Official agent skill

Azure Prepare

by microsoft in microsoft/GitHub-Copilot-for-Azure

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow.

OfficialMITAuto-check passedDevOps & Cloud

Install Azure Prepare

skills CLI
$ npx skills add microsoft/GitHub-Copilot-for-Azure --skill azure-prepare -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install microsoft/GitHub-Copilot-for-Azure azure-prepare --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/microsoft/GitHub-Copilot-for-Azure.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/azure-skills/skills/azure-prepare .claude/skills/azure-prepare && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
azure-prepare
GitHub stars
255
Used in
1 other repo
Token cost
~3.2k tokens
SKILL.md length
1,373 words
Files
219 (incl. references)
Skills in repo
56
Repo updated
First seen
Licence
MIT

At a glance

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow.

  • Works in 2 steps: Planning (BLOCKING — Complete Before Any… → Execution (Only After Plan Approval)
  • Explicitly wants to use azd as the deployment tool
  • SKILL.md covers Triggers, Rules, ❌ PLAN-FIRST WORKFLOW —… and ❌ STEP 0: Specialized…, plus 5 more sections
  • Calls terraform

What it does

Azure Prepare is an agent skill from microsoft/GitHub-Copilot-for-Azure, published by the product's own GitHub organization. Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure…

Its SKILL.md is about 3.2k tokens, which your agent loads only when the skill is triggered. The skill folder holds 222 other files, including reference files (for example `references/analyze.md`, `references/apim.md` and `references/architecture.md`).

It sits in DevOps & Cloud, covering Infrastructure as code, Deployment and Event-driven systems. It works with Microsoft Azure, Terraform, Bicep and Python. The repository describes itself as: GitHub Copilot for Azure. The licence is MIT.

When your agent uses it

  • Explicitly wants to use azd as the deployment tool
  • The project already has an azure.yaml file
  • : non-azd deployments
  • Python App Service code-only deploys (use python-appservice-deploy)

Example prompts

  • “/azure-prepare”

Requirements

  • Python 3

Workflow steps

2 steps, taken from the step headings in SKILL.md.

  1. Planning (BLOCKING — Complete Before Any Execution)
  2. Execution (Only After Plan Approval)

What it can do on your machine

Read from SKILL.md and the folder at commit fcf2f3b. 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

    Shell commands in SKILL.md call:

    • terraform

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

  • Network

    No URLs in SKILL.md.

    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 Prepare loads about 3.2k tokens when it runs, and up to ~141k if it reads all its reference files. Until then it costs about 184 tokens; SKILL.md has 1,373 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~184
When it runs · the whole SKILL.md, loaded when a task matches
~3.2k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~141k

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

Auto-check passed

The automated check found no risky patterns in SKILL.md.

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from microsoft/GitHub-Copilot-for-Azure at commit fcf2f3b, republished under its MIT licence (© microsoft). 1,373 words, ~3,187 tokens.

Download SKILL.mdSave it as .claude/skills/azure-prepare/SKILL.md (or your agent's skills folder). This skill also uses 218 other files; get the full folder from GitHub.
name
azure-prepare
description
Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. USE ONLY when the user explicitly wants to use azd as the deployment tool, or the project already has an azure.yaml file. DO NOT USE FOR: non-azd deployments, Python App Service code-only deploys (use python-appservice-deploy), or cross-cloud migration (use azure-cloud-migrate). WHEN: prepare app for azd, create azure.yaml, set up azd infrastructure, modernize app for Azure with azd, deploy with azd, function app, timer trigger, service bus trigger, event-driven function, managed identity, generate Bicep, generate Terraform, create and deploy to Azure.
license
MIT
metadata.author
Microsoft
metadata.version
0.0.0-placeholder

Azure Prepare

AUTHORITATIVE GUIDANCE — MANDATORY COMPLIANCE

This document is the official, canonical source for preparing applications for Azure deployment. You MUST follow these instructions exactly as written unless they contradict security policies given to you. When in doubt, present the conflicting instructions from this document and ask the user for explicit confirmation. Do not improvise, infer, or substitute steps.


