How do I install nvidia-skills?

Run these in Claude Code: /plugin marketplace add NVIDIA/skills then /plugin install nvidia-skills@nvidia-official. Then prompt normally.

Does nvidia-skills auto-invoke its skills?

Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.

Is nvidia-skills free?

Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.

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nvidia-skills

Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.

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Install on Claude Code

> /plugin marketplace add NVIDIA/skills
> /plugin install nvidia-skills@nvidia-official

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Repo: NVIDIA/skills

In this plugin

200 skills 3 agents

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What's inside

Skills

200

/nvidia-skill-finderUse 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, NeMo, Omniverse/OpenUSD/SimReady,/accelerated-computing-cudfOfficial NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads./aiq-deployUse when asked to install, deploy, run, validate, troubleshoot, or stop NVIDIA AI-Q Blueprint infrastructure./aiq-researchUse when asked to run deep research or AI-Q research through a reachable NVIDIA AI-Q Blueprint backend./amc-run-sample-calibrationRun end-to-end calibration on the shipped sample dataset (sdg_08_2_sample_data_010926.zip) against a running AMC microservice. Use when user says 'test sample dataset', 'run sample calibration', 'verify AMC install', or 'launch and test'./amc-run-video-calibrationCalibrate a new dataset from pre-recorded video files via the AutoMagicCalib REST API. Use when user has local MP4s and says 'calibrate my videos', 'run AMC on these videos', or similar. For RTSP/live streams, use amc-run-rtsp-calibration instead.

Show all 200 skills

Agents

logs-readerSpawn a general-purpose subagent and pass these instructions as the prompt.workflow-expertSpawn a subagent with access to the OSMO CLI component reference and pass these instructions as the prompt. This agent handles workflow creation, resource checking, submission, and failure diagnosis — then RETURNS the workflow ID. It does NOT monitor workflows. The calling agent reporterRender `${RESULTS_DIR}/DEFT_Loop_Report.html` from the canonical disk state, following the protocol in `references/REPORT_RENDERING.md` and the template at `references/DEFT_Loop_Report.html`.

README

Read on GitHub

NVIDIA Agent Skills

Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.

📖 Docs: docs.nvidia.com/skills · 📺 Livestream: From Vulnerable to Verified · 📝 Blog: NVIDIA Verified Agent Skills: Capability Governance for AI Agents

Skills are portable instruction sets that teach AI agents how to use NVIDIA software optimally: Physical AI and robotics workflows, simulation, CUDA-X libraries, RAG and AI Blueprints, and platform tools. This repository is a catalog: skills are maintained in their respective product repos, and mirrored here daily via an automated sync pipeline. Skills are being added continuously, so check back for updates. We are building this infrastructure in the open, and contributions are welcome. See the Roadmap for what is planned next.

Quickstart

Install NVIDIA skills with the default skills CLI flow:

npx skills add nvidia/skills

The CLI runs through npx and prompts you to choose a skill and install destination. You do not need to clone this repo or copy skill folders by hand.

Requires a current skills CLI (v1.5.16 or newer). Installing via npx skills@latest add nvidia/skills always uses the latest. On older CLIs (v1.5.15 and earlier), skills may install but not appear in Claude Code — see Troubleshooting.

The skill is available the next time your agent loads skills and encounters a relevant task. For example, ask your agent to "solve a linear programming problem with cuOpt" and the skill guides it through the cuOpt Python API. In Claude Code, run /reload-skills to load newly installed skills in your current session.

Install One Skill Without Prompts

Use this when you already know the skill name and want to skip prompts.

npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --yes

Replace cuopt-numerical-optimization-api with any skill name from the Skill Catalog.

Install for a Specific Agent

Use --agent to target a specific AI coding agent. Initially, we'll support common client targets, expanding the list over time. For the full list of clients supported by the spec, see the skills CLI Supported Agents table.

Claude Code

npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent claude-code

Codex

npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent codex

Snowflake CoCo

npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent cortex

Cursor

npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent cursor

Kiro

npx skills add nvidia/skills --skill cuopt-numerical-optimization-api --agent kiro-cli

Use --agent more than once to install the same skill into multiple agents.

npx skills add nvidia/skills \
  --skill cuopt-numerical-optimization-api \
  --agent claude-code \
  --agent codex \
  --agent cursor \
  --agent kiro-cli

Keep Skills Up to Date

New skills land continuously, and existing ones are revised, renamed, or consolidated as the catalog evolves. Refresh what you have installed with:

npx skills update

Run it interactively and the CLI also flags skills that were removed or merged upstream (for example, when several skills are consolidated into one) and offers to remove the stale local copies. Use npx skills list to see what is installed and npx skills check to preview what is out of date first.

Browse the Catalog

Use this when you want to see available NVIDIA skills before installing anything.

npx skills add nvidia/skills --list

For non-interactive installs, global installs, agent-specific installs, updates, removals, and fallback manual copying, see Advanced installation.

