Generated banner for Azure App Onboard
Generated logo for Azure App Onboard

Azure App Onboard

MicrosoftOfficialCreated by Microsoft

  • Skill
  • Workflow
  • Cloud and DevOps
  • MIT
  • Low risk
  • Has scripts

From the author

End-to-end orchestrator: from a business idea, app idea, or existing app to running Azure deployment with cost estimates and pre-deploy approval. Analyzes your app, auto-detects the right Azure services, scaffolds infrastructure code, and deploys — tailored to your app, not a template. Handles moving existing apps to Azure without rewriting or with minimal changes. WHEN: bring your app to Azure, plan my app, cost to run, is my code ready to deploy, deploy my app to the cloud, deploy all my services, what Azure services do I need, plan my Azure deployment, deploy my new app to Azure, one-click deploy, I have an app and want it on Azure, migrate my app to Azure, help me get started, build an app, no code yet, starter project. DO NOT USE FOR: use azd for deployment(use azure-deploy), optimizing existing costs (use cost-optimization), code readiness checks only (use azure-app-onboard-prereq).
— the description by Microsoft

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

Azure App Onboard is a comprehensive workflow agent designed to take a business idea or an existing codebase and transition it to a running Azure deployment. It automates the entire lifecycle from initial discovery and architecture planning to infrastructure scaffolding and final deployment. The skill is built to be intelligent and tailored, analyzing the specific requirements of your application rather than relying on generic templates. It includes built-in approval gates for both the architecture plan and the final deployment, ensuring you maintain control over costs and resource configuration throughout the process.

What it does

  • Analyzes your application code or business idea to determine the optimal Azure service stack.
  • Generates custom infrastructure-as-code (IaC) files tailored to your specific application needs.
  • Provides detailed cost estimates for the proposed Azure infrastructure before deployment.
  • Executes the deployment of resources directly to your Azure subscription.
  • Handles the migration of existing applications to Azure with minimal code changes.
  • Provides a structured, step-by-step onboarding experience for developers of all experience levels.

When to use it

  • When you have an application and want to deploy it to Azure but are unsure which services to use.
  • When you need to migrate an existing application to the cloud without a complete rewrite.
  • When you require a cost estimate for your infrastructure before committing to a deployment.
  • When you need guided, end-to-end assistance for setting up a new Azure project.
  • When you want to verify if your current codebase is ready for a cloud deployment.

Advantages

  • Eliminates guesswork by auto-detecting the right Azure services for your specific stack.
  • Reduces manual effort by automating the scaffolding of infrastructure-as-code.
  • Ensures transparency with mandatory approval gates for architecture and deployment.
  • Provides cost visibility early in the planning phase.
  • Supports a wide range of scenarios from greenfield projects to existing app migrations.

Usage examples

“I have a Python web app and want to deploy it to Azure. Can you help me get started?”
The agent will initiate the discovery phase, scan your codebase, propose an architecture, and guide you through the deployment process.
“I need to move my existing application to Azure, but I'm not sure what services I need. Can you plan this for me?”
The agent will analyze your app's requirements, suggest the appropriate Azure services, and provide a cost estimate for your approval.

Install

  1. Download the skill as a ZIP:

    https://mp-staging.autogineer.com/agent-skills/microsoft/azure-app-onboard/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip azure-app-onboard.zip -d .agents/skills

Documentation by Microsoft

Azure App Onboard

⛔ Every repo goes through the full pipeline (Steps 1–10). No exceptions. Do not skip steps, refuse, or short-circuit based on what you recognize. Follow the Workflow table below sequentially — read each step's references before acting.

Quick Reference

PropertyValue
Best forDevelopers who know what to build but not which Azure services to use
InputsBusiness idea or existing codebase, budget/scale preferences (optional)
OutputsArchitecture plan, cost estimate, IaC files, deployed Azure resources
PhasesDiscover → Architect → Scaffold → Deploy (self-contained, no external skill calls)

When to Use This Skill

  • Deploy existing code without knowing which Azure services to use

  • Check if your existing code is ready to deploy to Azure

  • Move an existing app to Azure without rewriting or with minimal changes

  • Get cost estimates before committing to infrastructure

  • Understand architecture decisions and rejected alternatives

  • Get answers to Azure architecture or service selection questions (e.g., "What database should I use?")

