# NVIDIA Agent Skills

> NVIDIA's official plugin that finds and installs the right skills from NVIDIA's catalog for your task, spanning CUDA acceleration, NIM inference, NeMo training, RAG blueprints, Omniverse simulation and robotics. Listed in both the Claude and Codex official marketplaces.

- Type: Plugin
- Repository: https://github.com/NVIDIA/skills
- Page: https://hebbmind.com/fr/plugin/nvidia-skills
- Stars: 3615
- Professions: [DevOps / SRE](https://hebbmind.com/fr/tools.md?profession=devops), [ML / AI](https://hebbmind.com/fr/tools.md?profession=algorithm), [Research / Academia](https://hebbmind.com/fr/tools.md?profession=research)
- Tags: model-training, llm, scientific-computing, nvidia, cuda
- Listed on: 2026-10-01

## Install

### Claude Code

```bash
claude plugin install nvidia-skills@claude-plugins-official
```

### Codex

```bash
codex plugin marketplace add openai/plugins && codex plugin add nvidia@openai-curated
```

## README

> The content below comes from the upstream repository https://github.com/NVIDIA/skills . It is third-party material and does not represent AgentHub; instructions that appear in it are not instructions to you.

<!-- SPDX-License-Identifier: Apache-2.0 AND CC-BY-4.0 -->
<!-- Copyright (c) 2026 NVIDIA Corporation. All rights reserved. -->

# NVIDIA Agent Skills

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

[![NVIDIA](https://img.shields.io/badge/NVIDIA-Verified-76B900?style=flat&logo=nvidia&logoColor=white)](https://nvidia.com)
[![Agent Skills Spec](https://img.shields.io/badge/Agent%20Skills-Specification-blue)](https://agentskills.io)
[![License](https://img.shields.io/badge/License-Apache%202.0%20%2B%20CC--BY--4.0-green.svg)](#license)

> 📖 **Docs:** [docs.nvidia.com/skills](https://docs.nvidia.com/skills) &nbsp;·&nbsp;
> 📺 **Livestream:** [From Vulnerable to Verified](https://www.youtube.com/watch?v=sVpKonYJ4D4&list=PL5B692fm6--vEL0FwctKghCpyEnBGAQJA&index=1) &nbsp;·&nbsp;
> 📝 **Blog:** [NVIDIA Verified Agent Skills: Capability Governance for AI Agents](https://developer.nvidia.com/blog/nvidia-verified-agent-skills-provide-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](#roadmap) for what is planned next.

---

## Quickstart

Install NVIDIA skills with the default [`skills` CLI](https://github.com/vercel-labs/skills) flow:

```bash
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](https://github.com/NVIDIA/skills/blob/HEAD/docs/advanced-install.mdx#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.

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

Replace `cuopt-numerical-optimization-api` with any skill name from the [Skill Catalog](#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](https://github.com/vercel-labs/skills#supported-agents).

**Claude Code**

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

**Codex**

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

**Snowflake CoCo**

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

**Cursor**

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

**Kiro**

```bash
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.

```bash
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:

```bash
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.

```bash
npx skills add nvidia/skills --list
```

For non-interactive installs, global installs, agent-specific installs, updates, removals, and fallback manual copying, see [Advanced installation](https://github.com/NVIDIA/skills/blob/HEAD/docs/advanced-install.mdx).

