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

Download the skill as a ZIP:
https://mp-staging.autogineer.com/agent-skills/microsoft/azure-compute/download

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.

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

Files

ATTRIBUTION.mdAdded by AutoGineer971 B
LICENSELicence file added by AutoGineer1.1 KiB
SKILL.md2.6 KiB
references/retail-prices-api.md6.3 KiB
references/vm-families.md5.8 KiB
references/vm-quotas.md4.1 KiB
references/vmss-guide.md6.2 KiB
workflows/capacity-reservation/capacity-reservation.md7.8 KiB
workflows/capacity-reservation/references/association-disassociation.md3.8 KiB
workflows/capacity-reservation/references/capacity-reservation-overview.md6.0 KiB
workflows/essential-machine-management/essential-machine-management.md5.0 KiB
workflows/essential-machine-management/references/emm-enable-flow-portal-guidance.md3.1 KiB
workflows/essential-machine-management/references/emm-enable-flow.md9.2 KiB
workflows/essential-machine-management/references/emm-overview.md2.4 KiB
workflows/essential-machine-management/references/emm-prerequisites.md3.5 KiB
workflows/vm-creator/examples/bicep/README.md1.6 KiB
workflows/vm-creator/examples/bicep/main.bicep3.8 KiB
workflows/vm-creator/examples/terraform/README.md2.5 KiB
workflows/vm-creator/examples/terraform/main.tf3.2 KiB
workflows/vm-creator/examples/terraform/outputs.tf135 B
workflows/vm-creator/examples/terraform/variables.tf1010 B
workflows/vm-creator/references/delivery-options/github-pr.md3.2 KiB
workflows/vm-creator/references/delivery-options/index.md2.3 KiB
workflows/vm-creator/references/delivery-options/print.md474 B
workflows/vm-creator/references/delivery-options/save-local.md2.0 KiB
workflows/vm-creator/references/depth-probe/beginner.md1.2 KiB
workflows/vm-creator/references/depth-probe/cost-deep.md1.1 KiB
workflows/vm-creator/references/depth-probe/index.md3.0 KiB
workflows/vm-creator/references/depth-probe/networking-deep.md1.6 KiB
workflows/vm-creator/references/depth-probe/security-deep.md1.2 KiB
workflows/vm-creator/references/depth-probe/spec-deep.md1.3 KiB
workflows/vm-creator/references/mcp-tools.md2.3 KiB
workflows/vm-creator/references/output-adapters/az-cli.md1.9 KiB
workflows/vm-creator/references/output-adapters/bicep.md1.7 KiB
workflows/vm-creator/references/output-adapters/index.md3.0 KiB
workflows/vm-creator/references/output-adapters/mcp-apply.md2.6 KiB
workflows/vm-creator/references/output-adapters/terraform.md1.5 KiB
workflows/vm-creator/references/plan-card.md3.9 KiB
workflows/vm-creator/references/validation-gates.md2.2 KiB
workflows/vm-creator/vm-creator.md7.5 KiB
workflows/vm-recommender/references/handoff-to-creator.md1.6 KiB
workflows/vm-recommender/references/web-fetch-policy.md1.6 KiB
workflows/vm-recommender/vm-recommender.md6.4 KiB

workflows/vm-creator/references/delivery-options/index.md

Delivery Options

After the Plan Card is approved (Step 5) and the output format is chosen (Step 6), the workflow has a generated artifact. Before printing it into the chat, ask one more question — where should it go?

Mode	When the user wants this	File
A. Print in chat	Quick one-off, copy-paste, just learning	print.md
B. Save to local folder	Wants files on disk, will commit/run later	save-local.md
C. Sync to a GitHub repo	Has an infra repo, wants the change as a PR	github-pr.md

Skip the question for Adapter 4 (Apply via MCP). Delivery is moot — the resources get created in Azure directly.

Asking

"Where should I drop this {format} artifact?" 1. Print in the chat (default for quick / one-off) 2. Save to a local folder — I'll suggest a path based on your current workspace 3. Sync to a GitHub repo as a new branch + PR

If the user already implied a target ("save it to my infra repo" / "open a PR" / "just print it"), skip the question and use that mode.

Re-emitting / changing delivery mid-flow

After delivery, the Plan Card is cached. The user can say:

User says	Action
"also save it locally"	Re-run Mode B with the same artifact
"open a PR instead"	Re-run Mode C
"give me terraform now too"	Re-render that adapter, then re-ask delivery
"delete that file you wrote"	`rm` the path that was written

Never re-ask Plan Card questions when only the delivery target is changing.

Safety checks (B and C)

Check	Why
Don't overwrite without showing the diff and getting explicit yes	User may have manual edits
Scrub `adminPassword` from generated files → replace with `${VM_ADMIN_PASSWORD}` env var	Repos leak passwords
Never push directly to `main` / `master` / default branch — feature branch + PR only	Auditability and review
Never `git push --force` (use `--force-with-lease` if a rewrite is truly needed)	Catastrophic on shared branches
Emit a parameter placeholder for SSH keys, not the literal key contents	Keys committed to git stay there forever
If the repo has `CODEOWNERS` for the path, mention who'll be auto-tagged	User shouldn't be surprised by review routing

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

2026-11-08

Also distributed in

microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

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