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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.

Use this Skill: https://skilld.dev/gh/microsoft/github-copilot-for-azure/azure-compute

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workflowsvm-creatorreferencesdepth-probeindex.md

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Depth Probe — Meet the User Where They Are

The VM Creator adapts its questioning to the user's expertise and intent. A beginner asking for a "dev VM" should not get peppered with networking and egress questions. An advanced networking engineer specifying "VMSS behind App Gateway with private endpoints" should not be asked whether they want a public IP.

Philosophy

  1. Never ask a question whose answer can be inferred or safely defaulted.
  2. Batch silent inferences into a Plan Card. Defaulted decisions should be visible and editable.
  3. Defaults ladder. When you must ask, prefer [recommended default] / [show alternatives] / [I have specifics].
  4. Branching is signal-driven, not flag-driven. Reclassify any time the user volunteers a deep signal.

Classification — read the initial request

Score each signal that appears in the user's first 1-2 messages. The highest-scoring branch wins; a user can be in multiple branches.

Signal phrase / keyword Branch
"VNet", "subnet", "NSG", "egress", "private endpoint", "App Gateway", "accelerated networking", "service tag", "UDR", "IPv6", "DNS", "Bastion" networking-deep
"vCPUs", "GPU", "memory", "family", "D-series", "N-series", "ephemeral OS disk", "proximity placement", "AMD", "Intel", "generation", "SR-IOV", "trusted launch" spec-deep
"spot", "reserved", "savings plan", "hybrid benefit", "autoscale floor/ceiling", "$", "budget", "cheapest", "cost-optimize" cost-deep
"managed identity", "Entra", "RBAC", "Key Vault", "JIT", "encryption at host", "CMK", "confidential", "compliance", "FedRAMP", "HIPAA" security-deep
"dev", "sandbox", "quick", "test out", "play with", "just need", "simple", or nothing specific beginner

Tiebreak: prefer the branch that affects the most expensive defaults: Networking > Security > Spec > Cost > Beginner. Networking mistakes are the hardest to undo post-deployment.

Cross-branch follow-ups (ask once, after primary branch)

Question When to ask
"Tags? (env, owner, cost-center)" Always — but accept "none" without follow-up
"Resource group: existing or new?" Always — propose <vm-name>-rg if new
"Number of instances?" Only for VMSS
"Orchestration mode (Flexible/Uniform)?" Only for VMSS — default Flexible

Reclassification mid-flow

If the user volunteers a deep signal at any step ("oh wait, I also need a NAT Gateway"), jump into that branch's questions for that topic. Never restart the whole flow — append the new questions and update the Plan Card.

Anti-patterns

  • ❌ Asking "what OS?" when the user said "Ubuntu sandbox"
  • ❌ Asking about spot pricing for a Windows production VM
  • ❌ Asking 8 networking questions before showing a Plan Card
  • ❌ Defaulting to public IP open to * without flagging it in the Plan Card
  • ❌ Burying the cost estimate at the bottom — put it on the Plan Card top row

Source: SKILL.md on GitHub

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    This skill provides comprehensive workflows for managing Azure compute resources, including VM creation, recommendations, and capacity management. It incorporates solid security practices like secret scrubbing and restricted network rules, with minor considerations related to external data ingestion.

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    Risk: MEDIUM · 1 issue

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    Score: 93/100 · 2 sections analyzed

Signed by skilld at 9c4c115. This ties the file your Agent reads to that commit on GitHub. It does not review the instructions.

Last checked against GitHub yesterday.

Activeupdated 2 months ago
metadata
{
  "author": "Microsoft",
  "version": "0.0.0-placeholder"
}
  • Infrastructure
  • azure
  • vm
  • virtual-machines
  • vmss
  • provisioning
  • troubleshooting
  • capacity-reservation
  • pricing

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Routes Azure VM and Virtual Machine Scale Set requests to five specialized workflows: VM recommendation and pricing, VM creation and provisioning, troubleshooting connectivity issues, capacity reservation, and machine enrollment. Use this skill when a user needs to size/compare VMs, deploy bare infrastructure, fix RDP/SSH access, or manage capacity reservations on Azure.

Generated from the current SKILL.md.

Does this skill handle application deployments like Docker or web apps?
No. This skill routes bare VM and VMSS infrastructure requests only. For deploying applications (Docker services, web apps, APIs, serverless workloads), use the azure-prepare skill instead.
What VM connectivity issues does this skill cover?
It covers RDP/SSH connection failures, port refused errors, black screen issues, and password resets. Use the VM Troubleshooter workflow when a user can't connect to an existing VM.
Can this skill help me choose the right VM size and pricing?
Yes. The VM Recommender workflow recommends VM sizes, compares options, and estimates costs based on workload requirements (web, backend, GPU, HPC, dev/test, etc.).
Does this skill support Capacity Reservation Groups?
Yes. It includes a dedicated workflow for creating, associating, and disassociating Capacity Reservation Groups to guarantee and pre-provision VM capacity.

Generated from the current SKILL.md. These answers refresh after source changes.