Azure Enterprise Infra Planner logo

Azure Enterprise Infra Planner

OrganizationPopular
microsoft
azure-enterprise-infra-planner

Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.

Overview

Publishermicrosoft
Repositoryazure-skills
Skill nameazure-enterprise-infra-planner
Stars
1.5K
Forks
246
Bundled files
38
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 38 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by microsoft on GitHub. Read the source before you install it.

Installation

Install the Azure Enterprise Infra Planner AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/microsoft/azure-skills.git /tmp/azure-skills
mkdir -p .claude/skills
cp -r /tmp/azure-skills/skills/azure-enterprise-infra-planner .claude/skills/azure-enterprise-infra-planner
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Azure Enterprise Infra Planner in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Azure Enterprise Infra Planner on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Azure Enterprise Infra Planner is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Azure Enterprise Infra Planner

When to Use This Skill

Activate this skill when user wants to:

  • Plan enterprise Azure infrastructure from a workload or architecture description
  • Architect a landing zone, hub-spoke network, or multi-region topology
  • Design networking infrastructure: VNets, subnets, firewalls, private endpoints, VPN gateways
  • Plan identity, RBAC, and compliance-driven infrastructure
  • Generate Bicep or Terraform for subscription-scope or multi-resource-group deployments
  • Plan disaster recovery, failover, or cross-region high-availability topologies

Quick Reference

PropertyDetails
MCP toolsinsights_get, get_azure_bestpractices_get, wellarchitectedframework_serviceguide_get, microsoft_docs_fetch, microsoft_docs_search, bicepschema_get
CLI commandsaz deployment group create, az bicep build, az resource list, terraform init, terraform plan, terraform validate, terraform apply, checkov
Output schemaschema.md
Key referencesworkflow.md, waf-checklist.md, resources/, constraints/

Workflow (Start Here)

Follow the step-by-step instructions in workflow.md to execute the 7 phases of infrastructure planning and provisioning.

Architecture

The skill runs a 7-phase, gated pipeline. Input is triaged into one of two flows:

  • Greenfield — only new requirements; run the phases straight through.
  • Referenced (brownfield) — the user supplies something that already exists (a live resource / resource group / subscription, IaC or an infra plan, or a requirements doc). The same phases run, plus referenced-workload.md: existing resources are inventoried and referenced (never recreated), the new workload is wired into them, and Phase 7 deploys additively (incremental only — never modifying or destroying the referenced resources).

Every phase advances only after its gate passes. Phase 5 requires explicit user approval; Phase 6 is a hardened, self-verifying gate — the generated IaC must be secure-by-default, pass local validation (az bicep build / terraform validate) with zero errors, pass a checkov security scan with no unresolved high/critical findings, and the skill must show the command output and emit a completion self-check before advancing; Phase 7 requires an explicit, risk-acknowledged deploy confirmation.

mermaid
flowchart TD
    IN([Input]) --> TRIAGE{Existing infra<br/>referenced?}
    TRIAGE -- "No (greenfield)" --> P1
    TRIAGE -- "Yes (referenced)" --> RW[/referenced-workload.md:<br/>inventory + assign roles<br/>reference, never recreate/]
    RW --> P1

    subgraph PIPE [7-phase gated pipeline]
        direction TB
        P1[Phase 1 · Extract insights] --> P2[Phase 2 · Research best practices]
        P2 --> P3[Phase 3 · Research resources]
        P3 --> P4[Phase 4 · Generate plan]
        P4 --> P5{Phase 5 · Verify<br/>user approves?}
        P5 -- "no" --> P4
        P5 -- "approved" --> P6[Phase 6 · Generate IaC]
        P6 --> VAL{Validate<br/>az bicep build /<br/>terraform validate}
        VAL -- "errors" --> P6
        VAL -- "clean" --> P7{Phase 7 · Deploy<br/>risk-ack confirm?}
    end

    P7 -- "greenfield" --> DEP[az deployment / terraform apply]
    P7 -- "referenced" --> DEPADD[Additive deploy · incremental only<br/>what-if preview · no destroy of<br/>referenced resources]
    DEP --> OUT([Deployed])
    DEPADD --> OUT

    classDef gate fill:#fff3cd,stroke:#d39e00,color:#000;
    classDef ref fill:#e2f0d9,stroke:#548235,color:#000;
    class P5,VAL,P7,TRIAGE gate;
    class RW,DEPADD ref;

Artifacts (written under <project-root>/): .azure/insights.json (Phase 1), .azure/infrastructure-plan.json (Phase 4, status draftapproveddeployed), and infra/main.bicep + infra/modules/* or infra/main.tf + infra/modules/** (Phase 6).

MCP Tools

ToolPurpose
insights_getRetrieve insights about the user's existing Azure environment to guide planning decisions
get_azure_bestpractices_getAzure best practices for code generation, operations, and deployment
wellarchitectedframework_serviceguide_getWAF service guide for a specific Azure service
microsoft_docs_searchSearch Microsoft Learn for relevant documentation chunks
microsoft_docs_fetchFetch full content of a Microsoft Learn page by URL
bicepschema_getBicep schema definition for any Azure resource type (latest API version)

Error Handling

ErrorCauseFix
MCP tool error or not availableTool call timeout, connection error, or tool doesn't existRetry once; fall back to reference files and notify user if unresolved
Plan approval missingmeta.status is not approvedStop and prompt user for approval before IaC generation or deployment
IaC validation failureaz bicep build or terraform validate returns errorsFix the generated code and re-validate; notify user if unresolved
Pairing constraint violationIncompatible SKU or resource combinationFix in plan before proceeding to IaC generation
Infra plan or IaC files not foundFiles written to wrong location or not createdVerify files exist at <project-root>/.azure/ and <project-root>/infra/; if missing, re-create the files by following workflow.md exactly

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Azure Enterprise Infra Planner AI skill do?

Architect and provision enterprise Azure infrastructure from workload descriptions. For cloud architects and platform engineers planning networking, identity, security, compliance, and multi-resource topologies with WAF alignment. Generates Bicep or Terraform directly (no azd). WHEN: 'plan Azure infrastructure', 'architect Azure landing zone', 'design hub-spoke network', 'plan multi-region DR topology', 'set up VNets firewalls and private endpoints', 'subscription-scope Bicep deployment', 'Azure Backup for VM workloads'. PREFER azure-prepare FOR app-centric workflows.

Why use Azure Enterprise Infra Planner on TypingMind?

Because you install it once and use it with any model. Azure Enterprise Infra Planner is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Azure Enterprise Infra Planner in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/microsoft/azure-skills/tree/main/skills/azure-enterprise-infra-planner. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Azure Enterprise Infra Planner?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Azure Enterprise Infra Planner?

As many as you like. As long as a model supports skills, you can use Azure Enterprise Infra Planner with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Azure Enterprise Infra Planner AI skill free?

Yes. It is published on GitHub by microsoft under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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