Skill Catalog

Product	Description	Skills
AIQ	NVIDIA AI-Q Blueprint - deploy local AI-Q services and run shallow or deep research workflows as agent skills.	`aiq-research`, `aiq-deploy`
CUDA-Q	CUDA Quantum — onboarding guide for installation, test programs, GPU simulation, QPU hardware, and quantum applications.	`cudaq-guide`
cuDF	Official NVIDIA-authored guidance for NVIDIA cuDF GPU DataFrames, pandas acceleration, dask-cuDF, ETL, joins, groupby, CSV/Parquet I/O, nullable semantics, and multi-GPU DataFrame workloads.	`accelerated-computing-cudf`
cuOpt	GPU-accelerated optimization — vehicle routing, linear programming, quadratic programming, installation, server deployment, and developer tools.	`cuopt-install`, `cuopt-multi-objective-exploration`, `cuopt-numerical-optimization-api`, `cuopt-numerical-optimization-formulation`, `cuopt-routing-api-python`, `cuopt-server-api-python`
cuPyNumeric	NumPy and SciPy on multi-node multi-GPU systems — skills to help with installing cuPyNumeric, migrating existing NumPy code, and doing parallel I/O	`cupynumeric-hdf5`, `cupynumeric-install`, `cupynumeric-migration-readiness`, `cupynumeric-parallel-data-load`
DALI	GPU-accelerated data loading and processing with NVIDIA DALI.	`dali-dynamic-mode`
Data Designer	Build declarative synthetic dataset generation pipelines with NeMo Data Designer.	`data-designer`
DeepStream	Agentic skills for guided DeepStream development.	`amc-run-sample-calibration`, `amc-run-video-calibration`, `amc-setup-calibration-stack`, `deepstream-dev`, `deepstream-generate-pipeline`, `deepstream-import-vision-model`, `deepstream-profile-pipeline`, `deepstream-sop`
Digital Health	Agent skills for the clinical ASR evaluation flywheel — term curation, synthetic clinical-speech benchmark generation, KER (Keyword Error Rate) scoring, and fine-tune guidance.	`digital-health-clinical-asr-setup`, `digital-health-clinical-asr-build`, `digital-health-clinical-asr-eval`, `digital-health-clinical-asr-finetune`
DOCA	Teach AI agents to use the NVIDIA DOCA SDK on BlueField DPUs and ConnectX NICs — setup, libraries, services, tools, deployment, and debugging.	`doca-bare-metal-deployment`, `doca-bf3-deployment`, `doca-bf4-deployment`, `doca-collectx-deployment`, `doca-container-deployment`, `doca-debug`, `doca-hardware-safety`, `doca-programming-guide`, `doca-public-knowledge-map`, `doca-setup`, `doca-structured-tools-contract`, `doca-upgrade`, `doca-version`, `doca-aes-gcm`, `doca-argp`, `doca-comch`, `doca-common`, `doca-compress`, `doca-devemu`, `doca-dma`, `doca-dpa`, `doca-dpdk-bridge`, `doca-erasure-coding`, `doca-eth`, `doca-flow`, `doca-flow-dpa-provider`, `doca-gpi`, `doca-gpunetio`, `doca-mgmt`, `doca-pcc`, `doca-pcc-ztr-rttcc-algo`, `doca-rdma`, `doca-rdmi`, `doca-rmax`, `doca-sha`, `doca-sta`, `doca-telemetry`, `doca-telemetry-exporter`, `doca-urom`, `doca-verbs`, `doca-argus`, `doca-dms`, `doca-firefly`, `doca-urom-svc`, `doca-bench`, `doca-bench-extension`, `doca-caps`, `doca-comm-channel-admin`, `doca-dpa-hl-tracer`, `doca-flow-dpa-perf`, `doca-flow-grpc-server`, `doca-flow-perf`, `doca-flow-tune`, `doca-gpunetio-ib-write-bw`, `doca-gpunetio-ib-write-lat`, `doca-pcc-counters`, `doca-sha-offload-engine`, `doca-socket-relay`, `doca-spcx-cc`, `doca-telemetry-utils`
Dynamo	NVIDIA Dynamo deployment bring-up on Kubernetes — pick and deploy recipes, start router modes, validate disagg NIXL/UCX/NCCL interconnect, and triage day-2 failures.	`dynamo-interconnect-check`, `dynamo-recipe-runner`, `dynamo-router-starter`, `dynamo-troubleshoot`
Earth2Studio	Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.	`earth2studio-create-datasource`, `earth2studio-create-diagnostic`, `earth2studio-create-prognostic`, `earth2studio-data-fetch`, `earth2studio-deterministic-forecast`, `earth2studio-discover`, `earth2studio-install`
HoloHub	Build, run, debug, benchmark, and develop HoloHub applications and Holoscan Modules with validated lifecycle workflows.	`holohub-app-lifecycle`, `holohub-debug-build-run`, `holohub-module-lifecycle`
Holoscan SDK	Install and set up the Holoscan SDK on any platform (container, Debian, Python, Conda, or source).	`holoscan-install-debian`, `holoscan-install-source`, `holoscan-install-wheel`, `holoscan-install-conda`, `holoscan-install-container`, `holoscan-setup`
Holoscan Sensor Bridge	Agent-ready skills for Holoscan Sensor Bridge devkit workflows, including demo environment bring-up, FPGA flashing for Lattice and VB1940 hardware, example application execution, QA test-plan automation, and support for configuring and using the Holoscan Sensor Bridge FPGA intellectual property (IP) core.	`hsb-setup`, `hsb-flash`, `hsb-app`, `hsb-test`, `hsb-ip-def`, `hsb-ip-packetizer`, `hsb-ip-create-top`
