claudemods

Sourcesnvidia/skills

nvidia/skills Indexed

Agent Skills for NVIDIA products — install into Claude Code, Codex, and other coding agents to run Physical AI, robotics, simulation, CUDA, and RAG workflows end to end.

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Indexed The index holds package records for this repository. The package count is historical registry records; it does not mean those packages are available now.

Repository

Canonical name
NVIDIA/skills
GitHub repository ID
1167034425
Package records
394 (historical registry records, not current availability)

Discovery and queue

First recorded source
marketplace:anthropics/claude-plugins-official
Discovered
Queue state
ok
Recorded errors
0
Last settled processing
Next-check eligibility
Eligible from

The first recorded source is what the queue stored first, not the full discovery history. The error count increases when processing ends in the error state and resets after a successful settlement; it is not a count of all attempts. “Last settled processing” is when it finished, not when it started.

Eligibility is calculated as of . It is not a schedule: each collector run handles only a limited number of sources, and being eligible does not promise when a check happens.

Last saved scan

Repository metadata read
Scan status
complete
Scan saved
Extractor version
2
Continuation record
None

The scan record is separate from the queue state: the queue state shows processing progress, the scan record shows what was last saved. A continuation record only means unfinished state is stored; it has no remaining count.

Source-file evidence coverage

Raw counts of the pinned source files that stored package versions reference in this repository. They show what has been recorded, not how complete the repository is.

Scope and limits

Counts distinct pinned file links (repository, commit, path) across all stored versions, from any package, that name exactly this repository's canonical name. Files of packages owned by this repository are not counted unless some version links to them here. Alias names are not merged and no history is guessed from a current name.

“Known” means a regular-file identity is recorded. It does not mean a whole directory or package is covered. Links that are not valid pinned file URLs are not counted.

395 pinned source files referenced

  • 395 known
  • 0 absent at commit
  • 0 file listing truncated
  • 0 unsupported
  • 0 not recorded
  • 0 read failed

Deduplicated by repository, commit and path; the same path at two commits counts as two file identities. These are not component-group counts.

Failed source-commit reads 0

No source commit has a stored failed read for files that are still unrecorded.

Linked packages 394

Linked by verified repository identity. The count is historical registry records, not current availability.

Showing 261–280 of 394 results

  • nvflare-sharedSkill

    Internal NVFLARE conversion references and templates. Use only when another NVFLARE skill directs you to a shared workflow, policy, or asset.

  • nvidia-skill-finderSkill

    Use for NVIDIA-related requests where an NVIDIA skill might help, even if the user did not ask for a skill. Trigger on NVIDIA products, hardware, software, SDKs, GPUs, Jetson/JetPack/L4T/BSP/SDK Manager/driver/flashing/setup, CUDA, NIM, Ne…

  • nvidia-skillsPlugin

    Find the right NVIDIA skill for GPU acceleration, CUDA, AI agents, data loading, training, inference, robotics, Physical AI, Omniverse, simulation, and other NVIDIA-powered workflows.

  • nvmolkit-usageSkill

    Use when writing or debugging nvMolKit Python code for GPU-accelerated RDKit fingerprints, similarity, conformers, clustering, and molecular searches.

  • omniverse-cad-to-simreadySkill

    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 conform…

  • omniverse-realtime-viewerSkill

    Use as the top-level router for Omniverse Realtime Viewer USD app requests and focused viewer reference documents.

  • omniverse-usd-performance-tuningSkill

    Top-level workflow skill for USD performance diagnosis and optimization. Handles slow loading, high memory, low FPS, and broad scene-optimization requests; delegates auth/runtime setup to Phase 0 owners.

  • openfold2-nimSkill

    Use this skill for OpenFold2, NVIDIA's BioNeMo NIM microservice for monomer protein structure prediction. Invoke whenever the user mentions OpenFold2, AlphaFold2-like monomer folding, protein sequence-to-structure prediction, A3M MSAs, mmC…

  • openfold3-nimSkill

    Use this skill for OpenFold3, NVIDIA's BioNeMo NIM microservice for biomolecular structure prediction. Invoke whenever the user mentions OpenFold3 or needs protein, protein-ligand, protein-DNA/RNA, or multi-chain complex prediction with th…

  • paidf-augmentationSkill

    Use when authoring or validating PAIDF augmentation YAML configs, or running remote Cosmos Transfer (including Cosmos3 WSM controls), Cosmos Predict, image-edit, or image-to-video inference.

  • paidf-auto-labelingSkill

    Use when a user needs to get started with PAIDF Auto-Labeling, plan a scenario, run or debug a shipped cookbook, author prompts or cookbooks, migrate a pipeline, or configure a stage. Confirm critical inputs (data path, output path, endpoi…

  • paidf-cosmos-predictSkill

    Prepare and run PAIDF Cosmos Predict video generation for DEFT media samples.

  • paidf-curation-and-retrievalSkill

    Use when operating PAIDF Curation and Retrieval or NVIDIA Cosmos Curator pipelines (split, filter, caption, embed, dedup, shard, image annotate) or PAIDF Data Mining nearest-neighbor matching on Curator embeddings. Activate for Make or CLI…

  • paidf-orchestration-setupSkill

    Audit, prepare, and deploy PAIDF Orchestration on a Kubernetes GPU cluster - single-GPU H100/L40S hosts, managed Kubernetes, kubeadm, and similar. Select for requests to set up, install, deploy, configure, or check a PAIDF Orchestration en…

  • paidf-orchestration-write-dagSkill

    Use when a user describes a custom PAIDF Orchestration pipeline — a specific ordered combination of stages such as augmentation only, auto-labeling only, detection+captioning only, or image attribute augmentation without full auto-labeling…

  • physical-ai-defect-image-generationSkill

    Use when the user wants to orchestrate defect image generation with NVIDIA Cosmos AnomalyGen (Cosmos-Predict2-derived) on OSMO for PCBA, metal surface, and glass inspection. The Day 0 path handles cold-start with USD-to-ROI, image-edit aug…

  • physical-ai-event-video-generationSkill

    Run the PAIDF Orchestration Event Video Generation DAG on Kubernetes - image-to-video anomaly generation, auto-labeling, and anomaly dataset generation. Select for requests about event video generation, anomaly video generation, image-to-v…

  • physical-ai-image-attribute-augmentationSkill

    Run the PAIDF Orchestration Image Attribute Augmentation DAG on Kubernetes - person-crop clothing augmentation, attribute search, and augmented dataset generation. Select for requests about image attribute augmentation, person attribute se…

  • physical-ai-infrastructure-setup-and-resilient-scalingSkill

    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 …

  • physical-ai-neural-reconstructionSkill

    Router for NVIDIA NuRec/NRE: USDZ rendering, NCore conversion, 3DGS, gRPC sensor sim, carline adaptation, PhysicalAI HF datasets. Do NOT use for SimReady or infra setup.

Saved scan notes 0

No additional scan notes are stored.

Recorded aliases 0

When last recorded, these names pointed to this repository. This is a recorded resolution, not a live GitHub check; packages and metadata are never merged because of it.

No aliases pointing to this repository are recorded.

Unsupported marketplace entries 0

Entries in this repository's marketplace that this registry does not support yet. They are preserved source data and are never fetched or executed.

No unsupported entries are recorded.