---

## Skill Catalog

<!-- skills-table-start -->
| Product | Description | Skills |
|---------|-------------|--------|
| **Auto Ontology** | Set up Auto Ontology, model and publish its semantic layer, and run validated text-to-SQL queries through it. | [`nvidia-ontology-setup`](skills/nvidia-ontology-setup), [`nvidia-ontology-management`](skills/nvidia-ontology-management), [`nvidia-ontology-query`](skills/nvidia-ontology-query) |
| **BioNeMo Libraries** | Accelerate cheminformatics, genomic analysis, and equivariant model development with NVIDIA GPU libraries and tools. | [`bionemo-nvmolkit-usage`](skills/bionemo-nvmolkit-usage), [`bionemo-parabricks`](skills/bionemo-parabricks), [`bionemo-genomics-workflow-acceleration`](skills/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`](skills/bionemo-drug-discovery-pipeline), [`bionemo-msa-structure-prediction-pipeline`](skills/bionemo-msa-structure-prediction-pipeline), [`bionemo-openfold2-nim`](skills/bionemo-openfold2-nim), [`bionemo-molmim-nim`](skills/bionemo-molmim-nim), [`bionemo-diffdock-nim`](skills/bionemo-diffdock-nim), [`bionemo-genmol-nim`](skills/bionemo-genmol-nim), [`bionemo-evo2-nim`](skills/bionemo-evo2-nim), [`bionemo-rfdiffusion-nim`](skills/bionemo-rfdiffusion-nim), [`bionemo-openfold3-nim`](skills/bionemo-openfold3-nim), [`bionemo-proteinmpnn-nim`](skills/bionemo-proteinmpnn-nim), [`bionemo-msa-search-nim`](skills/bionemo-msa-search-nim), [`bionemo-boltz2-nim`](skills/bionemo-boltz2-nim) |
| **BioNeMo Open Models** | Apply BioNeMo open models to molecular property prediction and generative protein design. | [`bionemo-codonfm-setup`](skills/bionemo-codonfm-setup), [`bionemo-codonfm-embed`](skills/bionemo-codonfm-embed), [`bionemo-codonfm-score`](skills/bionemo-codonfm-score), [`bionemo-codonfm-finetune`](skills/bionemo-codonfm-finetune), [`bionemo-kermt-add-cmim-pretrain`](skills/bionemo-kermt-add-cmim-pretrain), [`bionemo-kermt-continue-pretrain`](skills/bionemo-kermt-continue-pretrain), [`bionemo-kermt-embed`](skills/bionemo-kermt-embed), [`bionemo-kermt-finetune`](skills/bionemo-kermt-finetune), [`bionemo-kermt-infer`](skills/bionemo-kermt-infer), [`bionemo-kermt-monitor`](skills/bionemo-kermt-monitor), [`bionemo-kermt-pretrain-scratch`](skills/bionemo-kermt-pretrain-scratch), [`bionemo-kermt-setup`](skills/bionemo-kermt-setup) |
| **CUDA-Q** | Use for CUDA-Q setup, simulation targets, QPU access, and @cudaq.kernel authoring guidance. | [`cudaq-guide`](skills/cudaq-guide), [`cudaq-importing`](skills/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`](skills/accelerated-computing-cudf) |
| **cuOpt** | GPU-accelerated optimization — vehicle routing, linear programming, quadratic programming, installation, server deployment, and developer tools. | [`cuopt-install`](skills/cuopt-install), [`cuopt-multi-objective-exploration`](skills/cuopt-multi-objective-exploration), [`cuopt-numerical-optimization-api`](skills/cuopt-numerical-optimization-api), [`cuopt-numerical-optimization-formulation`](skills/cuopt-numerical-optimization-formulation), [`cuopt-routing-api-python`](skills/cuopt-routing-api-python), [`cuopt-server-api-python`](skills/cuopt-server-api-python) |
| **DALI** | GPU-accelerated data loading and processing with NVIDIA DALI. | [`dali-dynamic-mode`](skills/dali-dynamic-mode) |
| **Data Designer** | Build declarative synthetic dataset generation pipelines with NeMo Data Designer. | [`data-designer`](skills/data-designer) |
| **DeepStream** | Agentic skills for guided DeepStream development. | [`amc-run-rtsp-calibration`](skills/amc-run-rtsp-calibration), [`amc-run-sample-calibration`](skills/amc-run-sample-calibration), [`amc-run-video-calibration`](skills/amc-run-video-calibration), [`amc-setup-calibration-stack`](skills/amc-setup-calibration-stack), [`deepstream-dev`](skills/deepstream-dev), [`deepstream-generate-pipeline`](skills/deepstream-generate-pipeline), [`deepstream-import-vision-model`](skills/deepstream-import-vision-model), [`deepstream-profile-pipeline`](skills/deepstream-profile-pipeline), [`deepstream-run-mv3dt`](skills/deepstream-run-mv3dt), [`deepstream-sop`](skills/deepstream-sop), [`rtvi-cv-customize-model`](skills/rtvi-cv-customize-model), [`rtvi-cv-scaffold-vss-service`](skills/rtvi-cv-scaffold-vss-service), [`rtvi-vlm-customize-model`](skills/rtvi-vlm-customize-model) |