Isaac for Healthcare Workflows	Agent-ready skills for Isaac for Healthcare agentic and catheter-navigation workflows, covering task authoring, data pipelines, policy training and validation, CT-derived digital twins, DRR rendering, and interactive catheter simulation.	`i4h-workflow`, `i4h-workflow-setup`, `i4h-workflow-create`, `i4h-workflow-scene-edit`, `i4h-workflow-dataset-teleop`, `i4h-workflow-dataset-replay`, `i4h-workflow-dataset-mimic`, `i4h-workflow-dataset-annotate`, `i4h-workflow-dataset-convert`, `i4h-workflow-finetune`, `i4h-workflow-validate`, `i4h-workflow-e2e`, `i4h-lerobot-viz`, `i4h-catheter-navigation`, `i4h-catheter-navigation-setup`, `i4h-catheter-navigation-digital-twin`, `i4h-catheter-navigation-render-drr`, `i4h-catheter-navigation-viewport`, `i4h-catheter-navigation-smoke`, `i4h-catheter-navigation-e2e`
Jetson BSP	Agentic skills for setting up and customizing an NVIDIA Jetson Linux Board Support Package (BSP) — pick a target, prepare image and sources, customize IO (camera, PCIe, USB, pinmux, clocks, and more), then promote, flash, and validate.	`jetson-build-source`, `jetson-customize-camera`, `jetson-customize-clocks`, `jetson-customize-fan`, `jetson-customize-mgbe`, `jetson-customize-nvpmodel`, `jetson-customize-pcie`, `jetson-customize-pinmux`, `jetson-customize-uphy`, `jetson-customize-usb`, `jetson-derive-carrier`, `jetson-download-bsp`, `jetson-flash-image`, `jetson-generate-kb`, `jetson-init-image`, `jetson-init-source`, `jetson-init-target`, `jetson-link-docs`, `jetson-optimize-memory`, `jetson-print-bsp-info`, `jetson-promote-image`, `jetson-quick-start`, `jetson-set-target`, `jetson-validate-image`
Jetson Device	Device-side agent skills for working with a live NVIDIA Jetson after boot — diagnostics, memory auditing, headless setup, inference memory tuning, LLM serving and benchmarking, packaging guidance, and speculative decoding.	`jetson-diagnostic`, `jetson-headless-mode`, `jetson-inference-mem-tune`, `jetson-llm-benchmark`, `jetson-llm-serve`, `jetson-memory-audit`, `jetson-package`, `jetson-print-device-info`, `jetson-speculative-decoding`
Medical AI Skills	Agent-ready medical AI skills built on MONAI for DICOM handling, NVIDIA-hosted medical imaging model workflows, segmentation, synthesis, and evidence-oriented evaluation.	`dicom-metadata-extract`, `dicom-series-preflight`, `dicom-series-to-volume`, `nv-generate-ct-rflow`, `nv-generate-mr`, `nv-generate-mr-brain`, `nv-generate-mr-brain-finetune`, `nv-generate-vae-finetune`, `nv-reason-cxr`, `nv-segment-ct`, `nv-segment-ct-finetune`, `nv-segment-ctmr`
Megatron-Core	Large-scale distributed training — model parallelism, pipeline parallelism, and mixed precision.	`mcore-create-issue`, `mcore-linting-and-formatting`, `mcore-run-on-slurm`, `mcore-split-pr`, `mcore-testing`
NeMo AutoModel	NeMo AutoModel - PyTorch-native distributed training for LLMs/VLMs with Hugging Face support, recipes, launchers, and validation workflows.	`nemo-automodel-distributed-training`, `nemo-automodel-launcher-config`, `nemo-automodel-model-onboarding`, `nemo-automodel-recipe-development`
NeMo MBridge	NeMo MBridge - PyTorch-native bridge between Hugging Face and Megatron-Core for checkpoint conversion, training recipes, and NVIDIA GPU performance workflows.	`nemo-mbridge-mlm-bridge-training`, `nemo-mbridge-multi-node-slurm`, `nemo-mbridge-perf-activation-recompute`, `nemo-mbridge-perf-cpu-offloading`, `nemo-mbridge-perf-cuda-graphs`, `nemo-mbridge-perf-expert-parallel-overlap`, `nemo-mbridge-perf-hierarchical-context-parallel`, `nemo-mbridge-perf-megatron-fsdp`, `nemo-mbridge-perf-memory-tuning`, `nemo-mbridge-perf-moe-comm-overlap`, `nemo-mbridge-perf-moe-dispatcher-selection`, `nemo-mbridge-perf-moe-hardware-configs`, `nemo-mbridge-perf-moe-long-context`, `nemo-mbridge-perf-moe-optimization-workflow`, `nemo-mbridge-perf-moe-vlm-training`, `nemo-mbridge-perf-parallelism-strategies`, `nemo-mbridge-perf-sequence-packing`, `nemo-mbridge-perf-tp-dp-comm-overlap`, `nemo-mbridge-recipe-recommender`, `nemo-mbridge-resiliency`
NeMo Platform	NeMo Platform brings NVIDIA NeMo libraries together under one CLI, Python SDK, and web UI	`nemo-evaluator-plugin`, `nemo-data-designer-plugin`
NeMo Relay	Skills to help get started and use NeMo Relay - a runtime for instrumenting and controlling AI agents across harnesses, applications, and frameworks.	`nemo-relay-install`, `nemo-relay-get-started`, `nemo-relay-instrument-calls`, `nemo-relay-instrument-context-isolation`, `nemo-relay-instrument-typed-wrappers`, `nemo-relay-plugin-adaptive-tuning`, `nemo-relay-plugin-build`, `nemo-relay-plugin-observability`, `nemo-relay-migrate-from-flow`, `nemo-relay-debug-runtime-integration`
NeMo Retriever	NeMo Retriever - deploy NeMo Retriever Library locally, extract information from corpus of data, and answer questions against the corpus.	`nemo-retriever`
