azure-compute
PopularAzure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, can't connect / RDP / SSH, refused, black screen, reset password, reach VM, port 3389, NSG, security, Linux, troubleshoot, troubleshooting, connectivity, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.
"Azure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, can't connect / RDP / SSH, refused, black screen, reset password, reach VM, port 3389, NSG, security, Linux, troubleshoot, troubleshooting, connectivity, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota."
Azure Compute Skill
Routes Azure VM and Virtual Machine Scale Set (VMSS) requests to the right workflow.
When to Use This Skill
- User wants to recommend, compare, or price a VM or VMSS
- User wants to create, provision, or deploy a VM or VMSS
- User can't connect to a VM (RDP / SSH / port refused / black screen / password reset)
- User asks about Capacity Reservation Groups (CRG) — reserve, guarantee capacity, pre-provision
- User asks about Essential Machine Management (EMM) — machine enrollment, monitor
Disambiguate with azure-prepare: if the user wants to deploy an application (Docker service, web app, API, serverless workload), route to azure-prepare. vm-creator is for bare VM/VMSS infrastructure only.
Routing
Azure compute intent?
├── Recommend / compare / price a VM or VMSS → VM Recommender
├── Create / provision / deploy a VM or VMSS → VM Creator
├── Can't connect / RDP / SSH / port refused → VM Troubleshooter
├── Reserve / guarantee capacity (CRG) → Capacity Reservation
├── Machine enrollment / Essential Machine Management → Essential Machine Management
└── Unclear → Ask which of the above
Routing rule: read the matched workflow file before any reference file. The workflow owns the step-by-step guidance; references are looked up on demand.
Workflows
| Workflow | File | Use when |
|---|---|---|
| VM Recommender | vm-recommender.md | User asks which VM/VMSS to choose, wants pricing, or wants to compare options |
| VM Creator | vm-creator.md | User wants to provision a bare VM or VMSS (not an app deployment) |
| VM Troubleshooter | vm-troubleshooter.md | User can't connect, RDP/SSH refused, black screen, needs password reset |
| Capacity Reservation | capacity-reservation.md | User needs to reserve / guarantee VM capacity (CRG create / associate / disassociate) |
| Essential Machine Management | essential-machine-management.md | User asks about EMM / machine enrollment / monitor |
You Might Also Like
Related Skills
hyperframes-cli
HyperFrames CLI dev loop. Use when running npx hyperframes init, add, catalog, capture, lint, validate, inspect, layout, snapshot, preview, play, render, publish, lambda, doctor, browser, info, upgrade, skills, compositions, docs, benchmark, telemetry, transcribe, tts, or remove-background, or when troubleshooting the HyperFrames build/render environment. Entry point for AWS Lambda cloud rendering (`hyperframes lambda deploy / render / progress / destroy / policies`).
heygen-com
vercel-cli-with-tokens
Deploy and manage projects on Vercel using token-based authentication. Use when working with Vercel CLI using access tokens rather than interactive login — e.g. "deploy to vercel", "set up vercel", "add environment variables to vercel".
vercel-labs
azure-reliability
Assess and improve the reliability posture of PaaS Applications (Azure Functions and Azure App Service). Scans deployed resources for zone redundancy, ZRS storage, health probes, and multi-region failover. Presents a feature-pivoted checklist, then drives staged remediation (CLI or IaC patches) end-to-end with user confirmation. WHEN: \"assess reliability\", \"check reliability\", \"zone redundant\", \"multi-region failover\", \"high availability\", \"disaster recovery\", \"single points of failure\", \"reliability posture\", \"resiliency\".
microsoftazure-kubernetes
Plan, create, and configure production-ready Azure Kubernetes Service (AKS) clusters. Covers Day-0 checklist, SKU selection (Automatic vs Standard), networking options (private API server, Azure CNI Overlay, egress configuration), security, and operations (autoscaling, upgrade strategy, cost analysis). WHEN: create AKS environment, provision AKS, enable AKS observability, design AKS networking, choose AKS SKU, secure AKS, optimize AKS, AKS spot nodes, AKS cluster-autoscaler, rightsize AKS pod, pod rightsizing, over-provisioned AKS pod, pod resource requests and limits, Vertical Pod Autoscaler, VPA recommendations.
microsoftairunway-aks-setup
Set up AI Runway on AKS — from bare cluster to running model. Covers cluster verification, controller install, GPU assessment, provider setup, and first deployment. WHEN: \"setup AI Runway\", \"onboard AKS cluster\", \"install AI Runway\", \"airunway setup\", \"deploy model to AKS\", \"GPU inference on AKS\", \"KAITO setup on AKS\", \"run LLM on AKS\", \"vLLM on AKS\", \"set up model serving on AKS\", \"AI Runway controller\".
microsoftdeploy-model
Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).
microsoft