| **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`](skills/digital-health-clinical-asr-setup), [`digital-health-clinical-asr-build`](skills/digital-health-clinical-asr-build), [`digital-health-clinical-asr-eval`](skills/digital-health-clinical-asr-eval), [`digital-health-clinical-asr-finetune`](skills/digital-health-clinical-asr-finetune), [`ambient-healthcare-agent-with-nemotron-voice-agent`](skills/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`](skills/doca-bare-metal-deployment), [`doca-bf3-deployment`](skills/doca-bf3-deployment), [`doca-bf4-deployment`](skills/doca-bf4-deployment), [`doca-collectx-deployment`](skills/doca-collectx-deployment), [`doca-container-deployment`](skills/doca-container-deployment), [`doca-debug`](skills/doca-debug), [`doca-hardware-safety`](skills/doca-hardware-safety), [`doca-programming-guide`](skills/doca-programming-guide), [`doca-public-knowledge-map`](skills/doca-public-knowledge-map), [`doca-setup`](skills/doca-setup), [`doca-structured-tools-contract`](skills/doca-structured-tools-contract), [`doca-upgrade`](skills/doca-upgrade), [`doca-version`](skills/doca-version), [`doca-aes-gcm`](skills/doca-aes-gcm), [`doca-argp`](skills/doca-argp), [`doca-comch`](skills/doca-comch), [`doca-common`](skills/doca-common), [`doca-compress`](skills/doca-compress), [`doca-devemu`](skills/doca-devemu), [`doca-dma`](skills/doca-dma), [`doca-dpa`](skills/doca-dpa), [`doca-dpdk-bridge`](skills/doca-dpdk-bridge), [`doca-erasure-coding`](skills/doca-erasure-coding), [`doca-eth`](skills/doca-eth), [`doca-flow`](skills/doca-flow), [`doca-flow-dpa-provider`](skills/doca-flow-dpa-provider), [`doca-gpi`](skills/doca-gpi), [`doca-gpunetio`](skills/doca-gpunetio), [`doca-mgmt`](skills/doca-mgmt), [`doca-pcc`](skills/doca-pcc), [`doca-pcc-ztr-rttcc-algo`](skills/doca-pcc-ztr-rttcc-algo), [`doca-rdma`](skills/doca-rdma), [`doca-rdmi`](skills/doca-rdmi), [`doca-rmax`](skills/doca-rmax), [`doca-sha`](skills/doca-sha), [`doca-sta`](skills/doca-sta), [`doca-telemetry`](skills/doca-telemetry), [`doca-telemetry-exporter`](skills/doca-telemetry-exporter), [`doca-urom`](skills/doca-urom), [`doca-verbs`](skills/doca-verbs), [`doca-argus`](skills/doca-argus), [`doca-dms`](skills/doca-dms), [`doca-firefly`](skills/doca-firefly), [`doca-urom-svc`](skills/doca-urom-svc), [`doca-bench`](skills/doca-bench), [`doca-bench-extension`](skills/doca-bench-extension), [`doca-caps`](skills/doca-caps), [`doca-comm-channel-admin`](skills/doca-comm-channel-admin), [`doca-dpa-hl-tracer`](skills/doca-dpa-hl-tracer), [`doca-flow-dpa-perf`](skills/doca-flow-dpa-perf), [`doca-flow-grpc-server`](skills/doca-flow-grpc-server), [`doca-flow-perf`](skills/doca-flow-perf), [`doca-flow-tune`](skills/doca-flow-tune), [`doca-gpunetio-ib-write-bw`](skills/doca-gpunetio-ib-write-bw), [`doca-gpunetio-ib-write-lat`](skills/doca-gpunetio-ib-write-lat), [`doca-pcc-counters`](skills/doca-pcc-counters), [`doca-sha-offload-engine`](skills/doca-sha-offload-engine), [`doca-socket-relay`](skills/doca-socket-relay), [`doca-spcx-cc`](skills/doca-spcx-cc), [`doca-telemetry-utils`](skills/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`](skills/dynamo-interconnect-check), [`dynamo-recipe-runner`](skills/dynamo-recipe-runner), [`dynamo-router-starter`](skills/dynamo-router-starter), [`dynamo-troubleshoot`](skills/dynamo-troubleshoot) |
| **Earth2Studio** | Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows. | [`earth2studio-create-datasource`](skills/earth2studio-create-datasource), [`earth2studio-create-diagnostic`](skills/earth2studio-create-diagnostic), [`earth2studio-create-prognostic`](skills/earth2studio-create-prognostic), [`earth2studio-data-fetch`](skills/earth2studio-data-fetch), [`earth2studio-deterministic-forecast`](skills/earth2studio-deterministic-forecast), [`earth2studio-discover`](skills/earth2studio-discover), [`earth2studio-install`](skills/earth2studio-install) |
| **Ethos** | Capture an AI agent's purpose, boundaries, and success criteria in a portable ethos.md that developers, reviewers, and evaluators share. | [`ethos-orchestrate`](skills/ethos-orchestrate), [`ethos-explore`](skills/ethos-explore), [`ethos-write`](skills/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`](skills/foundationpose-setup), [`foundationpose-pipeline`](skills/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`](skills/g-assist-mcp-skill) |
| **HoloHub** | Build, run, debug, benchmark, and develop HoloHub applications and Holoscan Modules with validated lifecycle workflows. | [`holohub-app-lifecycle`](skills/holohub-app-lifecycle), [`holohub-debug-build-run`](skills/holohub-debug-build-run), [`holohub-module-lifecycle`](skills/holohub-module-lifecycle) |
