Agent skill · nvidia
paidf-orchestration-setup
Audit, prepare, and deploy PAIDF Orchestration on a Kubernetes GPU cluster - single-GPU H100/L40S hosts, managed Kubernetes, kubeadm, and similar. Select for requests to set up, install, deploy, configure, or check a PAIDF Orchestration environment; run a workflow on a new or unverified GPU host; connect via kubeconfig; validate GPU compute; deploy the Airflow controller; or choose external versus in-cluster model services. A plain SSH host is not a supported backend.
What it needs
About 8k tokens when loaded.
What this skill does
PAIDF Orchestration Environment Setup Prepare a Kubernetes GPU environment for PAIDF Orchestration without assuming a cloud provider. Treat Kubernetes—not the host vendor—as the integration contract. Safety boundary Start with a read-only audit. Before any prepare, Helm install, Airflow connection change, or remote mutation, summarize the exact changes and obtain user approval. Never print kubeconfig, NGC keys, Hugging Face tokens, AWS secrets, or Kubernetes Secret bodies. Select two independent axes 1. Select controller placement: use an existing controller, or deploy Airflow into the current Kubernetes cluster. 2. Select model-service placement separately: use external VLM/LLM/image-edit endpoints, or deploy those services in-cluster. Never infer one choice from the other. 3. Prefer external endpoints on a one-GPU H100 node. The controller and augmentation worker may still run in that node's cluster. 4. Reject a Docker-only or SSH-only host until a supported Kubernetes distribution and NVIDIA device plugin expose nvidia.com/gpu. Read topologies.md before changing infrastructure. Audit the compute cluster The cluster is reached only through a kubeconfig the user supplies. It carries a cluster address and admin credentials, so it is never part of the repository. Resolve it in this order: 1. Use $KUBECONFIG if it is already set in the environment. 2. Otherwise ask the user for the path and export it. Never guess a path, assume a repository-relative location, or fall back to ~/.kube/config. If the path the user names does not exist, say so and ask again. Run locally when the agent already has the kubeconfig (remotek8s.py audit has no --kubeconfig flag; pass it via the env var): Alternatively, pass it inline through --kubectl-command: Run through SSH when Kubernetes tooling exists only on the remote host: remotek8s.py is bundled with this skill — run it from the skill directory, not the repository scripts/ directory. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills nvidia/paidf-orchestration-setup