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azure-architecture-autopilot

@boshi-xixixi · 收录于 5 天前 · 上游提交 2 个月前

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

适合你,如果常需在 Azure 上设计或优化基础设施

/ 通过 npx 安装 校验哈希
npx oh-my-skill add boshi-xixixi/traeskill/azure-architecture-autopilot
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- boshi-xixixi/traeskill/azure-architecture-autopilot
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify boshi-xixixi/traeskill/azure-architecture-autopilot
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
254GitHub stars
~1.5K最小装载
~28.7K含声明引用
~64.4K文本包总量
索引托管

怎么用

商店整理自技能原文 · 版本 9cf38e6 · 表述以原文为准
它做什么

安装后,Claude 能根据自然语言指令设计 Azure 架构并生成交互式架构图,或分析现有 Azure 资源自动出图,随后通过对话优化并生成 Bicep 代码进行部署。

什么时候触发

当你提出新设计请求(如“创建X在Azure上”)、现有分析请求(如“分析当前基础设施”)或自然语言修改(如“速度慢”、“降成本”)时触发。

装好后可以这样说
启动新设计流程,生成架构图。
扫描现有资源并生成架构图。
分析现有资源并给出修改建议。
技能原文 SKILL.md作者撰写 · MIT · 9cf38e6

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 |

按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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