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Azure Architecture Builder

OfficialFree

Design and deploy Azure infrastructure using natural language.

by github37.7k stars on github/awesome-copilot
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Updated Aug 10, 2026
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Free Β· Opens the source repo

What Azure Architecture Builder does

Azure Architecture Builder is a powerful tool that allows users to design Azure infrastructure using natural language commands. It can also analyze existing Azure resources to generate architecture diagrams, enabling users to visualize their current setups. The skill includes an embedded diagram engine, which means you don't need to install any additional packages; it operates directly from bundled Python scripts. This makes it ready to use immediately without requiring network access or complex setup processes.

The skill supports a variety of tasks, including creating new Azure architectures, analyzing current resources, and modifying existing setups. Users can generate Bicep templates for infrastructure as code (IaC) deployments, ensuring that their Azure resources are managed efficiently. The tool is designed for developers and designers who need to streamline their Azure infrastructure design and deployment processes, making it easier to create and manage complex architectures.

One of the key features of Azure Architecture Builder is its ability to detect the user's language and respond accordingly, ensuring a smooth user experience. The skill guides users through different phases of architecture design, from initial concept to deployment, while providing updates and progress notifications throughout the process. This structured approach helps users stay informed and engaged as they work on their Azure projects.

Overall, Azure Architecture Builder is ideal for those who want to simplify their Azure infrastructure management and deployment tasks. Whether you're a developer looking to create new solutions or a designer needing to visualize and modify existing architectures, this skill provides the tools necessary to achieve your goals effectively.

When to use it

Use this skill when you need to create new Azure architectures, analyze existing resources, or modify current setups using natural language commands.

When not to use it

This skill may not be suitable for users who prefer traditional coding methods or need to work with Azure services not covered by the tool.

What you can build with it

Create a New Azure Architecture

When you need to set up a new Azure infrastructure, simply use natural language commands to describe your requirements, and the skill will guide you through the design process.

Analyze Existing Azure Resources

If you want to visualize your current Azure setup, you can ask the skill to analyze your existing resources and generate corresponding architecture diagrams.

Modify Azure Infrastructure

When you identify issues like performance or cost concerns, use natural language to request modifications, and the skill will assist in refining your architecture.

How to install Azure Architecture Builder

View source

1. Install with the skills CLI

npx skills add github/awesome-copilot/azure-architecture-autopilot --agent claude-code

2. Or install it manually

Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.

Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs

Inside SKILL.md

Written by github

Azure Architecture Builder

A pipeline that designs Azure infrastructure using natural language, or analyzes existing resources to visualize architecture and proceed through modification and deployment.

The diagram engine is embedded within the skill (scripts/ folder). No pip install needed β€” it directly uses the bundled Python scripts to generate interactive HTML diagrams with 605+ official Azure icons. Ready to use immediately without network access or package installation.

Automatic User Language Detection

🚨 Detect the language of the user's first message and provide all subsequent responses in that language. This is the highest-priority principle.

  • If the user writes in Korean β†’ respond in Korean
  • If the user writes in English β†’ respond in English (ask_user, progress updates, reports, Bicep comments β€” all in English)
  • The instructions and examples in this document are written in English, and all user-facing output must match the user's language

⚠️ Do not copy examples from this document verbatim to the user. Use only the structure as reference, and adapt text to the user's language.

Tool Usage Guide (GHCP Environment)

FeatureTool NameNotes
Fetch URL contentweb_fetchFor MS Docs lookups, etc.
Web searchweb_searchURL discovery
Ask userask_userchoices must be a string array
Sub-agentstaskexplore/task/general-purpose
Shell command executionpowershellWindows PowerShell

All sub-agents (explore/task/general-purpose) cannot use web_fetch or web_search. Fact-checking that requires MS Docs lookups must be performed directly by the main agent.

External Tool Path Discovery

az, python, bicep, etc. are often not on PATH. Discover once before starting a Phase and cache the result. Do not re-discover every time.

⚠️ Do not use Get-Command python β€” risk of Windows Store alias. Direct filesystem discovery ($env:LOCALAPPDATA\Programs\Python) takes priority.

az CLI path:

$azCmd = $null
if (Get-Command az -ErrorAction SilentlyContinue) { $azCmd = 'az' }
if (-not $azCmd) {
  $azExe = Get-ChildItem -Path "$env:ProgramFiles\Microsoft SDKs\Azure\CLI2\wbin", "$env:LOCALAPPDATA\Programs\Azure CLI\wbin" -Filter "az.cmd" -ErrorAction SilentlyContinue | Select-Object -First 1 -ExpandProperty FullName
  if ($azExe) { $azCmd = $azExe }
}

Python path + embedded diagram engine: refer to the diagram generation section in references/phase1-advisor.md.