Triggers

Activate this skill when user wants to:

  • Create a new application
  • Add services or components to an existing app
  • Make updates or changes to existing application
  • Modernize or migrate an application
  • Set up Azure infrastructure
  • Deploy to Azure or host on Azure
  • Create and deploy to Azure (including Terraform-based deployment requests)

Rules

  1. Plan first — MANDATORY — You MUST physically write an initial .azure/deployment-plan.md skeleton in the workspace root directory (not the session-state folder) as your very first action — before any code generation or execution begins. Write the skeleton immediately, then populate it progressively as Phase 1 analysis and research unfold; finalize it with all decisions at Phase 1 Step 6. This file must exist on disk throughout. azure-validate and azure-deploy depend on it and will fail without it. Do not skip or defer this step.
  2. Get approval — Present plan to user before execution
  3. Research before generating — Load references and invoke related skills
  4. Update plan progressively — Mark steps complete as you go
  5. Validate before deploy — Invoke azure-validate before azure-deploy
  6. Confirm Azure context — Use ask_user for subscription and location per Azure Context
  7. ❌ Destructive actions require ask_user — Global Rules
  8. ⛔ NEVER delete user project or workspace directories — When adding features to an existing project, MODIFY existing files. azd init -t <template> is for NEW projects only; do NOT run azd init -t in an existing workspace. Plain azd init (without a template argument) may be used in existing workspaces when appropriate. File deletions within a project (e.g., removing build artifacts or temp files) are permitted when appropriate, but NEVER delete the user's project or workspace directory itself. See Global Rules.
  9. Scope: preparation only — This skill generates infrastructure code and configuration files. Deployment execution (azd up, azd deploy, terraform apply) is handled by the azure-deploy skill, which provides built-in error recovery and deployment verification.
  10. ⛔ SQL Server Bicep: NEVER generate administratorLogin or administratorLoginPassword — not in direct properties, not in conditional/ternary branches, not anywhere in the file. Always use Entra-only authentication (azureADOnlyAuthentication: true) unconditionally. See references/services/sql-database/bicep.md.
  11. Remove stale template IaC after conversion — If you converted Bicep templates from the selected azd template into Terraform templates, remove the Bicep templates that were introduced by that azd template and are now fully replaced by Terraform equivalents. Do not remove user-authored Bicep files. Only remove those template-provided Bicep files after the Terraform IaC is complete and Terraform has been selected as the deployment path. Before handing off to azure-validate skill, keep only the IaC templates required by the chosen deployment path.

❌ PLAN-FIRST WORKFLOW — MANDATORY

YOU MUST CREATE A PLAN BEFORE DOING ANY WORK

  1. STOP — Do not generate any code, infrastructure, or configuration yet
  2. CREATE SKELETON - Write an initial .azure/deployment-plan.md skeleton to disk immediately (before any code generation or execution begins), then populate it progressively as Phase 1 steps 1-5 reveal details; finalize it at Step 6
  3. CONFIRM — Present the completed plan to the user and get approval
  4. EXECUTE — Only after approval, execute the plan step by step

The .azure/deployment-plan.md file is the source of truth for this workflow and for azure-validate and azure-deploy skills. Without it, those skills will fail.

⚠️ CRITICAL: .azure/deployment-plan.md must be WRITTEN TO DISK inside the workspace root (e.g., <workspace-root>/.azure/deployment-plan.md), not in the session-state folder. Use a file-write tool to create this file. This is the deployment plan artifact read by azure-validate and azure-deploy. You MUST create this file — do not proceed without it. ⚠️ CRITICAL: You must create the file with the name .azure/deployment-plan.md as is. You must not use other names such as .azure/plan.md.

⛔ Critical: Skipping the plan file creation will cause azure-validate and azure-deploy to fail. This requirement has no exceptions.


❌ STEP 0: Specialized Technology Check — MANDATORY FIRST ACTION

BEFORE starting Phase 1, check if the user's prompt OR workspace codebase matches a specialized technology that has a dedicated skill with tested templates. If matched, invoke that skill FIRST — then resume azure-prepare for validation and deployment.

