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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/handoff-protocol.md

Handoff Protocol — Step 9

Offer next steps: CI/CD setup, monitoring, domain config, 🗑️ resource cleanup, skill-based suggestions. Session artifacts remain for deferred pickup.

⛔ Handoff MUST include ALL FOUR sections: (1) Deployment Identity, (2) Cleanup Commands, (3) Redeploy Command, (4) Post-Deploy Recommendations. Missing any section = incomplete handoff. Do NOT skip cleanup even if deployment failed. Do NOT skip identity even if no resources were created. Do NOT skip recommendations even if the list is empty (print "No post-deploy recommendations.").

Deployment Identity

⛔ Start handoff with deployment identity. First lines of the handoff response MUST be:

🏢 Subscription: {context.json.azure.subscriptionName} ({context.json.azure.subscriptionId})
📁 Resource Group: {context.json.azure.resourceGroup}
🌍 Region: {context.json.azure.region}
🔗 Portal: https://portal.azure.com/#@/resource/subscriptions/{subId}/resourceGroups/{rgName}/overview

Source: context.json.azure. This is the user's quickest path to finding their resources after the session ends.

See deploy-checklist-template.md § Deployment Summary for the full deployment summary format.

Artifact Self-Check

⛔ Artifact self-check — MANDATORY before handoff. Verify these exist before presenting cleanup or next steps:

  1. deploy-result.json in session folder — if missing, read deploy-schemas.ts and write it NOW with status, endpoints, health, orphanedResourceGroups[]

  2. Portal deployment link printed in chat — if missing, generate from $resId pattern (see deploy/PHASE.md Step 6) and print now

  3. deployment-summary.md in session folder — if missing, create it NOW with the same content you are about to present in chat (status, subscription, RG, region, services table, endpoints, cleanup commands). One create call — do NOT skip.

Post-Deploy Recommendations

⛔ postDeployRecommendations[] MUST be surfaced — not silently dropped. Read prepare-plan.json.postDeployRecommendations[] (already merged with prereq findings by the prepare phase). Present EACH entry as a numbered recommendation with this format:

📋 Post-deploy recommendations:
1. **{title}** ({effort} effort) — {reason}. Services: {services[]}
2. ...

This section MUST appear BEFORE the skill-based suggestions and AFTER the cleanup commands. If postDeployRecommendations[] is empty, print "No post-deploy recommendations." Do NOT skip this section — findings buried in JSON artifacts are easily dropped from the handoff if not explicitly surfaced here.

Cleanup Commands

⛔ Cleanup commands are MANDATORY — always print BOTH. Every handoff must include these two cleanup blocks, regardless of whether healing occurred or orphans exist.

Primary cleanup (always print):

🗑️ Delete this deployment's resources:
  → az group delete -n {rg} --yes --no-wait

Tag-based bulk cleanup (always print — catches orphans from healing):

🏷️ Delete ALL resources from this AppOnboard session:
  → az group list --tag app-onboard-session-id={sessionId} --query "[].name" -o tsv | ForEach-Object { az group delete -n $_ --yes --no-wait }

This catches orphaned RGs from region fallback or naming conflict healing. For Terraform: cd infra && terraform destroy.

If deploy-result.json.orphanedResourceGroups[] is non-empty, list each explicitly with delete commands. For orphans with a subscription field, include --subscription {subscription}.

Redeploy Command

⛔ Redeploy command is MANDATORY. The full AppOnboard pipeline (prereq → prepare → scaffold → deploy) is a one-time setup. After that, the user only needs to rebuild and push code. Without this command, they'd have to reverse-engineer the deploy steps from session artifacts or re-run the entire pipeline. Give them the shortcut.

Derive from what you ran in deploy Step 6b (code deploy). Do NOT hardcode per service type — echo back the actual command(s) you executed to deploy code. The command varies by compute type, registry name, Dockerfile path, image tag, app name, etc. — all of which you already know from this session.

🔄 Redeploy (after code changes):
  → {code deploy command(s) from Step 6b}

Include this in the chat handoff AND in deployment-summary.md.

If deploy-result.json.healingAttempts[] is non-empty, surface: "⚕️ Deployment required {N} healing attempts" with per-attempt error/action/outcome and planLevelChange details.

Cross-session cleanup (optional — show if user asks):

🔍 Find ALL AppOnboard resources across all sessions:
  → az group list --tag app-onboard-skill=true -o table

Skill-Based Next Steps

⛔ Skill-based next steps are MANDATORY. Always suggest at minimum azure-compliance and azure-resource-visualizer. Evaluate every condition below.

⛔ Suggest, don't self-execute. Present these as optional suggestions. The deploy agent must NEVER perform post-deploy infra changes itself — zone redundancy, private endpoints, SKU upgrades, and resource re-creation are imperative mutations the deploy phase must not make. If the user explicitly opts into one, route to that skill as a new, scoped task; otherwise the pipeline ends at handoff.

ConditionSuggest
Alwaysazure-compliance — "Run a compliance scan on your deployed resources"
Alwaysazure-resource-visualizer — "Generate an architecture diagram of your resource group"
Reliability/HA gaps (single-zone, no failover, prod workload) or user asks to "harden" / "make production-ready"azure-reliability — "Assess & improve reliability: zone redundancy, multi-region failover, health probes"
Cost-sensitive workload or user asks about spendcost-analysis from the optional azure-cost plugin — "Review your Azure spend and identify its drivers"
Health check failed / healthStatus: "degraded"/"unreachable"azure-diagnostics — "Troubleshoot your deployment"
Auth/OAuth/MSAL detected in intent or prereqentra-app-registration — "Set up app registration for your auth flow"
postDeployRecommendations[] has upgrade suggestionsazure-upgrade — "Upgrade your runtime or framework"
Storage-heavy patternsazure-storage — "Optimize your storage configuration"
postDeployRecommendations[] mentions RBAC/roleazure-rbac — "Configure least-privilege role assignments"

If unavailable, direct the user to their client's supported plugin installation flow and leave the handoff pending.

Completion

⛔ End the handoff with an explicit completion line — the LAST thing you emit. It marks the pipeline done (so you stop working) and tells the user the core task succeeded and anything more is their choice. Frame it as closure WITH an open door — never a hard stop.

⛔ Use this EXACT sentence verbatim — do NOT paraphrase, reword, or reorder it: "The onboarding pipeline is finished." Only {primary endpoint URL} varies. This exact phrase is a required completion marker.

✅ **Deployment complete — your app is live at {primary endpoint URL}.** The onboarding pipeline is
finished. The next steps above are optional — tell me which you'd like and I'll route you to the
right skill.

⛔ The recommendations above are OPTIONAL — do NOT autonomously execute them. Present them and let the user choose; if they pick one, route to the matching skill (it makes the change properly). Don't turn a general acknowledgment into a batch of unsolicited hardening. Beyond this point the session is the user's — they may continue, invoke another skill, or run their own commands; that's expected and no longer part of this pipeline.

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

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