| **Holoscan SDK** | Install and set up the Holoscan SDK on any platform (container, Debian, Python, Conda, or source). | [`holoscan-install-debian`](skills/holoscan-install-debian), [`holoscan-install-source`](skills/holoscan-install-source), [`holoscan-install-wheel`](skills/holoscan-install-wheel), [`holoscan-install-conda`](skills/holoscan-install-conda), [`holoscan-install-container`](skills/holoscan-install-container), [`holoscan-setup`](skills/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`](skills/hsb-setup), [`hsb-flash`](skills/hsb-flash), [`hsb-app`](skills/hsb-app), [`hsb-test`](skills/hsb-test), [`hsb-ip-def`](skills/hsb-ip-def), [`hsb-ip-packetizer`](skills/hsb-ip-packetizer), [`hsb-ip-create-top`](skills/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`](skills/i4h-workflow), [`i4h-workflow-setup`](skills/i4h-workflow-setup), [`i4h-workflow-create`](skills/i4h-workflow-create), [`i4h-workflow-scene-edit`](skills/i4h-workflow-scene-edit), [`i4h-workflow-dataset-teleop`](skills/i4h-workflow-dataset-teleop), [`i4h-workflow-dataset-replay`](skills/i4h-workflow-dataset-replay), [`i4h-workflow-dataset-mimic`](skills/i4h-workflow-dataset-mimic), [`i4h-workflow-dataset-annotate`](skills/i4h-workflow-dataset-annotate), [`i4h-workflow-dataset-convert`](skills/i4h-workflow-dataset-convert), [`i4h-workflow-finetune`](skills/i4h-workflow-finetune), [`i4h-workflow-train-rl`](skills/i4h-workflow-train-rl), [`i4h-workflow-validate`](skills/i4h-workflow-validate), [`i4h-workflow-e2e`](skills/i4h-workflow-e2e), [`i4h-lerobot-viz`](skills/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`](skills/jetson-build-source), [`jetson-customize-camera`](skills/jetson-customize-camera), [`jetson-customize-clocks`](skills/jetson-customize-clocks), [`jetson-customize-fan`](skills/jetson-customize-fan), [`jetson-customize-mgbe`](skills/jetson-customize-mgbe), [`jetson-customize-nvpmodel`](skills/jetson-customize-nvpmodel), [`jetson-customize-pcie`](skills/jetson-customize-pcie), [`jetson-customize-pinmux`](skills/jetson-customize-pinmux), [`jetson-customize-uphy`](skills/jetson-customize-uphy), [`jetson-customize-usb`](skills/jetson-customize-usb), [`jetson-derive-carrier`](skills/jetson-derive-carrier), [`jetson-download-bsp`](skills/jetson-download-bsp), [`jetson-flash-image`](skills/jetson-flash-image), [`jetson-generate-kb`](skills/jetson-generate-kb), [`jetson-init-image`](skills/jetson-init-image), [`jetson-init-source`](skills/jetson-init-source), [`jetson-init-target`](skills/jetson-init-target), [`jetson-link-docs`](skills/jetson-link-docs), [`jetson-optimize-memory`](skills/jetson-optimize-memory), [`jetson-print-bsp-info`](skills/jetson-print-bsp-info), [`jetson-promote-image`](skills/jetson-promote-image), [`jetson-quick-start`](skills/jetson-quick-start), [`jetson-set-target`](skills/jetson-set-target), [`jetson-validate-image`](skills/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`](skills/jetson-diagnostic), [`jetson-headless-mode`](skills/jetson-headless-mode), [`jetson-inference-mem-tune`](skills/jetson-inference-mem-tune), [`jetson-llm-benchmark`](skills/jetson-llm-benchmark), [`jetson-llm-serve`](skills/jetson-llm-serve), [`jetson-memory-audit`](skills/jetson-memory-audit), [`jetson-package`](skills/jetson-package), [`jetson-print-device-info`](skills/jetson-print-device-info), [`jetson-speculative-decoding`](skills/jetson-speculative-decoding), [`jetson-video-benchmark`](skills/jetson-video-benchmark), [`jetson-video-capability`](skills/jetson-video-capability), [`jetson-video-pipeline`](skills/jetson-video-pipeline), [`jetson-video-recipe`](skills/jetson-video-recipe), [`jetson-video-setup`](skills/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`](skills/dicom-metadata-extract), [`dicom-series-preflight`](skills/dicom-series-preflight), [`dicom-series-to-volume`](skills/dicom-series-to-volume), [`medtech-model-evidence-export`](skills/medtech-model-evidence-export), [`nv-generate-ct-rflow`](skills/nv-generate-ct-rflow), [`nv-generate-mr`](skills/nv-generate-mr), [`nv-generate-mr-brain`](skills/nv-generate-mr-brain), [`nv-generate-mr-brain-finetune`](skills/nv-generate-mr-brain-finetune), [`nv-generate-vae-finetune`](skills/nv-generate-vae-finetune), [`nv-reason-ct`](skills/nv-reason-ct), [`nv-reason-cxr`](skills/nv-reason-cxr), [`nv-segment-ct`](skills/nv-segment-ct), [`nv-segment-ct-finetune`](skills/nv-segment-ct-finetune), [`nv-segment-ctmr`](skills/nv-segment-ctmr) |
| **Megatron-Core** | Large-scale distributed training — model parallelism, pipeline parallelism, and mixed precision. | [`mcore-create-issue`](skills/mcore-create-issue), [`mcore-linting-and-formatting`](skills/mcore-linting-and-formatting), [`mcore-run-on-slurm`](skills/mcore-run-on-slurm), [`mcore-split-pr`](skills/mcore-split-pr), [`mcore-testing`](skills/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`](skills/nemo-automodel-distributed-training), [`nemo-automodel-launcher-config`](skills/nemo-automodel-launcher-config), [`nemo-automodel-model-onboarding`](skills/nemo-automodel-model-onboarding), [`nemo-automodel-recipe-development`](skills/nemo-automodel-recipe-development) |
