags, validate access, or release them safely. Use when operating DeepOps with a MAAS-owned machine lifecycle.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Check whether a DeepOps-deployed Slurm or Kubernetes GPU cluster is healthy and report a machine-readable verdict. Use for health checks, post-deploy verification, "is the cluster working?" questions, and after any node or driver change.

NVIDIA/deepops

Skill Claude CodeCodex ✓ vendor

Use when preparing a shared Hugging Face model cache for Slurm or Kubernetes, pinning downloaded model revisions, validating offline model files, or diagnosing missing snapshots and cache permissions.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Use when adding or removing the optional KAI Scheduler or Run:ai platform on a DeepOps Kubernetes GPU cluster, enabling fractional-GPU scheduling, or diagnosing KAI/Run:ai install or scheduling failures.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Use when checking whether one DeepOps Slurm GPU node is prepared for fine-tuning, diagnosing missing cached training inputs or container prerequisites, or distinguishing readiness from actual training success.

NVIDIA/deepops

Skill Claude CodeCodex ✓ vendor

Use when choosing a DeepOps model workflow, combining shared model caching with single-node serving, or determining whether a fine-tuning or multi-node request has a supported procedure.

NVIDIA/deepops

Skill Claude CodeCodex needs its repo ✓ vendor

Use when serving a cached model on one GPU with vLLM, checking a local completion endpoint, or diagnosing startup and inference failures in the single-node quickstart.

NVIDIA/cuda-quantum

Skill Claude CodeCodex ✓ vendor

Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance.

NVIDIA/cuda-quantum

Skill Claude CodeCodex ✓ vendor

Use when porting circuits from another framework (e.g. Qiskit) into CUDA-Q kernels while preserving the source algorithm and validation fidelity.

NVIDIA/cuopt

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Trigger skill evolution — after solving non-trivial problems, propose skill updates.

NVIDIA/cuopt

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Bundles 9 skills · 366 tokens together

Agent skills for NVIDIA cuOpt: routing (VRP, TSP, PDP), LP/MILP/QP, installation (Python/C/developer), and REST server. Use when building or solving optimization with cuOpt.