  • Get guided Azure onboarding without prior experience

When NOT to Use

ScenarioUse Instead
Run azd up or execute an existing deploymentazure-deploy
Optimize existing Azure spendcost-optimization from the optional azure-cost plugin
Generate Bicep/Terraform for a known architectureazure-prepare
Validate infrastructure or run preflight checksazure-validate
Troubleshoot a running Azure deploymentazure-diagnostics
Deploy to or manage AKS/Kubernetes directlyazure-kubernetes
Look up or list existing Azure resourcesazure-resource-lookup

If cost-optimization is unavailable, explain that it is provided by the optional azure-cost plugin and direct the user to their client's supported plugin installation flow; do not imply the handoff completed.

Pipeline Rules

⛔ You MUST read references/pipeline-rules.md at the start of every AppOnboard session. It contains approval gates, phase lifecycle, session artifacts, deploy-as-is, and security baseline rules.

Workflow

⛔ Deploy recovery: After deploy gate approval OR before any az deployment/az webapp deploy/az acr build — if you haven't read deploy/PHASE.md, read .copilot-azure/sessions/{id}/deploy-checklist.md first, then deploy/PHASE.md. ⛔ NEVER invoke {"skill": "azure-deploy"} — that is a DIFFERENT skill for a DIFFERENT workflow.

⛔ Post-scaffold transition (MANDATORY): Immediately after scaffold-manifest.json is written, YOUR NEXT ACTION MUST be Step 8 (Deploy Approval Gate) — NOT a summary report, NOT a "here are the generated files" message, NOT a completion signal. Confirm context.json has completedPhases: [...,"scaffold"] + currentPhase: "deploy" (update it yourself if the scaffold subagent didn't). Re-read approval-gates.md § Deploy Gate if evicted from context (scaffold reference loading is heavy), then present the exact prompt: "🚀 Ready to deploy? (Yes / Run manually / Edit plan / Cancel)". This gate is the LAST content in your response — wait for the user's reply.

#StepActionReference
1Session check + Azure loginCreate/resume session, verify Azure CLI auth, resolve subscription + user identity⛔ You MUST read session-protocol.md
2Scope triageCheck azd markers, triage question. Empty workspace or code-only (no infra) → Step 3 directly.⛔ Read intent-gathering.md § Scope Triage
3Prereq scan⛔ Skip if completedPhases includes "prereq". Otherwise: invoke {"skill": "azure-app-onboard-prereq"}. Write prereq-output.json, update context.json. Halt if: overallHealth: "blocked" OR routeToSkill set.
4Gather intentPresent prereq results, confirm stack + Azure services, ask remaining questions.⛔ Read intent-gathering.md § After Prereq Returns
5Plan architectureWrite prepare-plan.json.⛔ You MUST read prepare/PHASE.md
6Scaffold approval gateDisplay plan for user approval BEFORE generating any files.⛔ Read approval-gates.md § Scaffold Gate
7ScaffoldGenerate IaC, self-review. Write scaffold-manifest.json. Update context.json.⛔ You MUST read scaffold/PHASE.md
8Deploy approval gateDisplay validation summary. ⛔ After approval: FIRST read deploy-checklist.md → deploy/PHASE.md. NEVER {"skill": "azure-deploy"}.⛔ Read approval-gates.md § Deploy Gate
9DeployExecute IaC, health-check. Write deploy-result.json.⛔ You MUST read deploy/PHASE.md
10HandoffSurface deployment identity, cleanup commands, next steps.⛔ You MUST read handoff-protocol.md

Error Handling

ErrorRemediation
Phase failsHalt, report phase + error. User decides: retry, skip, abort.
MCP server unavailableSkip affected checks, add disclaimer to costEstimate.assumptions[] and every approval gate.
Missing RBACReport required role + az role assignment command.

