PaperclipOrg
Claude Agent Skill · by Github

Azure Architecture Autopilot

Install Azure Architecture Autopilot skill for Claude Code from github/awesome-copilot.

Install
Terminal · npx
$npx skills add https://github.com/microsoft/github-copilot-for-azure --skill azure-ai
Works with Paperclip

How Azure Architecture Autopilot fits into a Paperclip company.

Azure Architecture Autopilot drops into any Paperclip agent that handles this kind of work. Assign it to a specialist inside a pre-configured PaperclipOrg company and the skill becomes available on every heartbeat — no prompt engineering, no tool wiring.

S
SaaS FactoryPaired

Pre-configured AI company — 18 agents, 18 skills, one-time purchase.

$27$59
Explore pack
Source file
SKILL.md170 lines
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---name: azure-architecture-autopilotdescription: >  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 infrastructure", "Draw a diagram for rg-xxx" (existing analysis)  - "Foundry is slow", "I want to reduce costs", "Strengthen security" (natural language modification)  - Azure resource deployment, Bicep template generation, IaC code generation  - Microsoft Foundry, AI Search, OpenAI, Fabric, ADLS Gen2, Databricks, and all Azure services--- # 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 scriptsto 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:```powershell$azCmd = $nullif (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:```markdown> **⏳ [Action]** — [Reason]> **✅ [Complete]** — [Result]> **⚠️ [Warning]** — [Details]> **❌ [Failed]** — [Cause]``` ## 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.```Phase 1 (references/phase1-advisor.md) — Interactive architecture design + diagram    ↓Phase 2 (references/bicep-generator.md) — Bicep code generation    ↓Phase 3 (references/bicep-reviewer.md) — Code review + compilation verification    ↓Phase 4 (references/phase4-deployer.md) — validate → what-if → 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) — Existing resource scan + diagram    ↓Modification conversation — "What would you like to change here?" (natural language modification request → follow-up questions)    ↓Phase 1 (references/phase1-advisor.md) — Confirm modifications + update diagram    ↓Phase 2~4 — 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 → 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 ServicesMicrosoft Foundry, Azure OpenAI, AI Search, ADLS Gen2, Key Vault, Microsoft Fabric, Azure Data Factory, VNet/Private Endpoint, AML/AI Hub ### Other Azure ServicesAll 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 |