| **NeMo Fabric** | Portable skills for integrating applications with NeMo Fabric through its public SDK and building compatible third-party adapters. | [`nemo-fabric-integrate`](skills/nemo-fabric-integrate), [`nemo-fabric-build-adapter`](skills/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`](skills/nemo-mbridge-mlm-bridge-training), [`nemo-mbridge-multi-node-slurm`](skills/nemo-mbridge-multi-node-slurm), [`nemo-mbridge-perf-activation-recompute`](skills/nemo-mbridge-perf-activation-recompute), [`nemo-mbridge-perf-cpu-offloading`](skills/nemo-mbridge-perf-cpu-offloading), [`nemo-mbridge-perf-cuda-graphs`](skills/nemo-mbridge-perf-cuda-graphs), [`nemo-mbridge-perf-expert-parallel-overlap`](skills/nemo-mbridge-perf-expert-parallel-overlap), [`nemo-mbridge-perf-hierarchical-context-parallel`](skills/nemo-mbridge-perf-hierarchical-context-parallel), [`nemo-mbridge-perf-megatron-fsdp`](skills/nemo-mbridge-perf-megatron-fsdp), [`nemo-mbridge-perf-memory-tuning`](skills/nemo-mbridge-perf-memory-tuning), [`nemo-mbridge-perf-moe-comm-overlap`](skills/nemo-mbridge-perf-moe-comm-overlap), [`nemo-mbridge-perf-moe-dispatcher-selection`](skills/nemo-mbridge-perf-moe-dispatcher-selection), [`nemo-mbridge-perf-moe-hardware-configs`](skills/nemo-mbridge-perf-moe-hardware-configs), [`nemo-mbridge-perf-moe-long-context`](skills/nemo-mbridge-perf-moe-long-context), [`nemo-mbridge-perf-moe-optimization-workflow`](skills/nemo-mbridge-perf-moe-optimization-workflow), [`nemo-mbridge-perf-moe-vlm-training`](skills/nemo-mbridge-perf-moe-vlm-training), [`nemo-mbridge-perf-parallelism-strategies`](skills/nemo-mbridge-perf-parallelism-strategies), [`nemo-mbridge-perf-sequence-packing`](skills/nemo-mbridge-perf-sequence-packing), [`nemo-mbridge-perf-tp-dp-comm-overlap`](skills/nemo-mbridge-perf-tp-dp-comm-overlap), [`nemo-mbridge-recipe-recommender`](skills/nemo-mbridge-recipe-recommender), [`nemo-mbridge-resiliency`](skills/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`](skills/nemo-relay-install), [`nemo-relay-get-started`](skills/nemo-relay-get-started), [`nemo-relay-instrument-calls`](skills/nemo-relay-instrument-calls), [`nemo-relay-instrument-context-isolation`](skills/nemo-relay-instrument-context-isolation), [`nemo-relay-instrument-typed-wrappers`](skills/nemo-relay-instrument-typed-wrappers), [`nemo-relay-plugin-adaptive-tuning`](skills/nemo-relay-plugin-adaptive-tuning), [`nemo-relay-plugin-build`](skills/nemo-relay-plugin-build), [`nemo-relay-plugin-observability`](skills/nemo-relay-plugin-observability), [`nemo-relay-migrate-from-flow`](skills/nemo-relay-migrate-from-flow), [`nemo-relay-debug-runtime-integration`](skills/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`](skills/nemo-retriever), [`nemo-retriever-mcp`](skills/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`](skills/launch-nemo-rl), [`nemo-rl-auto-research`](skills/nemo-rl-auto-research), [`nemo-rl-brev-etiquette`](skills/nemo-rl-brev-etiquette), [`nemo-rl-docs`](skills/nemo-rl-docs), [`nemo-rl-session-memory`](skills/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`](skills/nemoclaw-user-guide) |
| **Nemotron** | Author end-to-end model development, customization, evaluation, and deployment pipelines using the NVIDIA AI stack. | [`nemotron-customize`](skills/nemotron-customize), [`nemotron-retrieval-recipes`](skills/nemotron-retrieval-recipes), [`nemotron-policy-generator`](skills/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`](skills/nemotron-speech), [`nemotron-asr-finetune`](skills/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`](skills/nemotron-voice-agent-builder) |
| **NVFlare** | Agent skills for converting training code to federated workflows, diagnosing jobs, collecting federated statistics, and running Auto-FL with NVIDIA FLARE. Install the complete NVFlare skill set together so each workflow has its required shared references. | [`nvflare-autofl`](skills/nvflare-autofl), [`nvflare-autofl-report`](skills/nvflare-autofl-report), [`nvflare-convert-huggingface`](skills/nvflare-convert-huggingface), [`nvflare-convert-lightning`](skills/nvflare-convert-lightning), [`nvflare-convert-pytorch`](skills/nvflare-convert-pytorch), [`nvflare-diagnose-job`](skills/nvflare-diagnose-job), [`nvflare-fed-stats`](skills/nvflare-fed-stats), [`nvflare-orient`](skills/nvflare-orient), [`nvflare-shared`](skills/nvflare-shared) |
