- NreUse to drive NVIDIA Omniverse NuRec / Neural Reconstruction Engine (NRE) via the public NGC containers nvcr.io/nvidia/nre/nre and nvcr.io/nvidia/nre/nre-tools (NGC_API_KEY required) — train 3DGUT Gaussian reconstructions from NCore clips, generate aux data, render frames or LiDAR sweeps (local or warm `serve-grpc`), export PLY/depth/mesh/USDZ, edit actors, and evaluate metrics. Do NOT use for per-object asset capture (use `asset-harvester`) or sensor-to-NCore conversion (use `ncore`).NVIDIA/nurec-skills15
- Nurec FixerUse to run NVIDIA DiffusionHarmonizer (public successor to the older Fixer recipes) to enhance, harmonize, evaluate, or fine-tune novel-view frames from NRE / NuRec / 3DGS / NeRF reconstructions. Do NOT use for training the 3D reconstruction itself (use `nre`) or for sensor-to-NCore conversion (use `ncore`).NVIDIA/nurec-skills15
- Nurec IndexRouter for NVIDIA NuRec / NRE / 3DGUT / USDZ / NCore V4 / asset harvest / frame cleanup tasks — picks the right sibling (nre, ncore, asset-harvester, nurec-fixer, physical-ai-datasets). Use when the sub-skill is unclear or a multi-stage pipeline is needed; do NOT use for non-NuRec tasks or to run any pipeline itself.NVIDIA/nurec-skills15
- Physical Ai DatasetsUse when the user wants to find, download, or pick a NVIDIA Physical AI dataset on Hugging Face for autonomous-vehicle, robotics, spatial intelligence, manipulation, or neural-reconstruction workflows. Catalog of every dataset under huggingface.co/nvidia with the `PhysicalAI-` prefix, organised by domain (AV, Robotics-Manipulation, Robotics-GR00T, Robotics-mindmap, Robotics-NuRec, Spatial Intelligence, Grasping, Healthcare, Sim-Ready, Material properties), with per-dataset size, format, gating, NVIDIA/nurec-skills15
- K8s Launch Kit ConfigUse this skill when the user needs help understanding, creating, or editing a k8s-launch-kit (l8k) configuration file (l8k-config.yaml or cluster-config.yaml). Activate for: config file questions, parameter tuning, subnet configuration, NV-IPAM setup, DOCA driver settings, maintenance concurrency, NIC configuration operator settings, changing MTU, VFs, resource names, or understanding what any config field does.NVIDIA/k8s-launch-kit13
- K8s Launch Kit DeployUse this skill when the user wants to deploy generated NVIDIA networking manifests to a Kubernetes cluster using k8s-launch-kit (l8k). Activate for: applying manifests, deploying to cluster, the `l8k deploy` subcommand or the legacy --deploy flag on `l8k generate`, applying generated files, or any mention of pushing l8k output to a live cluster. Even if the user just says 'apply these' or 'push to cluster' after generating manifests, use this skill.NVIDIA/k8s-launch-kit13
- K8s Launch Kit DiscoverUse this skill when the user wants to discover their Kubernetes cluster's network hardware capabilities using k8s-launch-kit (l8k). Activate for: cluster discovery, hardware detection, NIC detection, finding what GPUs or NICs are in a cluster, creating a cluster config file, or when the user says 'discover' in the context of l8k or NVIDIA networking.NVIDIA/k8s-launch-kit13
- K8s Launch Kit DryrunUse this skill when the user wants to preview what k8s-launch-kit (l8k) would deploy without making changes, or wants to safely validate their configuration before applying. Activate for: dry-run, preview, validation, 'what would happen if', testing configurations, schema discovery, checking generated manifests, or any cautious pre-deployment step. Also use when the user asks 'is my config valid' or 'show me what would be created' -- even without mentioning dry-run explicitly.NVIDIA/k8s-launch-kit13
- K8s Launch Kit GenerateUse this skill when the user wants to generate Kubernetes YAML manifests for NVIDIA networking deployment using k8s-launch-kit (l8k). Activate for: manifest generation, profile selection, choosing between SR-IOV/host-device/RDMA-shared/IPoIB/MacVLAN/Spectrum-X, creating deployment files, or when the user asks 'which profile should I use' or needs help choosing a network configuration.NVIDIA/k8s-launch-kit13