Shared references: MCP tools (cross-phase tool parameters) | IaC resources (Azure resource docs for troubleshooting)

Files

references/approval-gates.md

Approval Gates — Steps 6 & 8

Gate summary: AppOnboard has 2 approval gates: (1) Scaffold Gate (orchestrator Step 6) — approve architecture plan before generating IaC, (2) Deploy Gate (orchestrator Step 8 / deploy/PHASE.md Step 4) — approve cost + resource summary before az deployment. Both are mandatory and SEPARATE — scaffold approval does NOT imply deploy approval.

Scaffold Approval Gate (Step 6)

Display the architecture plan for user approval BEFORE generating any files:

⛔ Resource group edit is MANDATORY in the gate display. Show this exact block:

🏢 **Subscription:** {subscriptionName} (`{subscriptionId}`)
📦 **Resource Group:** {rg-name} ({region})
   Want a different name or region? Say "Edit plan".

⛔ Gate MUST show Subscription (name + ID), Resource Group, and Region as standalone lines above the service table — see pipeline-rules.md § Approval gates. Do NOT omit or bury in a table.

Also display: services + SKUs + region + resource names + monthly cost estimate + files to generate. Check context.json.overrides[] for iacFormat — if Terraform, display "Terraform templates (infra/*.tf)"; if Bicep (default), display "Bicep templates (infra/main.bicep)". Show resource names so the user sees what will be created.

⛔ Surface plan assumptions. If prepare-plan.json.assumptions[] is present (e.g., free-tier degradation to a paid SKU), display each note prefixed with ⚠️ ABOVE the approval prompt — the user MUST see WHY the cost or SKU differs from the fast-track default. Do not bury or omit them.

Verify file list against target SKU — F1/D1: no Dockerfile (built-in runtime). ⛔ Exclude azure.yaml from file list (see pipeline-rules.md).

⛔ Container Apps code deploy preview (when plan includes Container Apps). After the service table, preview the deploy path: build via ACR, replace placeholder images, redeploy. If buildRequirements.hasBuildKitSyntax == true, note ACR-compatible versions will be created.

⛔ Data-loss warnings at the gate. If prereq-output.json.warnings[] contains any data-loss findings (SQLite on App Service, in-memory sessions, local file storage), surface them prominently with ⛔ formatting ABOVE the approval prompt. The user must see these before approving — do not bury them in a table or omit them.

⛔ Fix offer — fixes that edit the user's own files (asked BEFORE the gate prompt). Collect prereq-output.json.warnings[] with fixPhase: "scaffold" whose fix edits the user's app files (IaC-only fixes are scaffolded automatically and are NOT listed). If none → skip this step. Otherwise list them numbered — warning, file(s) it would change, and the exact change — and ask_user with choices exactly Fix all, Fix some, Fix none (Fix some → ask which numbers). Apply the chosen fixes as static edits only (no build or tests), show the diff, remove each fixed warning from warnings[] and postDeployRecommendations[], and update every session artifact that records the changed fact (stack, detectedStack and verdicts in context.json and prereq-output.json, readiness-report.md, prepare-plan.json notes) so none still describes the pre-edit state. Set every declined warning's fixPhase to "post-deploy". Never edit app files without the user's choice. Then present the gate prompt below unchanged — it is not re-shown.

⛔ Database network access (when plan includes PostgreSQL/MySQL). Show a Database access line above the approval prompt: the default AllowAllAzureServicesAndResourcesWithinAzureIps (0.0.0.0) lets the app connect but opens the server to all Azure services. ⛔ Render the exposure as its own bold sentence so a fast "Yes" is still an informed "Yes": "Proceeding opens the database to all Azure services — not just this app." Offer the alternative: "For private networking (VNet integration + private endpoint), say 'Private access' — AppOnboard does not build private networking itself, so it will hand off to azure-enterprise-infra-planner, which then owns the secure networking design and its deployment. AppOnboard stops here — it does not resume afterward." If the user proceeds (Yes), that counts as consent to the 0.0.0.0 rule.