NeMo-RL	RLHF training on Ray — GRPO, DPO, and SFT for LLMs and VLMs with FSDP2 and Megatron-Core.	`launch-nemo-rl`, `nemo-rl-auto-research`, `nemo-rl-brev-etiquette`, `nemo-rl-docs`, `nemo-rl-session-memory`
NemoClaw	Secure agent sandboxing — run OpenClaw inside NVIDIA OpenShell with managed inference, policy management, remote deployment, sandbox monitoring.	`nemoclaw-user-guide`
Nemotron	Author end-to-end model development, customization, evaluation, and deployment pipelines using the NVIDIA AI stack.	`nemotron-customize`, `nemotron-retrieval-recipes`, `nemotron-policy-generator`
Nemotron Speech	Deploy and operate NVIDIA Nemotron Speech (Riva) NIMs — ASR, TTS, and NMT, cloud-hosted via build.nvidia.com or self-hosted on your own GPU.	`nemotron-speech`, `nemotron-asr-finetune`
Physical AI	Physical AI skills for simulation, synthetic data generation, training, validation and deployment and more.	`omniverse-cad-to-simready`, `omniverse-realtime-viewer`, `omniverse-usd-performance-tuning`, `physical-ai-infrastructure-setup-and-resilient-scaling`, `physical-ai-neural-reconstruction`, `physical-ai-defect-image-generation`, `physical-ai-video-data-augmentation`, `physical-ai-people-attribute-search`
PhysicsNeMo	NVIDIA PhysicsNeMo - Open-source deep-learning framework for building, training, and fine-tuning deep learning models using state-of-the-art Physics-ML methods.	`physicsnemo-discover`, `physicsnemo-shard-tensor`
Portfolio Optimization	GPU-accelerated Mean-CVaR portfolio optimization with NVIDIA cuOpt — CVaR optimization, efficient frontier, scenario generation, backtesting, and rebalancing.	`portfolio-optimization`
RAG Blueprint	RAG pipeline — deploy, configure, troubleshoot, and manage retrieval augmented generation with Docker Compose or Helm.	`rag-blueprint`, `rag-eval`, `rag-perf`
Skill Card Generator	Reads an agent skill's source files and produces a skill card plus a review table. Use when a skill directory exists and a governance card needs to be generated or updated.	`skill-card-generator`
TAO Toolkit	NVIDIA TAO Toolkit - fine-tune and optimize 100+ pretrained vision AI models with your own data using low-code microservices, then export production-ready models for edge or cloud deployment.	`tao-analyze-changenet-rca`, `tao-finetune-huggingface-model`, `tao-port-huggingface-model`, `tao-run-automl`, `tao-run-automl-deft-pipeline`, `tao-run-deft-aoi`, `tao-run-inference-service`, `tao-train-single-step`, `paidf-anomalygen`, `tao-analyze-gaps-visual-changenet`, `tao-analyze-gaps-vlm-bcq`, `tao-convert-dataset-format`, `tao-generate-image-grounding`, `tao-generate-referring-expressions`, `tao-generate-video-reasoning-annotations`, `tao-mine-aoi-images`, `tao-route-visual-changenet-samples`, `tao-validate-dataset-format`, `tao-finetune-clip`, `tao-finetune-cosmos-embed`, `tao-finetune-cosmos-reason`, `tao-train-action-recognition`, `tao-train-bevfusion`, `tao-train-centerpose`, `tao-train-deformable-detr`, `tao-train-depth-anything-v2`, `tao-train-dino`, `tao-train-fast-foundation-stereo`, `tao-train-foundation-stereo`, `tao-train-grounding-dino`, `tao-train-image-classification`, `tao-train-mask-auto-encoder`, `tao-train-mask-auto-label`, `tao-train-mask-grounding-dino`, `tao-train-mask2former`, `tao-train-metric-learning-recognition`, `tao-train-nvdinov2`, `tao-train-nvpanoptix3d`, `tao-train-ocdnet`, `tao-train-ocrnet`, `tao-train-oneformer`, `tao-train-optical-inspection`, `tao-train-pointpillars`, `tao-train-pose-classification`, `tao-train-reid`, `tao-train-rtdetr`, `tao-train-segformer`, `tao-train-sparse4d`, `tao-train-visual-changenet`, `tao-run-on-brev`, `tao-run-on-docker`, `tao-run-on-kubernetes`, `tao-run-on-local-docker`, `tao-run-on-slurm`, `tao-run-platform`, `tao-setup-nvidia-gpu-host`, `tao-launch-workflow`, `tao-list-capabilities`
TileGym	Tile-based GPU programming — adding new kernels, cross-framework conversion, and performance optimization.	`tilegym-adding-cutile-kernel`, `tilegym-converting-cutile-to-julia`, `tilegym-converting-cutile-to-triton`, `tilegym-cutile-autotuning`, `tilegym-cutile-python`, `tilegym-improve-cutile-kernel-perf`, `tilegym-monkey-patch-kernels-to-transformers`
Video Search and Summarization	VSS Blueprint — deploy profiles, search and summarize video, generate analysis reports, manage alerts and incidents, query VIOS sensors, and use the RTVI VLM microservice.	`vss-ask-video`, `vss-deploy-dense-captioning`, `vss-deploy-detection-tracking-2d`, `vss-deploy-detection-tracking-3d`, `vss-deploy-profile`, `vss-deploy-video-embedding`, `vss-generate-video-calibration`, `vss-generate-video-report`, `vss-manage-alerts`, `vss-manage-video-io-storage`, `vss-query-analytics`, `vss-search-archive`, `vss-setup-behavior-analytics`, `vss-setup-video-analytics-api`, `vss-summarize-video`

