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",[],[707,708,709,710],{"slug":32,"name":33},{"slug":29,"name":30},{"slug":5,"name":6},{"slug":233,"name":711},"Security","2026-07-14T05:36:09.251774",{"name":714,"fullName":715,"repoUrl":716,"skillCount":392,"stars":717,"forks":208,"description":718,"topics":719,"topTags":720,"topTagCount":192,"lastUpdatedAt":725},"holodeck","NVIDIA\u002Fholodeck","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fholodeck",31,"Holodeck is a project to create test environments optimised for GPU projects.",[],[721,722,723,724],{"slug":243,"name":244},{"slug":446,"name":447},{"slug":5,"name":6},{"slug":116,"name":117},"2026-07-14T05:36:29.548299",{"name":727,"fullName":728,"repoUrl":729,"skillCount":392,"stars":730,"forks":731,"description":732,"topics":733,"topTags":734,"topTagCount":192,"lastUpdatedAt":741},"infra-controller","NVIDIA\u002Finfra-controller","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Finfra-controller",226,150,"NVIDIA Infra Controller - Hardware Lifecycle Management and multitenant networking",[],[735,736,737,738],{"slug":159,"name":160},{"slug":29,"name":30},{"slug":5,"name":6},{"slug":739,"name":740},"rest-api","REST API","2026-07-14T05:32:52.235912",{"name":743,"fullName":744,"repoUrl":745,"skillCount":392,"stars":190,"forks":478,"description":746,"topics":747,"topTags":748,"topTagCount":192,"lastUpdatedAt":753},"NeMo-Fabric","NVIDIA\u002FNeMo-Fabric","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FNeMo-Fabric","Project NVIDIA NeMo Fabric",[],[749,750,751,752],{"slug":88,"name":89},{"slug":29,"name":30},{"slug":5,"name":6},{"slug":116,"name":117},"2026-07-23T06:06:22.954737",{"name":755,"fullName":756,"repoUrl":757,"skillCount":392,"stars":758,"forks":759,"description":760,"topics":761,"topTags":766,"topTagCount":478,"lastUpdatedAt":774},"NemoClaw","NVIDIA\u002FNemoClaw","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FNemoClaw",21777,2940,"Run agents like Hermes, LangChain Deep Agents, and OpenClaw more securely inside NVIDIA OpenShell with managed inference",[762,763,5,228,764,627,765],"ai-agents","hermes","openshell","typescript",[767,768,771],{"slug":85,"name":86},{"slug":769,"name":770},"mcp","MCP",{"slug":772,"name":773},"search","Search","2026-07-20T06:00:01.461044",{"name":776,"fullName":777,"repoUrl":778,"skillCount":392,"stars":779,"forks":780,"description":781,"topics":782,"topTags":783,"topTagCount":478,"lastUpdatedAt":789},"nvidia-kaggle","NVIDIA\u002Fnvidia-kaggle","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fnvidia-kaggle",253,22,"NVIDIA Kaggle Plugin gives agents end-to-end Kaggle competition workflows through a single skill, nvidia-kaggle-skill. It can gather competition context, study public writeups and notebooks, reproduce kernels locally, submit to competitions, and manage Ka",[],[784,785,786],{"slug":41,"name":42},{"slug":5,"name":6},{"slug":787,"name":788},"research","Research","2026-07-14T05:36:16.524177",{"name":791,"fullName":792,"repoUrl":793,"skillCount":392,"stars":794,"forks":795,"description":612,"topics":796,"topTags":797,"topTagCount":192,"lastUpdatedAt":802},"OpenShell-Community","NVIDIA\u002FOpenShell-Community","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FOpenShell-Community",172,63,[],[798,799,800,801],{"slug":243,"name":244},{"slug":29,"name":30},{"slug":107,"name":108},{"slug":739,"name":740},"2026-07-14T05:36:26.866398",{"name":804,"fullName":805,"repoUrl":806,"skillCount":392,"stars":392,"forks":392,"description":807,"topics":808,"topTags":809,"topTagCount":192,"lastUpdatedAt":816},"paidf-augmentation","NVIDIA\u002Fpaidf-augmentation","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fpaidf-augmentation","Containerized generative-AI pipeline that transforms video, image, and text inputs into large, diverse, physically grounded datasets for model training and evaluation",[],[810,813,814,815],{"slug":811,"name":812},"data-engineering","Data Engineering",{"slug":41,"name":42},{"slug":5,"name":6},{"slug":38,"name":39},"2026-07-14T05:36:30.828379",{"name":818,"fullName":819,"repoUrl":820,"skillCount":392,"stars":592,"forks":392,"description":821,"topics":822,"topTags":823,"topTagCount":192,"lastUpdatedAt":828},"paidf-auto-labeling","NVIDIA\u002Fpaidf-auto-labeling","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fpaidf-auto-labeling","Auto-labeling pipeline that turns raw video and images into fine-tuning-ready scenes via super-resolution, detection and tracking, VLM scene understanding, and question