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Azure Compute

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Tool integration
  • Cloud and DevOps
  • MIT
  • Medium risk

From the author

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, 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.
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

The Azure Compute skill acts as a primary router for infrastructure-level tasks within Azure. It directs user requests to specialized workflows for recommending, provisioning, and managing bare virtual machine infrastructure. It is designed to handle the lifecycle of VMs and VMSS, including capacity planning through Capacity Reservation Groups and machine monitoring via Essential Machine Management.

What it does

  • Routes requests to specific workflows for VM and VMSS provisioning.
  • Provides guidance on selecting VM families based on workload requirements.
  • Facilitates capacity reservation and guarantee for critical infrastructure.
  • Supports Essential Machine Management for enrollment and monitoring tasks.
  • Enables cost estimation and pricing comparisons for various VM SKUs.
  • Distinguishes between infrastructure deployment and application-level service deployment.

When to use it

  • When you need to provision or deploy bare virtual machines or scale sets.
  • When you require assistance in selecting the appropriate VM family for a specific workload.
  • When you need to reserve or guarantee capacity for your Azure compute resources.
  • When you are setting up or monitoring machines using Essential Machine Management.
  • When you need to compare pricing for different VM SKUs or regions.

Advantages

  • Centralized entry point for all Azure compute-related infrastructure tasks.
  • Prevents confusion between infrastructure provisioning and application deployment.
  • Provides structured paths for complex tasks like capacity reservation.
  • Ensures consistent use of specialized tools for quota and SKU management.

Usage examples

“I need to deploy a set of web servers. Which VM family should I use?”
The skill routes the request to the VM Recommender to analyze your workload and suggest the appropriate D-series or B-series VMs.
“How can I reserve capacity for my production database VMs?”
The skill initiates the Capacity Reservation workflow to guide you through creating and associating a Capacity Reservation Group.
“Provision a new Ubuntu VM for testing.”
The skill routes the request to the VM Creator workflow to handle the infrastructure deployment.
“How do I enroll my machines in Essential Machine Management?”
The skill directs you to the Essential Machine Management workflow for enrollment and monitoring instructions.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/microsoft/azure-compute/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip azure-compute.zip -d .agents/skills

Documentation by Microsoft

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) — 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

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.

WorkflowFileUse when
VM Recommendervm-recommender.mdUser asks which VM/VMSS to choose, whether to use VMSS/autoscaling, wants pricing, or wants to compare options
VM Creatorvm-creator.mdUser wants to create, provision, or deploy a bare VM or VMSS (not an app deployment)
Capacity Reservationcapacity-reservation.mdUser needs to reserve / guarantee VM capacity (CRG create / associate / disassociate)
Essential Machine Managementessential-machine-management.mdUser asks about EMM / machine enrollment / monitor

Files

workflows/vm-creator/references/plan-card.md

Plan Card

The Plan Card is the single source of truth for the create-flow. It renders every decision — explicit user answers and silent defaults — as a markdown table the user can read top-to-bottom and either approve or edit.

Rendering rules

  1. Cost + quota on the top half. The user must see both without scrolling.

  2. Source column is mandatory. Each row says where the value came from: user, default, inferred, or the MCP tool that produced it.

  3. Flag risky defaults with ⚠. Open NSG to *, public IP exposed, no managed identity, password auth on Windows — all get a marker so the user can edit.

  4. No invisible state. If you defaulted it, it goes in the card.

  5. Re-emit on every change. When the user edits a row, render the full card again — diffs in chat are easy to miss.

Schema

ColumnRequired?Notes
SettingyesHuman-readable label (Region, Size, OS disk)
ValueyesThe concrete value, in backticks if it's a literal
Sourceyesuser / default / inferred / <tool name>

Example — Linux dev VM in eastus

| Setting | Value | Source |
|---|---|---|
| Hosting model | Single VM | user |
| Name | `dev-vm-01` | default (`<purpose>-vm-<nn>`) |
| Region | `eastus` | user |
| Resource group | `dev-vm-01-rg` (new) | default |
| Image | `Ubuntu2404` | user |
| Size | `Standard_D2s_v5` (2 vCPU / 8 GB) | default |
| Auth | SSH key from `~/.ssh/id_rsa.pub` | inferred |
| VNet | new `dev-vm-01-vnet` (`10.0.0.0/16`) | default |
| Subnet | `default` (`10.0.0.0/24`) | default |
| NSG | SSH 22 from your public IP (`203.0.113.42`) | default — ⚠ change to `*` only if needed |
| Public IP | Standard, dynamic | default |
| OS disk | 30 GB Premium SSD | default |
| Boot diagnostics | Managed | default |
| Estimated cost | ~$0.096/hr (~$70/mo) | from `compute_vm_list-skus` |
| Quota | ✅ 4/100 vCPUs used in `standardDSv5Family` | from `compute_vm_check-quota` |

After rendering — single batched action picker

Render the Plan Card markdown inline in the chat first (so the user can read it), then ask one AskUserQuestion that combines approval + output format + delivery:

"Looks good? Pick how you want it delivered:"

  1. Save Bicep to ./infra/{vm-name}/ (Recommended for repos)

  2. Print az CLI in chat (Quick copy-paste)

  3. Save Terraform to ./infra/{vm-name}/

  4. Open GitHub PR with Bicep

  5. Apply live via Azure MCP (actually creates resources)

  6. Edit a row first (then re-render and re-ask)

This collapses what used to be 3 sequential popups (approve → output format → delivery) into 1.

Implementation: a single AskUserQuestion tool call with header: "Deliver", multiSelect: false, and 6 options (the most likely combinations above) — the user can also pick "Other" to type a custom answer like "give me both bicep and terraform".

If the user picks "Edit a row first": then ask which row, update, re-render the full Plan Card, and re-ask the same batched action picker. Do not splinter into multiple popups.

If the user already implied the answer in their original prompt ("save bicep to ./infra" / "open a PR" / "just print az CLI" / "apply it"): skip this prompt entirely and proceed straight to delivery.

Explicit-override fast path — skip the Plan Card table too. If the user combines an explicit deliverable ("give me the Bicep", "just print az CLI") with an explicit refusal of dialog ("no questions", "skip planning", "no plan", "just do it"): do not render the Plan Card markdown table. Instead emit a single-line preview of the high-signal decisions — e.g. "→ Deploying Standard_D2s_v5 in eastus, NSG = your public IP only on 22, est. ~$70/mo" — and follow it immediately with the requested artifact. End with a one-liner noting the full Plan Card is available on request if they want to edit rows. Step 4 validation gates still run.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Security

What our scanner noticed· Medium risk

  • References to credential files

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills · .github/plugins/azure-skills/skills/azure-compute · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Also distributed in
microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-compute.zip