Getting Help & Contributing

Where to file an issue depends on what's broken:

Skill content issues (a specific skill has a bug, missing functionality, or incorrect content) — file in the source repo for that product, using the per-product table below.
Catalog issues (catalog README errors, sync workflow problems, distribution channels, signing/verification flow, docs in this repo) — file here using the catalog issue templates: Bug Report, Feature Request, or Documentation Request or Correction.
Questions or general discussion — use Discussions. The issue tracker is reserved for bug reports, feature proposals with a design, and documentation issues.
Security vulnerabilities — follow the disclosure process in SECURITY.md; do not open a public issue.

Per-product source repo links:

Product	Issues	Discussions	Contributing	Security
AIQ	Issues	Discussions	Contributing	Security
CUDA-Q	Issues	Discussions	Contributing	Security
cuDF	Issues	Discussions	Contributing	Security
cuOpt	Issues	Discussions	Contributing	Security
cuPyNumeric	Issues	—	Contributing	—
DALI	Issues	—	Contributing	—
Data Designer	Issues	Discussions	Contributing	Security
DeepStream	Issues	—	Contributing	Security
Digital Health	Issues	—	Contributing	Security
DOCA	Issues	—	Contributing	Security
Dynamo	Issues	Discussions	Contributing	Security
Earth2Studio	Issues	Discussions	Contributing	—
HoloHub	Issues	—	Contributing	Security
Holoscan SDK	Issues	—	Contributing	Security
Holoscan Sensor Bridge	Issues	—	Contributing	—
Isaac for Healthcare Workflows	Issues	—	Contributing	Security
Jetson BSP	Issues	—	Contributing	Security
Jetson Device	Issues	—	Contributing	Security
Medical AI Skills	Issues	—	Contributing	Security
Megatron-Core	Issues	Discussions	Contributing	—
NeMo AutoModel	Issues	Discussions	Contributing	Security
NeMo MBridge	Issues	Discussions	Contributing	Security
NeMo Platform	Issues	Discussions	Contributing	Security
NeMo Relay	Issues	Discussions	Contributing	Security
NeMo Retriever	Issues	Discussions	Contributing	Security
NeMo-RL	Issues	Discussions	Contributing	Security
NemoClaw	Issues	Discussions	Contributing	Security
Nemotron	Issues	Discussions	Contributing	Security
Nemotron Speech	Issues	—	Contributing	Security
Physical AI	Issues	—	Contributing	Security
PhysicsNeMo	Issues	Discussions	Contributing	Security
Portfolio Optimization	Issues	Discussions	Contributing	Security
RAG Blueprint	Issues	Discussions	Contributing	Security
Skill Card Generator	Issues	—	Contributing	Security
TAO Toolkit	Issues	Discussions	Contributing	Security
TileGym	Issues	—	Contributing	Security
Video Search and Summarization	Issues	Discussions	Contributing	Security

For issues with this catalog repo itself (README, structure, listing a new product): open an issue here.