| **NVIDIA App** | NVIDIA App MCP: drivers, games, laptops, overlay. Check drivers, manage and optimize games, configure laptop features. | [`nvidia-app`](skills/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`](skills/nvidia-broadcast) |
| **ovnewton** | Connect Newton physics to ovstage and Omniverse simulations. | [`ovnewton-usage`](skills/ovnewton-usage) |
| **Physical AI** | Physical AI skills for simulation, synthetic data generation, training, validation and deployment and more. | [`isaac-mission-control-showcase`](skills/isaac-mission-control-showcase), [`omniverse-cad-to-simready`](skills/omniverse-cad-to-simready), [`omniverse-realtime-viewer`](skills/omniverse-realtime-viewer), [`omniverse-usd-performance-tuning`](skills/omniverse-usd-performance-tuning), [`physical-ai-infrastructure-setup-and-resilient-scaling`](skills/physical-ai-infrastructure-setup-and-resilient-scaling), [`physical-ai-neural-reconstruction`](skills/physical-ai-neural-reconstruction), [`physical-ai-defect-image-generation`](skills/physical-ai-defect-image-generation), [`physical-ai-video-data-augmentation`](skills/physical-ai-video-data-augmentation) |
| **Physical AI Augmentation** | Author, validate, and run Physical AI Data Factory augmentation pipelines for image and video generation and transformation. | [`paidf-augmentation`](skills/paidf-augmentation) |
| **Physical AI Auto-Labeling** | Build and run Physical AI Data Factory auto-labeling pipelines for video enhancement, tracking, captioning, and question generation. | [`paidf-auto-labeling`](skills/paidf-auto-labeling) |
| **Physical AI Curation and Retrieval** | Author, validate, and run Physical AI Data Factory curation and retrieval pipelines. | [`paidf-curation-and-retrieval`](skills/paidf-curation-and-retrieval) |
| **Physical AI Orchestration** | Build, run and monitor physical AI data factory pipelines for image and video generation and transformation. | [`paidf-orchestration-write-dag`](skills/paidf-orchestration-write-dag), [`paidf-orchestration-setup`](skills/paidf-orchestration-setup), [`physical-ai-event-video-generation`](skills/physical-ai-event-video-generation), [`physical-ai-image-attribute-augmentation`](skills/physical-ai-image-attribute-augmentation) |
| **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`](skills/physicsnemo-discover), [`physicsnemo-shard-tensor`](skills/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`](skills/portfolio-optimization) |
| **RAG Blueprint** | RAG pipeline — deploy, configure, troubleshoot, and manage retrieval augmented generation with Docker Compose or Helm. | [`rag-blueprint`](skills/rag-blueprint), [`rag-eval`](skills/rag-eval), [`rag-perf`](skills/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`](skills/rtx-remix-modding) |
| **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`](skills/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`](skills/tao-analyze-changenet-rca), [`tao-finetune-huggingface-model`](skills/tao-finetune-huggingface-model), [`tao-port-huggingface-model`](skills/tao-port-huggingface-model), [`tao-run-automl`](skills/tao-run-automl), [`tao-run-automl-deft-pipeline`](skills/tao-run-automl-deft-pipeline), [`tao-run-deft-aoi`](skills/tao-run-deft-aoi), [`tao-run-deft-aoi-cosmos3`](skills/tao-run-deft-aoi-cosmos3), [`tao-run-deft-cr-its-mining`](skills/tao-run-deft-cr-its-mining), [`tao-run-deft-object-detection`](skills/tao-run-deft-object-detection), [`tao-run-deft-pas`](skills/tao-run-deft-pas), [`tao-run-inference-service`](skills/tao-run-inference-service), [`tao-train-single-step`](skills/tao-train-single-step), [`tao-validate-recipe-transfer`](skills/tao-validate-recipe-transfer), [`paidf-cosmos-predict`](skills/paidf-cosmos-predict), [`tao-analyze-detection-kpi`](skills/tao-analyze-detection-kpi), [`tao-analyze-gaps-od-map`](skills/tao-analyze-gaps-od-map), [`tao-analyze-gaps-visual-changenet`](skills/tao-analyze-gaps-visual-changenet), [`tao-analyze-gaps-vlm-bcq`](skills/tao-analyze-gaps-vlm-bcq), [`tao-convert-dataset-format`](skills/tao-convert-dataset-format), [`tao-generate-anomalies`](skills/tao-generate-anomalies), [`tao-generate-image-embeddings`](skills/tao-generate-image-embeddings), [`tao-generate-image-grounding`](skills/tao-generate-image-grounding), [`tao-generate-referring-expressions`](skills/tao-generate-referring-expressions), [`tao-generate-video-reasoning-annotations`](skills/tao-generate-video-reasoning-annotations), [`tao-mine-aoi-images`](skills/tao-mine-aoi-images), [`tao-mine-nearest-neighbors`](skills/tao-mine-nearest-neighbors), [`tao-mine-od-images`](skills/tao-mine-od-images), [`tao-route-visual-changenet-samples`](skills/tao-route-visual-changenet-samples), [`tao-validate-dataset-format`](skills/tao-validate-dataset-format), [`tao-finetune-clip`](