⛔ Private networking redirect. If the user chooses Private access (here or during Edit plan): set context.json.routeToSkill: "azure-enterprise-infra-planner" and routeReason: "private-networking-requested", then HALT — do NOT generate IaC. Tell the user: "AppOnboard can't generate private networking (VNet + private endpoint). Handing off to azure-enterprise-infra-planner, which will design the secure topology and deploy it from here — it takes over the rest of the onboarding. Your AppOnboard session is saved for reference." Then invoke {"skill": "azure-enterprise-infra-planner"}. This mirrors the prereq routeToSkill halt (SKILL.md Step 3) but fires at the Scaffold Gate.

⛔ Pick the prompt variant FIRST (based on whether the plan has a database), then use it verbatim — do NOT paraphrase or reword:

  • Plan includes PostgreSQL/MySQL → "✅ Ready to proceed with scaffolding? (Yes / Edit plan / Private access / Cancel)" — the ask_user choices MUST be exactly: Yes, Edit plan, Private access, Cancel.

  • No database in plan → "✅ Ready to proceed with scaffolding? (Yes / Edit plan / Cancel)" — the ask_user choices MUST be exactly: Yes, Edit plan, Cancel.

The ask_user choices MUST match the prompt text exactly — never name an option in one and omit it from the other (e.g. Private access must be a selectable choice, not something the user has to type).

⛔ RESPONSE BOUNDARY — MANDATORY. The approval gate MUST be the LAST content in your response. Do NOT generate any files, write any IaC, create any Dockerfiles, or execute any commands in the same response as the gate. Your next action MUST be reading the user's reply. If the user has not yet responded, WAIT — do not proceed.

Three options:

  • Yes → proceed to Step 7 (scaffold only — NOT deploy)

  • Edit plan → ask what to change → write to context.json.overrides[] → re-run Step 5 → show updated gate

  • Cancel → preserve session artifacts for later resumption, stop

Deploy Approval Gate (Step 8)

This is a SEPARATE gate from Step 6.

⛔ Context refresh: Before presenting this gate, re-read this SKILL.md Steps 8-9 if you have not read them in the last 5 turns. Scaffold reference loading (Steps 6-7) consumes significant context — deploy rules may have been evicted.

Display:

  • Validation status from scaffold-manifest.json.validationResult

  • Self-review summary (count of VERIFIED/PLAUSIBLE/FLAGGED findings)

  • Resource group name + region

  • Services + SKUs + estimated cost

  • End with "🚀 Ready to deploy? (Yes / Run manually / Edit plan / Cancel)"

⛔ After deploy approval: Your NEXT action MUST be: read deploy/PHASE.md, then read .copilot-azure/sessions/{id}/deploy-checklist.md. Do NOT call the azure-deploy skill — AppOnboard uses its own embedded deploy sub-skill.

If "Run manually" is selected → point to deploy-checklist-template.md § Deployment Summary for manual execution steps.

If validation failed or any FLAGGED findings exist at L1 (Security) or L3 (Hallucination), block Yes until resolved.

Only after user approves: proceed to deploy sub-skill (Step 9). context.json already has currentPhase: "deploy" from the post-scaffold checkpoint (main SKILL.md Step 7).

⛔ Before entering deploy: ⛔ Read deploy/PHASE.md before any deployment action. After mid-session compaction, re-read deploy/PHASE.md Steps 4-8. You MUST write deploy-result.json.

⛔ Deploy via az deployment sub create (see pipeline-rules.md). AppOnboard-generated azure.yaml found → never delete/overwrite; move to .copilot-azure/sessions/<id>/replaced-files/ (mirror path).

⛔ Container Apps code deploy is NOT optional. After IaC placeholder deploys, complete: az acr build → update image params → redeploy → health check. Do NOT present manual CLI "Next Steps" for core deploy tasks. If hasBuildKitSyntax, create Dockerfile.azure first.

⛔ Phase exit: deploy-result.json MUST be written before proceeding to Step 9. See deploy/PHASE.md for the full exit gate checklist.

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs an MCP server, Needs Node.js

Security

What our scanner noticed· Low risk

  • Instructions that use the network
  • Scripts that your agent may run

This skill includes scripts that your agent may run. Read them before you use it.

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Microsoft
Publisher
Microsoft (Official)
Source
microsoft/skills · .github/plugins/azure-skills/skills/azure-app-onboard · commit 0696600
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced
Also distributed in
microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download azure-app-onboard.zip