Verifying Skills

Every published skill ships with a detached OMS signature (skill.oms.sig). The sync pipeline drops any skill missing the required artifacts before publishing, so every skill in the catalog carries:

SKILL.md — the skill instructions consumed by the agent
skill-card.md — skill identity and governance card
skill.oms.sig — detached OMS signature (verifiable against nv-agent-root-cert.pem)
A Tier-3 evaluation dataset — accepted at evals/evals.json, evals/*.json, eval/*.json, or benchmark/evals.json
BENCHMARK.md — generated benchmark report capturing verifiable uplift data

Verify a skill against the NVIDIA trust anchor nv-agent-root-cert.pem:

pip install model-signing
model_signing verify certificate SKILL_DIR \
  --signature SKILL_DIR/skill.oms.sig \
  --certificate_chain nv-agent-root-cert.pem \
  --ignore_unsigned_files

A successful verification confirms that the skill contents have not been modified since signing by NVIDIA.

See Verify Signed Agent Skills for signature layout, the trust pipeline, and policy options.

Roadmap

✅ Public skills catalog with NVIDIA-verified skills across multiple products
✅ Automated sync pipeline with skills mirrored from product repos daily
✅ Security scanning for all published skills covering instruction safety and supply-chain integrity
✅ Skills signing so every published skill carries a verifiable NVIDIA signature
✅ Skills universal evaluation criteria and task-specific criteria
✅ Skill Card with machine-readable metadata for identity, provenance, quality, and behavioral boundaries
✅ Sync-time compliance gates — signature drift detection and missing-artifact enforcement
✅ Syndication to external marketplaces — Skills.sh, Codex plugin, Claude Code plugin, ClawHub, Hermes Hub
🔲 Syndication to additional MCP hubs and partner channels

Repository Structure

NVIDIA/skills/
├── skills/                      # NVIDIA-verified skills (count grows continuously),
│   │                              synced from upstream product repos
│   ├── README.md                 # Browser-facing install guidance
│   ├── <product-prefix>-*/       # Flat layout — one dir per skill, product-prefixed
│   │                               # e.g. aiq-*, cuopt-*, cupynumeric-*,
│   │                               # dali-*, deepstream-*, dicom-*, digital-health-*,
│   │                               # dynamo-*, earth2studio-*, holoscan-*, hsb-*,
│   │                               # jetson-*, launch-nemo-rl, mcore-*,
│   │                               # nemo-automodel-*, nemo-data-designer-plugin,
│   │                               # nemo-evaluator-plugin, nemo-mbridge-* (20 skills),
│   │                               # nemo-retriever, nemo-rl-* (4 skills),
│   │                               # nemoclaw-user-guide, nemotron-*, nemotron-speech,
│   │                               # nv-* (medical AI), physicsnemo-*, rag-*,
│   │                               # skill-card-generator, tao-*, tilegym-*,
│   │                               # vss-* (15 skills), accelerated-computing-cudf,
│   │                               # cudaq-guide, portfolio-optimization
│   ├── omniverse-*/              # Physical AI — manually staged (see manual-components.yml)
│   └── physical-ai-*/            # Physical AI — manually staged
├── components.d/                # Product registry — one file per component, teams onboard here
│   ├── README.md                 # Schema and onboarding instructions
│   └── <product>.yml             # one file per registered product
├── plugins/                     # Packaged plugin distributions
│   └── nvidia-skills/            # Curated NVIDIA skills bundle (Claude Code, Codex)
├── plugins.d/                   # Plugin build registry — config for `build-plugins.py`
│   ├── README.md
│   ├── _defaults.yml
│   └── nvidia-skills.yml
├── .claude-plugin/              # Claude Code marketplace metadata
│   └── marketplace.json
├── .agents/plugins/             # Agent marketplace metadata (other clients)
│   └── marketplace.json
├── docs/                        # Long-form documentation (published via Fern)
│   ├── README.md                 # How to build the docs locally
│   ├── index.mdx
│   ├── advanced-install.mdx
│   ├── agent-skill-trust-pipeline.mdx
│   ├── release-checklist.mdx
│   ├── scanning-agent-skills.mdx
│   ├── signing-agent-skills.mdx
│   └── skill-cards.mdx
├── fern/                        # Fern docs site configuration
├── .github/
│   ├── workflows/                # Sync pipeline, plugin validation, DCO check, author verify
│   └── scripts/                  # regenerate-readme.sh, build-plugins.py,
│                                 # manual-components.yml (temp Physical AI catalog
│                                 # exception, removed after Computex 2026),
│                                 # marketplace/metadata.json (skill metadata sidecar)
├── nv-agent-root-cert.pem       # Trust anchor for OMS signature verification
├── skills.sh.json               # Skills.sh marketplace grouping config
├── CHANGELOG.md
├── CONTRIBUTING.md              # Contribution guidelines
├── SECURITY.md                  # Security reporting policy
├── CODE_OF_CONDUCT.md           # Community code of conduct
├── LICENSE-APACHE               # Apache 2.0 (source code)
└── LICENSE-CC-BY-4.0            # CC BY 4.0 (documentation/skills)

Skills are maintained in their respective product repos (see the Source column in the Skill Catalog) and synced to this repo daily. Products only appear under skills/ after the sync pipeline confirms each skill carries:

skill.oms.sig — detached OMS-format signature (verifiable against nv-agent-root-cert.pem)
skill-card.md — skill identity and governance card
A Tier-3 evaluation dataset — accepted at evals/evals.json, evals/*.json, eval/*.json, or benchmark/evals.json

When evaluation runs produce a BENCHMARK.md, it ships alongside the skill so consumers can see verifiable benchmark uplift data.

