| Auto Ontology |
Set up Auto Ontology, model and publish its semantic layer, and run validated text-to-SQL queries through it. |
nvidia-ontology-setup, nvidia-ontology-management, nvidia-ontology-query |
| BioNeMo Libraries |
Accelerate cheminformatics, genomic analysis, and equivariant model development with NVIDIA GPU libraries and tools. |
bionemo-cuequivariance, bionemo-cuequivariance-jax, bionemo-cuequivariance-torch, bionemo-nvmolkit-usage, bionemo-parabricks, bionemo-genomics-workflow-acceleration |
| BioNeMo NIMs |
Run and combine BioNeMo NIM microservices for biomolecular research and drug discovery through hosted APIs or local deployments. |
bionemo-drug-discovery-pipeline, bionemo-msa-structure-prediction-pipeline, bionemo-openfold2-nim, bionemo-molmim-nim, bionemo-diffdock-nim, bionemo-genmol-nim, bionemo-evo2-nim, bionemo-rfdiffusion-nim, bionemo-rfd4-proteina-nim, bionemo-openfold3-nim, bionemo-proteinmpnn-nim, bionemo-msa-search-nim, bionemo-boltz2-nim |
| BioNeMo Open Models |
Apply BioNeMo open models to molecular property prediction and generative protein design. |
bionemo-codonfm-setup, bionemo-codonfm-embed, bionemo-codonfm-score, bionemo-codonfm-finetune, bionemo-complexa-evaluate-pdbs, bionemo-complexa-sweep, bionemo-complexa-target, bionemo-kermt-add-cmim-pretrain, bionemo-kermt-continue-pretrain, bionemo-kermt-embed, bionemo-kermt-finetune, bionemo-kermt-infer, bionemo-kermt-monitor, bionemo-kermt-pretrain-scratch, bionemo-kermt-setup |
| CDF AnomalyGen |
Run Cosmos Data Factory AnomalyGen workflows for fine-tuning, synthetic defect generation, evaluation, refinement, and pseudo-labeling. |
cdf-anomalygen |
| CDF Augmentation |
Author, validate, and run Cosmos Data Factory augmentation pipelines for image and video generation and transformation. |
cdf-augmentation |
| CDF Auto-Labeling |
Build and run Cosmos Data Factory auto-labeling pipelines for video enhancement, tracking, captioning, and question generation. |
cdf-auto-labeling |
| CDF Curation and Retrieval |
Author, validate, and run Cosmos Data Factory curation and retrieval pipelines. |
cdf-curation-and-retrieval |
| CDF Simulation |
Build and validate Cosmos Data Factory Simulation jobs and compiled payloads for PCB-AOI workflows. |
cdf-simulation |
| Cosmos Data Factory Orchestration |
Build, run and monitor Cosmos Data Factory pipelines for image and video generation and transformation. |
cdf-orchestration-preflight, cdf-orchestration-setup, cdf-orchestration-write-dag, cdf-autonomous-vehicle-dataset-generation, cdf-defect-image-generation, cdf-event-video-generation, cdf-image-attribute-augmentation, cdf-video-data-augmentation |
| CUDA-Q |
Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance. |
cudaq-guide, cudaq-importing |
| 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, cudf-query-engine-builder |
| cuML |
Official NVIDIA-authored guidance for cuML GPU machine learning, scikit-learn acceleration with cuml.accel, API compatibility, multi-GPU process execution, and model export. |
cuml |
| 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 |
| DALI |
GPU-accelerated data loading and processing with NVIDIA DALI. |
dali-dynamic-mode |
| DeepStream |
Agentic skills for guided DeepStream development. |
amc-run-rtsp-calibration, 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-run-mv3dt, deepstream-sop, rtvi-cv-customize-model, rtvi-cv-scaffold-vss-service, rtvi-vlm-customize-model |
| DGX Spark Skills |
Agent guidance for DGX Spark and related GB10 system identification, troubleshooting, updates, playbooks, NVIDIA Sync, diagnostics, and support. |
dgx-spark-skills |
| Digital Health |
Agent skills for (1) the clinical ASR evaluation flywheel — term curation, synthetic clinical-speech benchmark generation, KER (Keyword Error Rate) scoring, and fine-tune guidance; (2) the ambient healthcare agent creation with Nemotron Voice Agent. |
