Skill collection
NVIDIA/skills agent skills, page 8
Skills in NVIDIA/skills, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 337 | NVIDIA RAG Blueprint — deploy, configure, troubleshoot, and manage. | NVIDIA/ | 3.6k | — | ~2.8k | Automated safety check: Notes | Apache-2.0 | today |
| 338 | Filesystem RAG benchmarks: corpus/, train.json, evaluaterag.py (RAGAS quality). | NVIDIA/ | 3.6k | — | ~2.3k | Automated safety check: Notes | Apache-2.0 | today |
| 339 | Performance benchmarking for a deployed NVIDIA RAG Blueprint server: profiling pass + aiperf load test driven by a single YAML config. | NVIDIA/ | 3.6k | — | ~4.1k | Automated safety check: Pass | Apache-2.0 | today |
| 340 | How to swap the DeepStream CV detection model in the VSS Alerts Blueprint verification (2dcv) mode - covers ONNX export, custom bbox parsers, compose mount gotchas, nvinfer config, runtime TRT… | NVIDIA/ | 3.6k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | today |
| 341 | How to swap the VLM in the VSS Alerts Blueprint — covers RTVI-VLM microservice deployment methods, all three VLM consumers (rtvi-vlm, vlm-as-verifier, vss-agent), and health checks. | NVIDIA/ | 3.6k | — | ~5k | Automated safety check: Notes | Apache-2.0 | today |
| 342 | Shared Cosmos3 frontend that explicitly routes Cosmos Framework and Cosmos-RL, validates runtime model/video-dataset/SLURM inputs, consumes an SQSH or packaged backend image, optionally plans… | NVIDIA/ | 3.6k | — | ~5k | Automated safety check: Notes | Apache-2.0 | today |
| 343 | Integrate a HuggingFace Computer Vision model into the NVIDIA TAO Toolkit ecosystem (tao-core config, tao-pytorch trainer, tao-deploy TensorRT pipeline). | NVIDIA/ | 3.6k | — | ~4.5k | Automated safety check: Notes | Apache-2.0 | today |
| 344 | Standard single-step train/eval/export workflow for any TAO model. | NVIDIA/ | 3.6k | — | ~1.2k | Automated safety check: Notes | Apache-2.0 | today |
| 345 | Deploy and operate the RTVI-CV-3D microservice as MV3DT (MODE=mv3dt): per-camera DeepStream perception plus BEV Fusion over calibrated cameras. | NVIDIA/ | 3.6k | — | ~4.8k | Automated safety check: Notes | Apache-2.0 | today |
| 346 | Trace, complete, and interpret the Pareto frontier across competing objectives using repeated single-objective cuOpt solves (weighted-sum and ε-constraint). | NVIDIA/ | 3.6k | — | ~3.9k | Automated safety check: Pass | Apache-2.0 | today |
| 347 | LP, MILP, QP — concepts, problem-text parsing, and formulation patterns (parameters, constraints, decisions, objective). | NVIDIA/ | 3.6k | — | ~4.9k | Automated safety check: Pass | Apache-2.0 | today |
| 348 | A skill your agent uses when the user wants to create a dataset, generate synthetic data, or build a data generation pipeline. | NVIDIA/ | 3.6k | — | ~1.2k | Automated safety check: Warn | Apache-2.0 | today |
| 349 | Build Holoscan SDK from source via the in-tree ./run script. | NVIDIA/ | 3.6k | — | ~1.5k | Automated safety check: Notes | Apache-2.0 | today |
| 350 | Bootstrap a custom carrier board by forking carrier files and scaffolding a DT overlay from the reference devkit. | NVIDIA/ | 3.6k | — | ~4.2k | Automated safety check: Pass | Apache-2.0 | today |
| 351 | Build a per-target knowledge-base markdown next to the active profile by walking the BSP root and source tree. | NVIDIA/ | 3.6k | — | ~3.8k | Automated safety check: Pass | Apache-2.0 | today |
| 352 | Extract Jetson Linux + sample-rootfs tarballs and run applybinaries.sh for the active target, then record bspimage in the profile. | NVIDIA/ | 3.6k | — | ~1.8k | Automated safety check: Notes | Apache-2.0 | today |
| 353 | Entry skill for Jetson / IGX BSP customization. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~4.7k | Automated safety check: Pass | Apache-2.0 | today |
| 354 | Switch the active Jetson target-platform pointer to an existing profile YAML. | NVIDIA/ | 3.6k | — | ~1.7k | Automated safety check: Pass | Apache-2.0 | today |
| 355 | Guide for selecting and configuring distributed training strategies in NeMo AutoModel, including FSDP2, Megatron FSDP, DDP, and parallelism settings. | NVIDIA/ | 3.6k | — | ~4.8k | Automated safety check: Pass | Apache-2.0 | today |
| 356 | Configure NeMo AutoModel job launches for interactive runs, Slurm clusters, and SkyPilot cloud execution. | NVIDIA/ | 3.6k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | today |
| 357 | Create and modify NeMo AutoModel training and evaluation recipes, including YAML structure, builders, and execution flow. | NVIDIA/ | 3.6k | — | ~3k | Automated safety check: Pass | Apache-2.0 | today |
| 358 | Run Megatron-LM (MLM) and Megatron Bridge training with mock or real data. | NVIDIA/ | 3.6k | — | ~1.6k | Automated safety check: Pass | Apache-2.0 | today |
| 359 | Validate and use CPU offloading in Megatron Bridge, including layer-level activation offloading and fractional optimizer state offloading with HybridDeviceOptimizer. | NVIDIA/ | 3.6k | — | ~2.3k | Automated safety check: Pass | Apache-2.0 | today |
| 360 | Validate and use CUDA graph capture in Megatron Bridge, including local full-iteration graphs and Transformer Engine scoped graphs for attention, MLP, and MoE modules. | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | today |