Standards & Compatibility

This repository adheres to the Agent Skills specification:

Skills are portable directories with a SKILL.md file at their root.
Metadata uses YAML frontmatter with required name and description fields.
Skills follow a progressive disclosure model — lightweight metadata loads at startup, full instructions load on activation.
Validate your skill using the skills-ref reference library.

License

This code is dual-licensed with documentation/skills under the CC-BY-4.0 AND source code under Apache-2.0 license terms. The full license texts can be found in LICENSE-APACHE and LICENSE-CC-BY-4.0 respectively.

File tree

1491

NVIDIA/skillsView on GitHub

.agents/
  plugins/
    marketplace.json
.claude-plugin/
  marketplace.json
.cursor-plugin/
  marketplace.json
.github/
  CODEOWNERS
  external-contributors.yml
  ISSUE_TEMPLATE/
    bug_report.yml
    config.yml
    documentation.yml
    feature_request.yml
  PULL_REQUEST_TEMPLATE.md
  scripts/
    aggregate_benchmarks.py
    build-plugins.py
    build-plugins.sh
    manual-components.yml
    marketplace/
      generate-skill-metadata.py
      metadata-exclusions.yaml
      metadata.json
      metadata.schema.json
      README.md
      skills-sh.schema.json
      skills-subdomains.json
      test_generate_skill_metadata.py
    prune-orphans.sh
    regenerate-readme.sh
    verify_content_integrity.py
    version-plugins.py
    version-plugins.sh
  workflows/
    clawhub-publish.yml
    dco.yml
    generate-skill-metadata.yml
    publish-docs.yml
    request-nvskills-ci.yml
    require-nvskills-status.yml
    sync-skills.yml
    team-request.yml
    validate-plugins.yml
    verify-authors.yml
    verify-content-integrity.yml
.gitignore
benchmarks.json
catalog-exceptions.yml
CHANGELOG.md
CODE_OF_CONDUCT.md
components.d/
  aiq.yml
  cuda-q.yml
  cudf.yml
  cuopt.yml
  cupynumeric.yml
  dali.yml
  data-designer.yml
  deepstream.yml
  digital-health.yml
  doca.yml
  dynamo.yml
  earth2studio.yml
  holohub.yml
  holoscan-sdk.yml
  holoscan-sensor-bridge.yml
  isaac-for-healthcare-workflows.yml
  jetson-bsp.yml
  jetson-device.yml
  medical-ai-skills.yml
  megatron-core.yml
  nemo-automodel.yml
  nemo-mbridge.yml
  nemo-platform.yml
  nemo-relay.yml
  nemo-retriever.yml
  nemo-rl.yml
  nemoclaw.yml
  nemotron-speech.yml
  nemotron.yml
  physical-ai-data-factory.yml
  physicsnemo.yml
  portfolio-optimization.yml
  rag-blueprint.yml
  README.md
  skill-card-generator.yml
  tao-toolkit.yml
  tilegym.yml
  video-search-and-summarization.yml
CONTRIBUTING.md
docs/
  advanced-install.mdx
  agent-skill-trust-pipeline.mdx
  evaluating-agent-skills.mdx
  index.mdx
  README.md
  release-checklist.mdx
  scanning-agent-skills.mdx
  signing-agent-skills.mdx
  skill-cards.mdx
fern/
  docs.yml
  fern.config.json
LICENSE-APACHE
LICENSE-CC-BY-4.0
nv-agent-root-cert.pem
plugins/
plugins.d/
  _defaults.yml
  nvidia-skills.yml
  README.md
  nvidia-skills/
    .claude-plugin/
      plugin.json
    .codex-plugin/
      plugin.json
    .cursor-plugin/
      plugin.json
    assets/
      nvidia.png
    README.md
    skills/
      nvidia-skill-finder/
        agents/
          openai.yaml
        BENCHMARK.md
        evals/
          evals.json
        references/
          taxonomy-routing.md
        skill-card.md
        SKILL.md
        skill.oms.sig
  README.md
README.md
SECURITY.md
skills/
skills.sh.json
  accelerated-computing-cudf/
    BENCHMARK.md
    evals/
      evals.json
      files/
        cudf-apply-udf/
          code/
            generate_data.py
            udf_pipeline.py
        cudf-csv-etl/
          code/
            etl_pipeline.py
            generate_data.py
        cudf-groupby-agg/
          code/
            generate_data.py
            groupby_analysis.py
        cudf-multi-join/
          code/
            generate_data.py
            multi_join.py
        cudf-native-stream-handoff-boundary/
          code/
            run_smoke.sh
            threaded_handoff.cu
          NOTICE.md
        cudf-null-handling/
          code/
            generate_data.py
            null_pipeline.py
        cudf-parquet-io/
          code/
            generate_data.py
            parquet_pipeline.py
        cudf-pivot-melt/
          code/
            generate_data.py
            reshape_analysis.py
        cudf-string-ops/
          code/
            clean_contacts.py
            generate_data.py
        cudf-timeseries-resample/
          code/
            generate_data.py
            timeseries_analysis.py
        cudf-window-functions/
          code/
            generate_data.py
            window_analysis.py
        negative-deep-learning-training/
          code/
            train.py
        source-cudf-null-fillna-semantics/
          code/
            null_cleanup.py
          NOTICE.md
    references/
      api-patterns.md