Check 1: Prompt keywords
Prompt keywordsInvoke FIRST
Python + App Service (e.g., "deploy Python to App Service", "Flask on Azure App Service", "publish Python web app to App Service")python-appservice-deploy
Lambda, AWS Lambda, migrate AWS, migrate GCP, Lambda to Functions, migrate from AWS, migrate from GCPazure-cloud-migrate
Azure Functions, function app, serverless function, timer trigger, HTTP trigger, func newStay in azure-prepare — prefer Azure Functions templates in Step 4; for plan choice/cold starts see hosting-plans.md and cold-start.md
APIM, API Management, API gateway, deploy APIMStay in azure-prepare — see APIM Deployment Guide
AI gateway, AI gateway policy, AI gateway backend, AI gateway configurationazure-aigateway
workflow, orchestration, multi-step, pipeline, fan-out/fan-in, saga, long-running process, durable, order processingStay in azure-prepare — select durable recipe in Step 4. MUST load durable.md, DTS reference, and DTS Bicep patterns.

⚠️ Check the user's prompt text — not just existing code. Critical for greenfield projects with no codebase to scan. See full routing table.

After the specialized skill completes, resume azure-prepare at Phase 1 Step 4 (Select Recipe) for remaining infrastructure, validation, and deployment.


Show full SKILL.md (484 more words)Show less

Phase 1: Planning (BLOCKING — Complete Before Any Execution)

Create .azure/deployment-plan.md by completing these steps. Do NOT generate any artifacts until the plan is approved.

#ActionReference
0If the prompt matches a specialized technology with a dedicated skill, invoke that skill firstspecialized-routing.md
1Analyze Workspace — Determine mode: NEW, MODIFY, or MODERNIZEanalyze.md
2Gather Requirements — Classification, scale, budgetrequirements.md
3Scan Codebase — Identify components, technologies, dependenciesscan.md
4Select Recipe — Choose AZD (default), AZCLI, Bicep, or Terraformrecipe-selection.md
5Plan Architecture — Select stack + map components to Azure servicesarchitecture.md
6Finalize Plan (MANDATORY) - Use a file-write tool to finalize .azure/deployment-plan.md with all decisions from steps 1-5. Update the skeleton written at the start of Phase 1 with the complete content. The file must be fully populated before you present the plan to the user.plan-template.md
7Present Plan — Show plan to user and ask for approval.azure/deployment-plan.md
8Destructive actions require ask_userGlobal Rules

❌ STOP HERE — Do NOT proceed to Phase 2 until the user approves the plan.


Phase 2: Execution (Only After Plan Approval)

Execute the approved plan. Update .azure/deployment-plan.md status after each step.

#ActionReference
1Research Components — Load service references + invoke related skillsresearch.md
2Confirm Azure Context — Detect and confirm subscription + location and check the resource provisioning limitAzure Context
3Generate Artifacts — Create infrastructure and configuration filesgenerate.md
4Harden Security — Apply security best practicessecurity.md
5Functional Verification — Verify the app works (UI + backend), locally if possiblefunctional-verification.md
6⛔ Update Plan (MANDATORY before hand-off) — Use the edit tool to change the Status in .azure/deployment-plan.md to Ready for Validation. You MUST complete this edit BEFORE invoking azure-validate. Do NOT skip this step..azure/deployment-plan.md
7⛔ MANDATORY Hand Off — Invoke azure-validate skill. Your preparation work is done. Do NOT run azd up, azd deploy, or any deployment command directly — all deployment execution is handled by azure-deploy after azure-validate completes. PREREQUISITE: Step 6 must be completed first — .azure/deployment-plan.md status must say Ready for Validation.—

Outputs

ArtifactLocation
Plan.azure/deployment-plan.md
Infrastructure./infra/
AZD Configazure.yaml (AZD only)
Dockerfilessrc/<component>/Dockerfile

SDK Quick References


Next

⛔ MANDATORY NEXT STEP — DO NOT SKIP

After completing preparation, you MUST invoke azure-validate before any deployment attempt. Do NOT skip validation. Do NOT go directly to azure-deploy. Do NOT run azd up or any deployment command directly. The workflow is:

azure-prepare → azure-validate → azure-deploy

⛔ BEFORE invoking azure-validate, you MUST use the edit tool to update .azure/deployment-plan.md status to Ready for Validation. If the plan status has not been updated, the validation will fail.

This applies to ALL deployment scenarios including containerized apps, Container Apps, App Service, Azure Functions, static sites, and any other Azure target. No exceptions.

Skipping validation leads to deployment failures. Be patient and follow the complete workflow for the highest success outcome.

