azure-compute
π―SkillA helper that sends your Azure virtual machine requests to the right step-by-step guide. It helps you choose, price, create and reserve cloud servers in Azure.
Installation
npx skills add microsoft/azure-skills --skill azure-computeRun it in a terminal; it asks which AI coding tools to install it for (Claude Code, Codex, Cursor and more).
Uses skills.sh Β· Node.js 22.20+
After installing
Ask for related work and the agent uses it on its own, or call it yourself.
/azure-computeInstall by hand
Copy the whole skill folder from GitHub to the place below. Copying only SKILL.md can leave out files the skill uses.
Open the skill folder β- This project
.claude/skills/azure-compute/ - All projects
~/.claude/skills/azure-compute/
These paths are for Claude Code. For other tools, the command above puts it in the right place.
What this skill does
Overview
azure-compute handles requests about Azure virtual machines (VMs, cloud servers you rent) and VM Scale Sets (VMSS, groups of VMs that can grow or shrink). It first works out what you want. Then it opens the matching workflow file and loads only the reference files that workflow needs.
Key Features
- Get help choosing a VM size, comparing prices, and deciding whether to use autoscaling, which adds or removes servers automatically.
- Create a bare VM or VMSS when you need only the server, not an app on it.
- Reserve VM capacity ahead of time with Capacity Reservation Groups (CRG).
- Enroll and monitor machines with Essential Machine Management (EMM).
- When you create a VM, the agent uses tools such as
compute_vm_list-skusandcompute_vm_check-quotato list VM sizes and check your quota.
Who is this for?
It suits engineers who set up Azure servers for websites, backends, GPU or machine learning work, or dev/test. If you want to deploy an app such as a web app or API, the skill points you to azure-prepare instead.
Summarized by AI from this skill's SKILL.md. Suggest a better one
SKILL.md
View on GitHub βAzure 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, 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 β 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 asks about Capacity Reservation Groups (CRG) β reserve, guarantee capacity, pre-provision
- User asks about Essential Machine Management (EMM) β 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
Mandatory workflow-first routing: never route directly to references/* files. First classify the user intent below, open the matched workflow file, then load only the reference files that workflow requests. Reference files are supporting material, not entry points. If the intent is unclear, ask a clarifying question to disambiguate between the workflows.
| Workflow | File | Use when |
|---|---|---|
| VM Recommender | vm-recommender.md | User asks which VM/VMSS to choose, whether to use VMSS/autoscaling, wants pricing, or wants to compare options |
| VM Creator | vm-creator.md | User wants to create, provision, or deploy a bare VM or VMSS (not an app deployment) |
| 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 |
More from this repository10
Helps you build, deploy, test, and manage AI agents and models on Microsoft Foundry, Microsoft's Azure service for AI. It guides the AI through each task with fixed steps.
Helps you find and fix problems in apps running on Azure, such as crashes, slow responses, or connection failures. It checks things in a set order and can work only from logs you provide.
azure-prepare gets a new or existing app ready to deploy to Azure with azd, Microsoft's command-line tool for Azure. It first writes a plan for your approval, then creates the setup files.
azure-deploy puts your app on Azure after the azure-prepare and azure-validate skills have prepared and checked it. It runs the deployment, recovers from errors, and gives you the live web addresses.
azure-validate checks your Azure app before you deploy it, so you can catch setup and permission problems early. It runs after azure-prepare and before azure-deploy.
azure-resource-lookup finds and lists your Azure resources, such as web apps, virtual machines, and storage accounts, across your subscriptions. It only reads data and never changes anything.
azure-resource-visualizer draws a diagram of an Azure resource group that shows how each resource connects to the others. It saves the diagram and notes in a markdown file.
Lets Claude search and summarize large amounts of logs and app data stored in Azure Data Explorer. You ask what you want to know, and it writes and runs the queries for you.
Helps you send all requests to your AI models and tools through Azure API Management, so you can control cost, block harmful content and limit traffic. It includes Azure command-line steps for setup and testing.
Helps you find and fix errors in apps that send and receive messages through Azure Event Hubs or Service Bus. It checks service health and Microsoft docs to suggest a fix.