digital-health-clinical-asr-setup, digital-health-clinical-asr-build, digital-health-clinical-asr-eval, digital-health-clinical-asr-finetune, ambient-healthcare-agent-with-nemotron-voice-agent |
| 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-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-gpunetio, doca-mgmt, doca-pcc, doca-rdma, doca-rmax, doca-sha, doca-sta, doca-telemetry, doca-telemetry-exporter, doca-urom, doca-verbs, doca-argus, doca-dms, doca-dts, doca-firefly, doca-urom-svc, doca-bench, doca-caps, doca-comm-channel-admin, doca-flow-tune, doca-ngauge, doca-pcc-counters, doca-perftest, doca-pipeline-language-developer-tools, doca-sha-offload-engine, doca-socket-relay, doca-spcx-cc, doca-telemetry-traceback-application, 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 |
| ETHOS.md |
Capture an AI agent’s purpose, boundaries, and success criteria in a portable ethos.md that developers, reviewers, and evaluators share. |
ethos-orchestrate, ethos-explore, ethos-write |
| FoundationPose Perception Pipeline |
Set up the FoundationPose perception stack, adapt BOP datasets, and run or evaluate pose inference with TAO Deploy depth. |
foundationpose-setup, foundationpose-pipeline |
| G-Assist |
Check or change a machine’s NVIDIA display and GPU settings such as resolution, refresh rate, V-Sync, G-SYNC, brightness, color, and GPU performance, via the G-Assist MCP server. |
g-assist-mcp-skill |
| HoloHub |
Build, run, debug, benchmark, and develop Holoscan applications and Holoscan Modules with validated lifecycle workflows. |
holoscan-app-debug-build-run, holoscan-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-train-rl, i4h-workflow-validate, i4h-workflow-e2e, i4h-lerobot-viz |
| 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, jetson-video-benchmark, jetson-video-capability, jetson-video-pipeline, jetson-video-recipe, jetson-video-setup |
| 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, medtech-model-evidence-export, nv-generate-ct-rflow, nv-generate-mr, nv-generate-mr-brain, nv-generate-mr-brain-finetune, nv-generate-vae-finetune, nv-reason-ct, 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 Data Designer |
Build declarative synthetic dataset generation pipelines with NeMo Data Designer. |
data-designer |
| NeMo Fabric |
Portable skills for integrating applications with NeMo Fabric through its public SDK and building compatible third-party adapters. |
nemo-fabric-integrate, nemo-fabric-build-adapter |
| 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 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-retriever-mcp |
| 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 |
| Nemotron Voice Agent |
Create or refine NVIDIA voice agents (Cascaded or Omni) with Pipecat or LiveKit — speech customization, model selection, cloud or local deployment, and iteration. |
nemotron-voice-agent-builder |
| Nsight |
Agent-facing assets for Nsight developer workflows, including skills that help agents work with NVIDIA developer tools. |
compute-sanitizer-diagnose-cuda-bugs |
| NVIDIA App |
NVIDIA App MCP: drivers, games, laptops, overlay. Check drivers, manage and optimize games, configure laptop features. |
nvidia-app |
| NVIDIA Broadcast |
Control NVIDIA Broadcast through its MCP gateway: apply audio and video effects, process local media, select devices, and change camera resolution. |
nvidia-broadcast |
| NVIDIA FLARE |
Agent skills for converting training code to federated workflows, diagnosing jobs, collecting federated statistics, and running Auto-FL with NVIDIA FLARE. Install the complete NVIDIA FLARE skill set together so each workflow has its required shared references. |