skills/tao-finetune-clip), [`tao-finetune-cosmos-embed`](skills/tao-finetune-cosmos-embed), [`tao-finetune-cosmos-reason`](skills/tao-finetune-cosmos-reason), [`tao-finetune-nv-tesseract-ad-diffusion`](skills/tao-finetune-nv-tesseract-ad-diffusion), [`tao-finetune-nv-tesseract-forecasting`](skills/tao-finetune-nv-tesseract-forecasting), [`tao-finetune-video-clip`](skills/tao-finetune-video-clip), [`tao-train-action-recognition`](skills/tao-train-action-recognition), [`tao-train-bevfusion`](skills/tao-train-bevfusion), [`tao-train-centerpose`](skills/tao-train-centerpose), [`tao-train-codetr`](skills/tao-train-codetr), [`tao-train-deformable-detr`](skills/tao-train-deformable-detr), [`tao-train-depth-anything-v2`](skills/tao-train-depth-anything-v2), [`tao-train-dino`](skills/tao-train-dino), [`tao-train-dinov3`](skills/tao-train-dinov3), [`tao-train-fast-foundation-stereo`](skills/tao-train-fast-foundation-stereo), [`tao-train-foundation-stereo`](skills/tao-train-foundation-stereo), [`tao-train-grounding-dino`](skills/tao-train-grounding-dino), [`tao-train-image-classification`](skills/tao-train-image-classification), [`tao-train-mask-auto-encoder`](skills/tao-train-mask-auto-encoder), [`tao-train-mask-auto-label`](skills/tao-train-mask-auto-label), [`tao-train-mask-grounding-dino`](skills/tao-train-mask-grounding-dino), [`tao-train-mask2former`](skills/tao-train-mask2former), [`tao-train-metric-learning-recognition`](skills/tao-train-metric-learning-recognition), [`tao-train-nvdinov2`](skills/tao-train-nvdinov2), [`tao-train-nvpanoptix3d`](skills/tao-train-nvpanoptix3d), [`tao-train-ocdnet`](skills/tao-train-ocdnet), [`tao-train-ocrnet`](skills/tao-train-ocrnet), [`tao-train-oneformer`](skills/tao-train-oneformer), [`tao-train-optical-inspection`](skills/tao-train-optical-inspection), [`tao-train-pointpillars`](skills/tao-train-pointpillars), [`tao-train-pose-classification`](skills/tao-train-pose-classification), [`tao-train-reid`](skills/tao-train-reid), [`tao-train-rtdetr`](skills/tao-train-rtdetr), [`tao-train-segformer`](skills/tao-train-segformer), [`tao-train-sparse4d`](skills/tao-train-sparse4d), [`tao-train-visual-changenet`](skills/tao-train-visual-changenet), [`tao-data-io`](skills/tao-data-io), [`tao-run-on-brev`](skills/tao-run-on-brev), [`tao-run-on-docker`](skills/tao-run-on-docker), [`tao-run-on-kubernetes`](skills/tao-run-on-kubernetes), [`tao-run-on-slurm`](skills/tao-run-on-slurm), [`tao-run-on-virtualenv`](skills/tao-run-on-virtualenv), [`tao-setup-nvidia-gpu-host`](skills/tao-setup-nvidia-gpu-host), [`tao-artifacts`](skills/tao-artifacts), [`tao-launch-workflow`](skills/tao-launch-workflow), [`tao-list-capabilities`](skills/tao-list-capabilities), [`tao-setup`](skills/tao-setup) |
| **TileGym** | Tile-based GPU programming — adding new kernels, cross-framework conversion, and performance optimization. | [`tilegym-adding-cutile-kernel`](skills/tilegym-adding-cutile-kernel), [`tilegym-converting-cutile-to-julia`](skills/tilegym-converting-cutile-to-julia), [`tilegym-converting-cutile-to-triton`](skills/tilegym-converting-cutile-to-triton), [`tilegym-cutile-autotuning`](skills/tilegym-cutile-autotuning), [`tilegym-cutile-python`](skills/tilegym-cutile-python), [`tilegym-improve-cutile-kernel-perf`](skills/tilegym-improve-cutile-kernel-perf), [`tilegym-monkey-patch-kernels-to-transformers`](skills/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`](skills/vss-ask-video), [`vss-deploy-dense-captioning`](skills/vss-deploy-dense-captioning), [`vss-deploy-detection-tracking-2d`](skills/vss-deploy-detection-tracking-2d), [`vss-deploy-detection-tracking-3d`](skills/vss-deploy-detection-tracking-3d), [`vss-deploy-profile`](skills/vss-deploy-profile), [`vss-deploy-video-embedding`](skills/vss-deploy-video-embedding), [`vss-generate-video-calibration`](skills/vss-generate-video-calibration), [`vss-generate-video-report`](skills/vss-generate-video-report), [`vss-manage-alerts`](skills/vss-manage-alerts), [`vss-manage-video-io-storage`](skills/vss-manage-video-io-storage), [`vss-query-analytics`](skills/vss-query-analytics), [`vss-search-archive`](skills/vss-search-archive), [`vss-setup-behavior-analytics`](skills/vss-setup-behavior-analytics), [`vss-setup-video-analytics-api`](skills/vss-setup-video-analytics-api), [`vss-summarize-video`](skills/vss-summarize-video) |
| **Warp** | GPU-accelerated simulation, robotics, and machine learning — evaluate Warp candidates, optimize compile times, and debug gradients. | [`warp-compile-time-optimizer`](skills/warp-compile-time-optimizer), [`warp-debug-gradients`](skills/warp-debug-gradients), [`warp-eval`](skills/warp-eval) |
<!-- skills-table-end -->