- K8s Launch Kit PipelineUse this skill when the user wants to run the full k8s-launch-kit (l8k) pipeline end-to-end: discover cluster hardware, select a profile, generate manifests, and deploy them all in one command. Also activate for CI/CD integration, automation pipelines, 'one-liner', 'complete workflow', or end-to-end NVIDIA networking deployment.NVIDIA/k8s-launch-kit13
- K8s Launch Kit Sharedk8s-launch-kit (l8k) CLI: Shared patterns for binary location, global flags, output formatting, exit codes, and error handling. Read this before using any other k8s-launch-kit skill.NVIDIA/k8s-launch-kit13
- K8s Launch Kit TroubleshootUse this skill when the user has problems with NVIDIA Network Operator on Kubernetes, or wants to analyze a sosreport diagnostic dump. Activate for: OFED driver crashes, SR-IOV pods failing, NicClusterPolicy errors, network operator pod issues, RDMA not working, NIC configuration failures, pods stuck in CrashLoopBackOff or ContainerCreating with network annotations, VF allocation issues, or when the user mentions 'troubleshoot', 'debug', 'sosreport', 'diagnose', or describes any NVIDIA networkinNVIDIA/k8s-launch-kit13
- K8s Launch Kit ValidateUse this skill when the user wants to verify that an NVIDIA networking deployment matches the configuration that produced it. Activate for: 'is my deployment correct', 'are all the manifests applied', 'does the network operator version match', 'verify deployment', 'check cluster state against config', or any question about whether the cluster reflects what l8k generated. Wraps the `l8k validate` subcommand.NVIDIA/k8s-launch-kit13
- K8s Network EngineerEmbody a senior NVIDIA Networking Engineer who is an expert on deploying cloud-native networking on Kubernetes with k8s-launch-kit (l8k). Activate whenever the user mentions NVIDIA network profiles, SR-IOV, RDMA, Spectrum-X, BlueField, ConnectX, NIC configuration, Network Operator, DOCA drivers, multirail networking, l8k, k8s-launch-kit, or any Kubernetes networking topic involving NVIDIA hardware. Also activate when the user asks general questions about high-performance networking, GPU interconNVIDIA/k8s-launch-kit13
- 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'.NVIDIA/DeepStream10
- 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.NVIDIA/DeepStream10
- Amc Setup Calibration StackLaunch AutoMagicCalib microservice and web UI from NGC release images via Docker Compose. Use when user says 'deploy auto calibration', 'launch auto calibration', 'launch AMC', 'start MS+UI', or 'set up auto-magic-calib'. Requires NGC API key.NVIDIA/DeepStream10
- AnomalygenPAIDF AnomalyGen pipeline — fine-tune, generate synthetic anomaly images (SDG), evaluate quality (nn_score), and per-sample search. Modes: full (train + generate), finetune_only, inference_only (from checkpoint). Invoke for any AnomalyGen / SDG / fine-tune / synthetic-anomaly task — even if the user only mentions one phase.NVIDIA/paidf-anomalygen10
- Anomalygen GuardProduct runtime guardrails and preflight validation for PAIDF AnomalyGen. Use only when ANOMALYGEN_PRODUCT_MODE=1, typically inside the product container, before training, inference, evaluation, refinement, filtering, artifact edits, or release runtime validation.NVIDIA/paidf-anomalygen10
- Anomalygen ReleaseBuild and validate PAIDF AnomalyGen product and develop Docker containers from docker/Dockerfile.cuda128. Use when the user asks to build an anomalygen product container, build an anomalygen develop container, validate container runtime permissions, or produce release summaries.NVIDIA/paidf-anomalygen10
- Deepstream DevNVIDIA DeepStream SDK 9.0 development with Python pyservicemaker API. Use when building video analytics pipelines, GStreamer-based video processing, TensorRT inference integration, object detection/tracking, or Kafka/message broker integration.NVIDIA/DeepStream10