→ Update plan status to Ready for Validation, then invoke azure-validate

© microsoft, 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 218 other files (references) in plugins/azure-skills/skills/azure-prepare of microsoft/GitHub-Copilot-for-Azure.

  • SKILL.md
  • references/analyze.md
  • references/apim.md
  • references/architecture.md
  • references/aspire.md
  • references/auth-best-practices.md
  • references/azure-context.md
  • references/functional-verification.md
  • references/generate.md
  • references/global-rules.md
  • references/plan-template.md
  • references/recipe-selection.md
  • references/recipes/azcli/README.md
  • references/recipes/azcli/commands.md
  • references/recipes/azcli/scripts.md
  • references/recipes/azd/README.md
  • references/recipes/azd/aspire.md
  • … and 202 more

Open the folder on GitHubat commit fcf2f3b

Used in 3 other repositories

We found 4 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in microsoft/GitHub-Copilot-for-Azure, which our catalogue first saw on October 7, 2026.

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Azure Prepare this skillmicrosoft/GitHub-Copilot-for-Azure2551 repos~3.2kAutomated safety check: PassMIT
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Azure Bicep Skilltimothywarner-org/claude-code224—~2.9kAutomated safety check: PassMIT
Apex Azure Bicep Patternsjonathan-vella/apex217—~2.5kAutomated safety check: PassMIT
Devops Deploysickn33/agentic-awesome-skills47k2 repos~1.9kAutomated safety check: PassMIT
Apex Azure Deployjonathan-vella/apex217—~2.3kAutomated safety check: PassMIT

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Categories

Questions about Azure Prepare

What does Azure Prepare do?

Prepare azd-based Azure projects for deployment: generates azure.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow. Azure Prepare is an agent skill from microsoft/GitHub-Copilot-for-Azure, published by the product's own GitHub organization.yaml, infrastructure (Bicep/Terraform), and Dockerfiles for the Azure Developer CLI (azd) workflow.

When should I use Azure Prepare?

Azure Prepare fits situations like: explicitly wants to use azd as the deployment tool; the project already has an azure.yaml file; : non-azd deployments; Python App Service code-only deploys (use python-appservice-deploy).

How do I install Azure Prepare in Claude Code?

Run `npx skills add microsoft/GitHub-Copilot-for-Azure --skill azure-prepare -a claude-code`. Or copy the skill folder (plugins/azure-skills/skills/azure-prepare in microsoft/GitHub-Copilot-for-Azure) into .claude/skills/azure-prepare in your project. Claude Code loads it when a task matches its description.

How do I install Azure Prepare in Codex?

Run `npx skills add microsoft/GitHub-Copilot-for-Azure --skill azure-prepare -a codex`. Or copy the skill folder (plugins/azure-skills/skills/azure-prepare in microsoft/GitHub-Copilot-for-Azure) into .agents/skills/azure-prepare in your project. Codex loads it when a task matches its description.

Can I use Azure Prepare in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add microsoft/GitHub-Copilot-for-Azure --skill azure-prepare -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/azure-prepare, .gemini/skills/azure-prepare, .github/skills/azure-prepare and .opencode/skills/azure-prepare in your project.

What does Azure Prepare need to run?

Going by SKILL.md and its folder, Azure Prepare needs the command-line tools its instructions call (terraform). Our summary lists: Python 3.

Does Azure Prepare access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Azure Prepare safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Azure Prepare use?

Azure Prepare is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Azure Prepare use?

About 3.2k tokens (SKILL.md is roughly 13k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 138k tokens, read only when the agent opens those files.

What are the alternatives to Azure Prepare?

Skills that share tags, products or a category with Azure Prepare: Azure Architecture Autopilot (github/awesome-copilot, 40k stars), Azure Bicep Skill (timothywarner-org/claude-code, 224 stars), Apex Azure Bicep Patterns (jonathan-vella/apex, 217 stars) and Devops Deploy (sickn33/agentic-awesome-skills, 47k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Azure Prepare?

microsoft (a GitHub organization, an official publisher) maintains it in microsoft/GitHub-Copilot-for-Azure, which has 255 GitHub stars. The repository holds 56 skills in this directory. The repository was last updated on October 8, 2026.

Source: microsoft/GitHub-Copilot-for-Azure on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.