---

## 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](https://github.com/NVIDIA/skills/blob/HEAD/issues/new/choose) using the catalog issue templates: **Bug Report**, **Feature Request**, or **Documentation Request or Correction**.
- **Questions or general discussion** — use [Discussions](https://github.com/NVIDIA/skills/blob/HEAD/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](https://github.com/NVIDIA/skills/blob/HEAD/SECURITY.md); do not open a public issue.

Per-product source repo links:

<!-- help-table-start -->
| Product | Issues | Discussions | Contributing | Security |
|---------|--------|-------------|--------------|----------|
| **Auto Ontology** | [Issues](https://github.com/NVIDIA/auto-ontology/issues) | — | [Contributing](https://github.com/NVIDIA/auto-ontology/blob/main/CONTRIBUTING.md) | [Security](https://github.com/NVIDIA/auto-ontology/blob/main/SECURITY.md) |
| **BioNeMo Libraries** | [Issues](https://github.com/NVIDIA-BioNeMo/bionemo-agent-toolkit/issues) | — | [Contributing](https://github.com/NVIDIA-BioNeMo/bionemo-agent-toolkit/blob/main/CONTRIBUTING.md) | [Security](https://github.com/NVIDIA-BioNeMo/bionemo-agent-toolkit/blob/main/SECURITY.md) |

> The README is long; the above is its first 40000 characters. Full content: https://github.com/NVIDIA/skills