- Deepstream Generate PipelineBuild DeepStream GStreamer pipelines interactively. Use when the user asks about pipelines for video/image inference, detection, tracking, or streaming — including natural phrases like 'pipeline to infer on image', 'run inference on video', 'detect objects in stream', 'save inference output', 'deepstream pipeline', 'gst-launch pipeline', 'process video with detection', 'build a pipeline', or any request involving GStreamer/DeepStream elements (nvinfer, nvstreammux, nvtracker, etc.).NVIDIA/DeepStream10
- Deepstream Import Vision ModelUse this skill to bring any vision model from HuggingFace or NVIDIA NGC into an NVIDIA DeepStream pipeline with end-to-end automation: ONNX download, SafeTensors export, TRT engine build, custom nvinfer bbox parser, multi-stream benchmark, and PDF report. Object detection models only.NVIDIA/DeepStream10
- Deepstream Profile PipelineProfile a DeepStream pipeline with Nsight Systems and derive its configs from the measurement. Use when the user asks for an efficient, performant, or profiled pipeline — or to benchmark, tune, or measure FPS.NVIDIA/DeepStream10
- Deepstream SopUse this skill when building, deploying, evaluating, debugging, or measuring latency for the DeepStream SOP Inference Microservice — a GPU-accelerated FastAPI service that detects whether operators perform assembly-line steps in order via event boundary detection (GEBD) plus VLM classification. Trigger even if the user does not name it: verify operator step sequence, detect missing or out-of-order SOP steps, score factory/work-cell video for procedure compliance, run VLM-based SOP checking on inNVIDIA/DeepStream10
- Ai Inference RecipeCreates single-point srt-slurm recipes from NVIDIA AI Inference benchmark rows. Use when the user mentions ai-inference, NVIDIA inference performance pages, benchmark rows, or asks to create a non-sweep recipe from model/GPU/framework/sequence/concurrency details.NVIDIA/srt-slurm-recipes4
- Digital Health Clinical Asr BuildStage 2 of the Clinical ASR Flywheel. Use when curating clinical terms, tagging IPA, and synthesizing a NeMo manifest. NOT for scoring (use /digital-health-clinical-asr-eval).NVIDIA/digital-health-skills4
- Digital Health Clinical Asr EvalStage 3 of Clinical ASR Flywheel. Score a NeMo manifest, produce the five-section KER leaderboard (by-ipa_source diagnostic). Not for ASR auth (/riva-asr).NVIDIA/digital-health-skills4
- Digital Health Clinical Asr FinetuneStage 4 of the Clinical ASR Flywheel. Use when priority KER is above 0.3 to run stock NeMo SFT on Parakeet TDT v2 and offline cycle N+1 re-eval. NOT for generic word boosting (use /finetune-asr).NVIDIA/digital-health-skills4
- Digital Health Clinical Asr SetupStage 1 of Clinical ASR Flywheel. Use when bootstrapping a cycle: NVCF+MW disclosure, NVIDIA_API_KEY check, deps install, TTS+ASR smoke test.NVIDIA/digital-health-skills4
- Nemo Clinical Data DesignerUse when generating synthetic tabular datasets via Data Designer — sampler columns, LLM columns, custom generators. Not for ASR audio.NVIDIA/digital-health-skills4
- Riva AsrUse when the user wants to deploy, run, or test an ASR (speech-to-text) Riva NIM — cloud-hosted (build.nvidia.com) or self-hosted Parakeet/Canary/Whisper.NVIDIA/digital-health-skills4
- Riva Asr CustomUse when the user wants to deploy a custom-trained ASR model as a Riva NIM, or convert a NeMo model via nemo2riva / riva-build / riva-deploy / RMIR.NVIDIA/digital-health-skills4
- Riva Nim SetupUse when getting started with NVIDIA Riva Speech NIMs: NGC access, Docker login for nvcr.io, NVIDIA Container Toolkit, GPU verification, Riva Python client.NVIDIA/digital-health-skills4
- Riva TtsUse when the user wants to deploy, run, or test a TTS (speech-synthesis) Riva NIM — cloud-hosted (build.nvidia.com) or self-hosted Magpie / voice cloning.NVIDIA/digital-health-skills4
- Auto LabelingBuild Docker-backed PAIDF auto-labeling commands for SR, tracking, VLM JSON, and MCQ runs. Use for pipeline planning or execution requests. Do NOT use for unrelated Docker tasks.NVIDIA/paidf-auto-labeling2