Progress Updates Required

Use blockquote + emoji + bold format:

> **⏳ [Action]** β€” [Reason]
> **βœ… [Complete]** β€” [Result]
> **⚠️ [Warning]** β€” [Details]
> **❌ [Failed]** β€” [Cause]

Parallel Preload Principle

While waiting for user input via ask_user, preload information needed for the next step in parallel.

ask_user QuestionPreload Simultaneously
Project name / scan scopeReference files, MS Docs, Python path discovery, diagram module path verification
Model/SKU selectionMS Docs for next question choices
Architecture confirmationaz account show/list, az group list
Subscription selectionaz group list

Path Branching β€” Automatically Determined by User Request

Path A: New Design (New Build)

Trigger: "create", "set up", "deploy", "build", etc.

Phase 1 (references/phase1-advisor.md) β€” Interactive architecture design + diagram
    ↓
Phase 2 (references/bicep-generator.md) β€” Bicep code generation
    ↓
Phase 3 (references/bicep-reviewer.md) β€” Code review + compilation verification
    ↓
Phase 4 (references/phase4-deployer.md) β€” validate β†’ what-if β†’ deploy

Path B: Existing Analysis + Modification (Analyze & Modify)

Trigger: "analyze", "current resources", "scan", "draw a diagram", "show my infrastructure", etc.

Phase 0 (references/phase0-scanner.md) β€” Existing resource scan + diagram
    ↓
Modification conversation β€” "What would you like to change here?" (natural language modification request β†’ follow-up questions)
    ↓
Phase 1 (references/phase1-advisor.md) β€” Confirm modifications + update diagram
    ↓
Phase 2~4 β€” Same as above

When Path Determination Is Ambiguous

Ask the user directly:

ask_user({
  question: "What would you like to do?",
  choices: [
    "Design a new Azure architecture (Recommended)",
    "Analyze + modify existing Azure resources"
  ]
})

Phase Transition Rules

  • Each Phase reads and follows the instructions in its corresponding references/*.md file
  • When transitioning between Phases, always inform the user about the next step
  • Do not skip Phases (especially the what-if between Phase 3 β†’ Phase 4)
  • 🚨 Required condition for Phase 1 β†’ Phase 2 transition: 01_arch_diagram_draft.html must have been generated using the embedded diagram engine and shown to the user. Do not proceed to Bicep generation without a diagram. Completing spec collection alone does not mean Phase 1 is done β€” Phase 1 includes diagram generation + user confirmation.
  • Modification request after deployment β†’ return to Phase 1, not Phase 0 (Delta Confirmation Rule)

Service Coverage & Fallback

Optimized Services

Microsoft Foundry, Azure OpenAI, AI Search, ADLS Gen2, Key Vault, Microsoft Fabric, Azure Data Factory, VNet/Private Endpoint, AML/AI Hub

Other Azure Services

All supported β€” MS Docs are automatically consulted to generate at the same quality standard. Do not send messages that cause user anxiety such as "out of scope" or "best-effort".

Stable vs Dynamic Information Handling

CategoryHandling MethodExamples
StableReference files firstisHnsEnabled: true, PE triple set
DynamicAlways fetch MS DocsAPI version, model availability, SKU, region

Quick Reference

FileRole
references/phase0-scanner.mdExisting resource scan + relationship inference + diagram
references/phase1-advisor.mdInteractive architecture design + fact checking
references/bicep-generator.mdBicep code generation rules
references/bicep-reviewer.mdCode review checklist
references/phase4-deployer.mdvalidate β†’ what-if β†’ deploy
references/service-gotchas.mdRequired properties, PE mappings
references/azure-dynamic-sources.mdMS Docs URL registry
references/azure-common-patterns.mdPE/security/naming patterns
references/ai-data.mdAI/Data service guide
assets/06-architecture-diagram.pngExample generated architecture diagram
assets/07-azure-portal-resources.pngExample Azure portal resource view
assets/08-deployment-succeeded.pngExample successful deployment result

Frequently asked questions about Azure Architecture Builder

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