nvflare-autofl, nvflare-autofl-report, nvflare-convert-huggingface, nvflare-convert-lightning, nvflare-convert-pytorch, nvflare-diagnose-job, nvflare-fed-stats, nvflare-orient, nvflare-shared |
| NVSHMEM |
Install, build, run, tune, and debug the NVSHMEM library and applications. |
nvshmem-install, nvshmem-get-started, nvshmem-docs, nvshmem-troubleshoot-and-report-bugs, nvshmem-tune-performance, nvshmem-enable-tma, nvshmem-configure-nic-pe-mapping, nvshmem-select-remote-transport, nvshmem-collect-performance-data |
| ovnewton |
Connect Newton physics to ovstage and Omniverse simulations. |
ovnewton-usage |
| Physical AI |
Physical AI skills for simulation, synthetic data generation, training, validation and deployment and more. |
isaac-humanoid-cloud-control, isaac-cable-insertion-policy-deployment, isaac-cable-insertion-policy-training, isaac-mission-control-showcase, omniverse-cad-to-simready, omniverse-content-services, 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-physics-selection |
| 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 |
| PVA SDK |
NVIDIA Programmable Vision Accelerator (PVA) SDK skills for environment setup, host readiness checks, operator specification, generation, build and test, and debugging. |
pva-build-test, pva-debug, pva-doctor, pva-opgen, pva-setup, pva-spec |
| RAG Blueprint |
RAG pipeline — deploy, configure, troubleshoot, and manage retrieval augmented generation with Docker Compose or Helm. |
rag-blueprint, rag-eval, rag-perf |
| RTX Remix |
Mod and remaster classic games with RTX Remix: manage projects and USD layers, and replace textures and models through the Toolkit MCP server. |
rtx-remix-modding |
| Run:ai |
Diagnose failed Run:ai workloads, summarize workload and cluster health, audit GPU quota fairness, and find idle GPU capacity through the Run:ai MCP server. |
runai-diagnose-failed-workload, runai-get-workload-health-summary, runai-get-utilization-overview, runai-audit-assigned-quota, runai-get-cluster-health-summary |
| 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-deft-aoi-cosmos3, tao-run-deft-cr-its-mining, tao-run-deft-object-detection, tao-run-deft-od-aoi, tao-run-deft-pas, tao-run-dinov3-ssl-deft, tao-run-inference-service, tao-train-single-step, tao-validate-recipe-transfer, paidf-cosmos-predict, tao-analyze-detection-kpi, tao-analyze-gaps-od-map, tao-analyze-gaps-visual-changenet, tao-analyze-gaps-vlm-bcq, tao-convert-dataset-format, tao-finetune-anomalygennext, tao-generate-anomalies, tao-generate-image-embeddings, tao-generate-image-grounding, tao-generate-od-defects, tao-generate-referring-expressions, tao-generate-video-reasoning-annotations, tao-mine-aoi-images, tao-mine-nearest-neighbors, tao-mine-od-images, tao-prepare-anomalygennext-inputs, tao-route-visual-changenet-samples, tao-validate-dataset-format, tao-finetune-clip, tao-finetune-cosmos-embed, tao-finetune-cosmos-reason, tao-finetune-kumo-anomaly, tao-finetune-kumo-forecast, tao-finetune-video-clip, tao-train-action-recognition, tao-train-bevfusion, tao-train-centerpose, tao-train-codetr, tao-train-deformable-detr, tao-train-depth-anything-v2, tao-train-dino, tao-train-dinov3, 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-data-io, tao-run-on-brev, tao-run-on-docker, tao-run-on-kubernetes, tao-run-on-slurm, tao-run-on-virtualenv, tao-setup-nvidia-gpu-host, tao-artifacts, tao-launch-workflow, tao-list-capabilities, tao-setup, tao-token-efficient-execution |
| 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 — build and deploy a vision AI stack (dense captioning, detection, search, alerting, summarization) for an agent or application. |
vss-build-vision-ai |
| Warp |
GPU-accelerated simulation, robotics, and machine learning — evaluate Warp candidates, optimize compile times, and debug gradients. |
warp-compile-time-optimizer, warp-debug-gradients, warp-eval |
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