azure-prepare

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, se

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

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.
Get approval — Present plan to user before execution
Research before generating — Load references and invoke related skills
Update plan progressively — Mark steps complete as you go
Validate before deploy — Invoke azure-validate before azure-deploy
Confirm Azure context — Use ask_user for subscription and location per Azure Context
❌ Destructive actions require ask_user — Global Rules
⛔ 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.
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.
⛔ 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.
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

STOP — Do not generate any code, infrastructure, or configuration yet

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

CONFIRM — Present the completed plan to the user and get approval

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 keywords	Invoke 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 GCP	azure-cloud-migrate
Azure Functions, function app, serverless function, timer trigger, HTTP trigger, func new	Stay 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 APIM	Stay in azure-prepare — see APIM Deployment Guide
AI gateway, AI gateway policy, AI gateway backend, AI gateway configuration	azure-aigateway
workflow, orchestration, multi-step, pipeline, fan-out/fan-in, saga, long-running process, durable, order processing	Stay 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.

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.

#	Action	Reference
0	If the prompt matches a specialized technology with a dedicated skill, invoke that skill first	specialized-routing.md
1	Analyze Workspace — Determine mode: NEW, MODIFY, or MODERNIZE	analyze.md
2	Gather Requirements — Classification, scale, budget	requirements.md
3	Scan Codebase — Identify components, technologies, dependencies	scan.md
4	Select Recipe — Choose AZD (default), AZCLI, Bicep, or Terraform	recipe-selection.md
5	Plan Architecture — Select stack + map components to Azure services	architecture.md
6	Finalize 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
7	Present Plan — Show plan to user and ask for approval	`.azure/deployment-plan.md`
8	Destructive actions require `ask_user`	Global 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.

#	Action	Reference
1	Research Components — Load service references + invoke related skills	research.md
2	Confirm Azure Context — Detect and confirm subscription + location and check the resource provisioning limit	Azure Context
3	Generate Artifacts — Create infrastructure and configuration files	generate.md
4	Harden Security — Apply security best practices	security.md
5	Functional Verification — Verify the app works (UI + backend), locally if possible	functional-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

Artifact	Location
Plan	`.azure/deployment-plan.md`
Infrastructure	`./infra/`
AZD Config	`azure.yaml` (AZD only)
Dockerfiles	`src/<component>/Dockerfile`

SDK Quick References

Azure Developer CLI: azd
Azure Identity: Python | .NET | TypeScript | Java
App Configuration: Python | TypeScript | Java

⛔ 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