| 361 | Validate and use MoE expert-parallel communication overlap in Megatron-Bridge, including overlapmoeexpertparallelcomm, delaywgradcompute, and flex dispatcher backends such as DeepEP and HybridEP. | NVIDIA/ | 3.6k | — | ~3.5k | Automated safety check: Pass | Apache-2.0 | today |
| 362 | Operational guide for enabling hierarchical context parallelism in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification. | NVIDIA/ | 3.6k | — | ~1.4k | Automated safety check: Pass | Apache-2.0 | today |
| 363 | Operational guide for enabling Megatron FSDP in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification. | NVIDIA/ | 3.6k | — | ~973 | Automated safety check: Pass | Apache-2.0 | today |
| 364 | Techniques for reducing peak GPU memory in Megatron Bridge — expandable segments, PEFT + SP input re-gather, parallelism resizing, activation recompute, CPU offloading constraints, and common OOM… | NVIDIA/ | 3.6k | — | ~3.6k | Automated safety check: Pass | Apache-2.0 | today |
| 365 | MoE expert-parallel communication overlap in Megatron Bridge. | NVIDIA/ | 3.6k | — | ~1.9k | Automated safety check: Pass | Apache-2.0 | today |
| 366 | Choose the right MoE token dispatcher (alltoall, DeepEP, or HybridEP) for the hardware, EP degree, and optimization stage. | NVIDIA/ | 3.6k | — | ~2k | Automated safety check: Pass | Apache-2.0 | today |
| 367 | Representative, point-in-time MoE training playbooks by hardware and model family. | NVIDIA/ | 3.6k | — | ~2k | Automated safety check: Pass | Apache-2.0 | today |
| 368 | Long-context MoE training guidance for Megatron Bridge. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~1.2k | Automated safety check: Pass | Apache-2.0 | today |
| 369 | Evidence-gated workflow for MoE performance optimization in Megatron Bridge. | NVIDIA/ | 3.6k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | today |
| 370 | Practical guidance for training MoE VLMs in Megatron Bridge. | NVIDIA/ | 3.6k | — | ~1.3k | Automated safety check: Pass | Apache-2.0 | today |
| 371 | Operational guide for choosing and combining parallelism strategies in Megatron Bridge, including sizing rules, hardware topology mapping, and combined parallelism configuration. | NVIDIA/ | 3.6k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | today |
| 372 | Validate and use packed sequences and long-context training in Megatron-Bridge, including offline LLM packing, collate-time VLM packing, Energon online packing, and CP constraints. | NVIDIA/ | 3.6k | — | ~3.3k | Automated safety check: Pass | Apache-2.0 | today |
| 373 | Operational guide for enabling TP, DP, and PP communication overlap in Megatron-Bridge, including config knobs, code anchors, pitfalls, and verification. | NVIDIA/ | 3.6k | — | ~924 | Automated safety check: Pass | Apache-2.0 | today |
| 374 | Resiliency features in Megatron Bridge including fault tolerance, straggler detection, in-process restart, preemption, and re-run state machine. | NVIDIA/ | 3.6k | — | ~2.8k | Automated safety check: Pass | Apache-2.0 | today |
| 375 | A skill your agent uses when the user wants to set up, scale, validate, or harden NVIDIA physical AI infrastructure for synthetic data generation workflows across local MicroK8s or Azure AKS… | NVIDIA/ | 3.6k | — | ~2.8k | Automated safety check: Notes | Apache-2.0 | today |
| 376 | Kubernetes execution platform — submits TAO container jobs as k8s Jobs with NVIDIA GPU scheduling; single-pod for one node, Indexed Jobs for multi-node distributed training. | NVIDIA/ | 3.6k | — | ~4.9k | Automated safety check: Warn | Apache-2.0 | today |
| 377 | Expert cuTile programming assistant. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~5k | Automated safety check: Pass | Apache-2.0 | today |
| 378 | Test system for Megatron-LM. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~1.8k | Automated safety check: Pass | Apache-2.0 | today |
| 379 | Route open-ended NVFLARE advice and only conversion requests whose preliminary source inspection reports unresolved or conflicting ownership; never load this skill merely to inspect a concrete… | NVIDIA/ | 3.6k | — | ~747 | Automated safety check: Pass | Apache-2.0 | today |
| 380 | Mod or remaster a game with RTX Remix - open and edit projects, swap textures and models. | NVIDIA/ | 3.6k | — | ~2.2k | Automated safety check: Pass | Apache-2.0 | today |
| 381 | Guide for onboarding new model architectures into NeMo AutoModel, including architecture discovery, implementation patterns, registration, and validation. | NVIDIA/ | 3.6k | — | ~5.7k | Automated safety check: Pass | Apache-2.0 | today |
| 382 | Documentation conventions for NeMo-RL. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~357 | Automated safety check: Pass | Apache-2.0 | today |
| 383 | One-time session setup and orchestration map for the TAO skill bank. | NVIDIA/ | 3.6k | — | ~1.8k | Automated safety check: Warn | Apache-2.0 | today |
| 384 | Linting and formatting for Megatron-LM. An agent skill from NVIDIA/skills. | NVIDIA/ | 3.6k | — | ~406 | Automated safety check: Pass | Apache-2.0 | today |