---
id: daily-azure-architecture-autopilot
name: "azure-architecture-autopilot"
url: https://skills.yangsir.net/skill/daily-azure-architecture-autopilot
author: github
domain: cloud-infra
tags: ["azure", "infrastructure-as-code", "cloud-architecture", "devops", "automation"]
install_count: 1500
rating: 4.30 (58 reviews)
github: https://github.com/github/awesome-copilot
---

# azure-architecture-autopilot

> 通过自然语言设计 Azure 架构，自动生成资源图和部署脚本，或将现有资源可视化并修改部署

**Stats**: 1,500 installs · 4.3/5 (58 reviews)

## Before / After 对比

### 云架构设计

**Before**:

架构师在 Azure Portal 手动创建虚拟网络、虚拟机、负载均衡器，配置网络安全组和路由表，一个标准架构需要 2-4 小时

**After**:

描述'需要一个高可用 Web 应用'，自动生成架构图、ARM 模板和部署脚本，15 分钟完成资源配置和验证

| Metric | Before | After | Change |
|---|---|---|---|
| 架构搭建时间 | 180分钟 | 15分钟 | -92% |

## Readme

# azure-architecture-autopilot

# 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:

```
$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]** — [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 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

Weekly Installs457Repository[github/awesome-copilot](https://github.com/github/awesome-copilot)GitHub Stars28.8KFirst Seen14 days agoSecurity Audits[Gen Agent Trust HubPass](/github/awesome-copilot/azure-architecture-autopilot/security/agent-trust-hub)[SocketPass](/github/awesome-copilot/azure-architecture-autopilot/security/socket)[SnykPass](/github/awesome-copilot/azure-architecture-autopilot/security/snyk)Installed ongemini-cli400opencode397codex396github-copilot396cursor394antigravity393

---
*Source: https://skills.yangsir.net/skill/daily-azure-architecture-autopilot*
*Markdown mirror: https://skills.yangsir.net/api/skill/daily-azure-architecture-autopilot/markdown*