Design Azure infrastructure using natural language, or analyze existing Azure resources to auto-generate architecture diagrams, refine them through conversation, and deploy with Bicep. When to use this skill: - "Create X on Azure", "Set up a RAG architecture" (new design) - "Analyze my current Azure

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 — 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 → respond in Korean If the user writes in English → respond in English (ask user, progress updates, reports, Bicep comments — 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) Feature Tool Name Notes Fetch URL content web fetch For MS Docs lookups, etc. Web search web search URL discovery Ask user ask user choices must be a string array Sub agents task explore/task/general purpose Shell command execution powershell Windows 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 — risk of Windows Store alias. Direct filesystem discovery ( $env:LOCALAPPDATA\Programs\Python ) takes priority. az CLI path: Python path + embedded diagram engine: refer to the diagram generation section in references/phase1 advisor.md . Progress Updates Required Use blockquote + emoji + bold format: Parallel Preload Principle While waiting for user input via ask user , preload information needed for the next step in parallel. ask user Question Preload Simultaneously Project name / scan scope Reference files, MS Docs, Python path discovery, diagram module path verification Model/SKU selection MS Docs for next question choices Architecture confirmation az account show/list , az group list Subscription selection az group list Path Branching — Automatically Determined by User Request Path A: New Design (New Build) Trigger : "create", "set up", "deploy", "build", etc. Path B: Existing Analysis + Modification (Analyze & Modify) Trigger : "analyze", "current resources", "scan", "draw a diagram", "show my infrastructure", etc. When Path Determination Is Ambiguous Ask the user directly: 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 → Phase 4) 🚨 Required condition for Phase 1 → 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 — Phase 1 includes diagram generation + user confirmation. Modification request after deployment → 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 — 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 Category Handling Method Examples Stable Reference files first isHnsEnabled: true , PE triple set Dynamic Always fetch MS Docs API version, model availability, SKU, region Quick Reference File Role references/phase0 scanner.md Existing resource scan + relationship inference + diagram references/phase1 advisor.md Interactive architecture design + fact checking references/bicep generator.md Bicep code generation rules references/bicep reviewer.md Code review checklist references/phase4 deployer.md validate → what if → deploy references/service gotchas.md Required properties, PE mappings references/azure dynamic sources.md MS Docs URL registry references/azure common patterns.md PE/security/naming patterns references/ai data.md AI/Data service guide assets/06 architecture diagram.png Example generated architecture diagram assets/07 azure portal resources.png Example Azure portal resource view assets/08 deployment succeeded.png Example successful deployment result

azure-architecture-autopilot