      cudf-pandas-accelerator.md
      dask-cudf-patterns.md
    skill-card.md
    SKILL.md
    skill.oms.sig
  aiq-deploy/
    BENCHMARK.md
    evals/
      evals.json
    references/
      configs.md
      docker-compose.md
      end-to-end-validation.md
      env-and-secrets.md
      frag.md
      kubernetes-helm.md
      local-web.md
      locate-or-clone.md
      shutdown.md
      skill-backend.md
      terminal-cli.md
      troubleshooting.md
      validation.md
    skill-card.md
    SKILL.md
    skill.oms.sig
  aiq-research/
    BENCHMARK.md
    evals/
      basic-product.json
      evals.json
    scripts/
      aiq.py
    skill-card.md
    SKILL.md
    skill.oms.sig
  amc-run-sample-calibration/
    BENCHMARK.md
    evals/
      evals.json
    scripts/
      run_sample_calibration.py
    skill-card.md
    SKILL.md
    skill.oms.sig
  amc-run-video-calibration/
    BENCHMARK.md
    evals/
      evals.json
    scripts/
      run_video_calibration.py
    skill-card.md
    SKILL.md
    skill.oms.sig
  amc-setup-calibration-stack/
    BENCHMARK.md
    evals/
      evals.json
    skill-card.md
    SKILL.md
    skill.oms.sig
  cudaq-guide/
    BENCHMARK.md
    evals/
      config.yml
      EVAL.md
      evals.json
    skill-card.md
    SKILL.md
    skill.oms.sig
  cuopt-developer/
    benchmark/
    BENCHMARK.md
      evals.json
    evals/
      evals.json
    references/
      build_and_test.md
      contributing.md
      conventions.md
      first_time_setup.md
      python_bindings.md
      troubleshooting.md
      vrp_skills.md
    resources/
      numerical_debugging.md
    skill-card.md
    SKILL.md
    skill.oms.sig
  cuopt-install/
    benchmark/
    BENCHMARK.md
      evals.json
    evals/
      evals.json
    references/
      verification_examples.md
    skill-card.md
    SKILL.md
    skill.oms.sig
  cuopt-multi-objective-exploration/
    BENCHMARK.md
    evals/
      evals.json
    skill-card.md
    SKILL.md
    skill.oms.sig
  cuopt-numerical-optimization-api/
    assets/
      c/
        lp_basic/
          lp_simple.c
          README.md
        lp_duals/
          lp_duals.c
          README.md
        lp_warmstart/
          README.md
        milp_basic/
          milp_simple.c
          README.md
        milp_production_planning/
          milp_production.c
          README.md
        mps_solver/
          data/
            sample.mps
          mps_solver.c
          README.md
        README.md
      cli/
        lp_production/
          production.mps
          README.md
        lp_simple/
          README.md
          sample.mps
        milp_facility/
          facility.mps
          README.md
        README.md
      python/
        least_squares/
          model.py
          README.md
        lp_basic/
          model.py
          README.md
        lp_duals/
          model.py
          README.md
        lp_warmstart/
          model.py
          README.md
        maximization_workaround/
          model.py
          README.md
        milp_basic/
          incumbent_callback.py
          model.py
          README.md
        milp_production_planning/
          model.py
          README.md
        mps_solver/
          data/
            README.md
            sample.mps
          model.py
          README.md
          results.md
        portfolio/
          model.py
          README.md
        README.md
    BENCHMARK.md
    evals/
      evals.json
    references/
      c_api.md
      cli_api.md
      python_api.md
      qp_examples.md
    skill-card.md
    SKILL.md
    skill.oms.sig
  cuopt-numerical-optimization-formulation/
    BENCHMARK.md
    evals/
      evals.json
    skill-card.md
    SKILL.md
    skill.oms.sig
  cuopt-routing-api-python/
    assets/
      pdp_basic/
        model.py
        README.md
      README.md
      vrp_basic/
        model.py
... 1600 more

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FAQ

nvidia-skills is a Claude Code plugin with 200 hand-picked skills for development work, indexed on Flowy. Install it with the command on its page. It includes nvidia-skill-finder, accelerated-computing-cudf, aiq-deploy. Its skills do not fire on their own yet. Request auto-invocation to have Flowy route them as you prompt. Free and open source.

What is nvidia-skills?: Official, NVIDIA-verified Agent Skills for Claude Code, Codex, and other coding agents.
How do I install nvidia-skills?: Run these in Claude Code: /plugin marketplace add NVIDIA/skills then /plugin install nvidia-skills@nvidia-official. Then prompt normally.
Does nvidia-skills auto-invoke its skills?: Not yet. It is indexed on Flowy as a plain plugin. Request auto-invocation on its page and Flowy will route its skills for you as you prompt.
Is nvidia-skills free?: Yes. Flowy is free and open source, with nothing gated. You can read every skill in full before you install.