generation",[],[824,825,826,827],{"slug":53,"name":54},{"slug":269,"name":270},{"slug":559,"name":560},{"slug":5,"name":6},"2026-07-14T05:32:21.766434",{"name":830,"fullName":831,"repoUrl":832,"skillCount":392,"stars":391,"forks":392,"description":833,"topics":834,"topTags":835,"topTagCount":192,"lastUpdatedAt":840},"paidf-simulation","NVIDIA\u002Fpaidf-simulation","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Fpaidf-simulation","Synthetic data generation engine using NVIDIA Isaac Sim and Omniverse Replicator to render photorealistic, fully labeled PCB inspection imagery, including golden and defect boards",[],[836,837,838,839],{"slug":811,"name":812},{"slug":559,"name":560},{"slug":5,"name":6},{"slug":38,"name":39},"2026-07-14T05:36:25.595046",{"name":842,"fullName":843,"repoUrl":844,"skillCount":392,"stars":845,"forks":846,"description":847,"topics":848,"topTags":849,"topTagCount":192,"lastUpdatedAt":856},"TileGym","NVIDIA\u002FTileGym","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002FTileGym",770,79,"Helpful kernel tutorials, examples and SKILLs for tile-based GPU programming",[],[850,851,852,853],{"slug":29,"name":30},{"slug":5,"name":6},{"slug":35,"name":36},{"slug":854,"name":855},"rust","Rust","2026-07-14T05:33:14.807388",{"name":858,"fullName":859,"repoUrl":860,"skillCount":392,"stars":861,"forks":862,"description":863,"topics":864,"topTags":867,"topTagCount":478,"lastUpdatedAt":871},"torch-harmonics","NVIDIA\u002Ftorch-harmonics","https:\u002F\u002Fgithub.com\u002FNVIDIA\u002Ftorch-harmonics",686,69,"Differentiable signal processing on the sphere for PyTorch",[41,273,865,866],"signal-processing","sphere",[868,869,870],{"slug":85,"name":86},{"slug":29,"name":30},{"slug":5,"name":6},"2026-07-14T05:32:03.82994",{"items":873,"total":478},[874,886,898],{"slug":875,"name":875,"fn":876,"description":877,"org":878,"tags":879,"stars":532,"repoUrl":531,"updatedAt":547},"osmo-admin","manage OSMO service configuration","Use only for offline\u002Flocal OSMO service-config admin requests involving explicit config roots or values files, or to ask for one when a file-specific config request omits it. Do not inspect the workspace to infer a root. Do not use for live workflow support, resource capacity, pod\u002Fnode diagnostics, or cluster operations, except live service-config paths that must be refused.\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":6},[880,882,883],{"name":206,"slug":205,"type":881},"tag",{"name":6,"slug":5,"type":881},{"name":884,"slug":885,"type":881},"Operations","operations",{"slug":887,"name":887,"fn":888,"description":889,"org":890,"tags":891,"stars":532,"repoUrl":531,"updatedAt":897},"osmo-deploy","deploy OSMO to Kubernetes clusters","How to deploy OSMO to a Kubernetes cluster on Azure (AKS), AWS (EKS), MicroK8s (single-node), or any kubectl-reachable cluster (BYO). Use this skill whenever the user asks to install, deploy, set up, or stand up OSMO; whenever they ask to provision an OSMO cluster; whenever they mention deploy-osmo-minimal.sh, deploy-k8s.sh, or \"OSMO helm install\"; whenever they ask to wire up workflow storage (MinIO \u002F Azure Blob \u002F S3); or whenever they ask to add a GPU pool to an OSMO cluster, install KAI scheduler, install the NVIDIA GPU Operator, or run the post-install smoke tests. Targets OSMO 6.3 (ConfigMap mode).\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":6},[892,893,894,895,896],{"name":541,"slug":540,"type":881},{"name":544,"slug":543,"type":881},{"name":33,"slug":32,"type":881},{"name":198,"slug":197,"type":881},{"name":6,"slug":5,"type":881},"2026-07-14T05:33:24.181591",{"slug":899,"name":899,"fn":900,"description":901,"org":902,"tags":903,"stars":532,"repoUrl":531,"updatedAt":911},"osmo-user","manage cloud robotics workflows with OSMO","Drive the OSMO CLI for cloud-robotics compute on behalf of an end user: check resources, submit\u002Fmonitor\u002Fdebug\u002Fexplain workflows, fetch logs and Grafana\u002FKubernetes links, inspect direct data storage, manage workflow apps, and set workflow credentials. Use whenever the user asks about OSMO pools, quota, GPUs, or nodes, or about submitting, listing, querying, monitoring, or troubleshooting workflows — including failed, PENDING, queued, stuck, or image-pull-blocked workflows, or when they ask to inspect or transfer direct storage URIs such as `s3:\u002F\u002F...`, even when they describe a workflow, cluster resource, or storage URI without saying \"OSMO\". Do not use for Kubernetes admin, server-side `osmo config` changes, OSMO install\u002Fdeploy, non-OSMO compute, or general NVIDIA hardware questions.\n",{"slug":5,"name":6,"logoUrl":7,"githubOrg":6},[904,905,908,909,910],{"name":244,"slug":243,"type":881},{"name":906,"slug":907,"type":881},"Grafana","grafana",{"name":198,"slug":197,"type":881},{"name":179,"slug":178,"type":881},{"name":6,"slug":5,"type":881},"2026-07-14T05:33:25.461692"]