Azure Architecture Autopilot

What it does

When your agent uses it

• Designing a new Azure architecture from a plain-language description
• Generating a diagram of an existing Azure resource group
• Asking for a design change such as reducing cost or improving security
• Generating and reviewing a Bicep template before deployment

Example prompts

• “Set up a RAG architecture on Azure using AI Search and OpenAI.”
• “Draw a diagram for rg-prod-eastus and suggest ways to reduce its cost.”
• “Foundry is slow in this design — suggest and apply a fix.”

Requirements

• Azure CLI (`az`)
• Python
• Bicep

What it can do on your machine

Read from SKILL.md and the folder at commit 7cce7cf. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Ships 3 files in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • az
  • pip

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  No URLs in SKILL.md. Its commands use az and pip, which can reach the network depending on how they are called.

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Azure Architecture Autopilot loads about 1.9k tokens when it runs, and up to ~38k if it reads all its reference files. Until then it costs about 166 tokens; SKILL.md has 651 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~166

When it runs · the whole SKILL.md, loaded when a task matches

~1.9k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~38k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from github/awesome-copilot at commit 7cce7cf, republished under its MIT licence (© github). 651 words, ~1,890 tokens.

name

azure-architecture-autopilot

description

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

$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 }
}

> **⏳ [Action]** — [Reason]
> **✅ [Complete]** — [Result]
> **⚠️ [Warning]** — [Details]
> **❌ [Failed]** — [Cause]

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

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

ask_user({
  question: "What would you like to do?",
  choices: [
    "Design a new Azure architecture (Recommended)",
    "Analyze + modify existing Azure resources"
  ]
})

© github, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 17 other files (scripts, references, assets) in skills/azure-architecture-autopilot of github/awesome-copilot.

• SKILL.md
• .gitignore
• assets/06-architecture-diagram.png
• assets/07-azure-portal-resources.png
• assets/08-deployment-succeeded.png
• references/ai-data.md
• references/architecture-guidance-sources.md
• references/azure-common-patterns.md
• references/azure-dynamic-sources.md
• references/bicep-generator.md
• references/bicep-reviewer.md
• references/phase0-scanner.md
• references/phase1-advisor.md
• references/phase4-deployer.md
• references/service-gotchas.md
• scripts/cli.py
• scripts/generator.py
• scripts/icons.py

Open the folder on GitHubat commit 7cce7cf

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in github/awesome-copilot, which our catalogue first saw on October 7, 2026.

• boshi-xixixi/TraeSkill.trae/Skills/.agents/skills/azure-architecture-autopilot