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github/awesome-copilot/skills/azure-architecture-autopilot/SKILL.md

azure-architecture-autopilot

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, Bice

Source repository stars
37,126
Declared platforms
0
Static risk flags
1
Last source update
2026-07-28
Source checked
2026-07-28

Decision brief

What it does—and where it fits

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

Best for

    Not for

    • Tasks that require unconfirmed production actions or broad system permissions.
    • Environments where the pinned source and install steps cannot be inspected.

    Compatibility matrix

    Platform support, with evidence labels

    PlatformStatusEvidenceWhat to check
    CodexNot declaredNo explicit evidencePortability before use
    Claude CodeNot declaredNo explicit evidencePortability before use
    CursorNot declaredNo explicit evidencePortability before use
    Gemini CLINot declaredNo explicit evidencePortability before use
    Open the compatibility checker

    Installation

    Inspect first. Install second.

    The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.

    Source-detected install commandSource
    npx skills add https://github.com/github/awesome-copilot --skill "skills/azure-architecture-autopilot"
    Safe inspection promptEditorial

    Inspect the Agent Skill "azure-architecture-autopilot" from https://github.com/github/awesome-copilot/blob/9933dcad5be5caeb288cebcd370eeeb2fc2f1685/skills/azure-architecture-autopilot/SKILL.md at commit 9933dcad5be5caeb288cebcd370eeeb2fc2f1685. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.

    Workflow

    What the source asks the agent to do

    1. 01

      Tool Usage Guide (GHCP Environment)

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

      All sub-agents (explore/task/general-purpose) cannot use webfetch or websearch. Fact-checking that requires MS Docs lookups must be performed directly by the main agent.
    2. 02

      Phase Transition Rules

      Each Phase reads and follows the instructions in its corresponding references/.md file

      Each Phase reads and follows the instructions in its corresponding references/.md fileWhen transitioning between Phases, always inform the user about the next stepDo not skip Phases (especially the what-if between Phase 3 → Phase 4)
    3. 03

      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 KoreanIf the user writes in English → respond in English (askuser, 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
    4. 04

      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.

      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.Python path + embedded diagram engine: refer to the diagram generation section in references/phase1-advisor.md.
    5. 05

      Progress Updates Required

      Use blockquote + emoji + bold format:

      Use blockquote + emoji + bold format:

    Permission review

    Static risk signals and limitations

    Network access

    medium · line 25

    The documentation includes network, browsing, or remote request actions.

    | Fetch URL content | `web_fetch` | For MS Docs lookups, etc. |

    Network access

    medium · line 26

    The documentation includes network, browsing, or remote request actions.

    | Web search | `web_search` | URL discovery |

    Evidence record

    Why each signal appears

    EvidenceSourceComputedTestedEditorial
    SignalValueEvidence typeMeaning
    Quality score87/100ComputedDocumentation, specificity, maintenance, and trust rules
    Repository stars37,126SourceRepository attention, not individual Skill quality
    Compatibility0 platformsSourceDeclared in the catalog source record
    Usage guideautomated source guideEditorialGenerated or reviewed according to the visible evidence level

    Pinned source

    Provenance and original SKILL.md

    Repository
    github/awesome-copilot
    Skill path
    skills/azure-architecture-autopilot/SKILL.md
    Commit
    9933dcad5be5caeb288cebcd370eeeb2fc2f1685
    License
    MIT
    Collected
    2026-07-28
    Default branch
    main
    View the original SKILL.md

    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)

    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 — 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 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 — 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

    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 → what-if → 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

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