Azure Prepare

MicrosoftOfficialCreated by Microsoft

Skill
Workflow
Cloud and DevOps
MIT
Medium risk
Has scripts

From the author

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.

— the description by Microsoft

AutoGineer summary

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

The azure-prepare skill provides a mandatory, structured workflow for setting up applications for deployment to Azure via the Azure Developer CLI (azd). It enforces a plan-first approach, requiring the creation of a deployment plan file before any infrastructure generation or configuration occurs. The skill guides users through analyzing their workspace, selecting appropriate deployment recipes (Bicep or Terraform), and configuring necessary Azure services, while ensuring security best practices are followed. It acts as the initial phase in a three-part deployment pipeline: prepare, validate, and deploy.

What it does

Generates azure.yaml configuration files for azd-based projects.
Creates infrastructure-as-code templates using Bicep or Terraform.
Enforces a mandatory .azure/deployment-plan.md file to track project state.
Integrates with specialized skills for specific technologies like Azure Functions or API Management.
Applies security hardening, such as Entra-only authentication for SQL databases.
Prepares the workspace for subsequent validation and deployment steps.

When to use it

When you need to prepare a new or existing project for deployment to Azure using azd.
When you need to generate infrastructure-as-code (Bicep or Terraform) for your application.
When you are modernizing an existing application to run on Azure.
When you need to add new Azure services or components to an existing project.

Advantages

Ensures consistent deployment configurations across projects.
Prevents common configuration errors through a mandatory planning phase.
Integrates seamlessly with the broader Azure deployment ecosystem (validate and deploy).
Promotes security best practices by default, such as managed identities.
Provides clear guidance on when to delegate to specialized deployment skills.

Usage examples

“I want to deploy my new web application to Azure using azd.”: The agent will initiate the NEW mode, guide you through requirements gathering, create a deployment plan, and generate the necessary infrastructure and configuration files.
“Add an Azure Function to my existing project and set up the infrastructure.”: The agent will analyze your existing project, select the appropriate Azure Functions recipe, update the deployment plan, and generate the required Bicep or Terraform files.

Install

Download the skill as a ZIP:
https://autogineer.com/agent-skills/microsoft/azure-prepare/download

Unzip it into the cross-client skills folder of your project:

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

Documentation by Microsoft

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

Files

references/resources-limits-quotas.md

Azure Resource Limits and Quotas

Check Azure resource availability during azure-prepare workflow. Validate after customer selects region.

Types

Hard Limits - Fixed constraints that cannot be changed
Quotas - Subscription limits that can be increased via support request

CLI First: Always use az quota CLI for quota checks. Provides better error handling and consistent output. "No Limit" in REST/Portal doesn't mean unlimited - verify with service docs.

Hard Limits

Fixed service constraints (cannot be changed).

Check via: azure__documentation tool or azure-provisioning-limit skill

Examples: Cosmos DB item size (2 MB), Container Apps HTTP timeout (240s), App Service Free tier deployment slots (0)

Process:

Identify services and resource sizes needed
Look up limits in documentation
Compare plan vs limits
If exceeded: redesign or change tier

Quotas

Subscription/regional limits that can be increased via support request.

Check via: az quota CLI (install: az extension add --name quota)

Examples: AKS clusters (5,000/region), Storage accounts (250/region), Container Apps environments (50/region)

Key Concept: No 1:1 mapping between ARM resource types and quota names.

ARM: Microsoft.App/managedEnvironments → Quota: ManagedEnvironmentCount
ARM: Microsoft.Compute/virtualMachines → Quota: standardDSv3Family, cores, virtualMachines

Process:

Install extension: az extension add --name quota
Discover quota names: az quota list --scope /subscriptions/{id}/providers/{Provider}/locations/{region}
Check usage: az quota usage show --resource-name {name} --scope ...
Check limit: az quota show --resource-name {name} --scope ...
Calculate: Available = Limit - Current Usage
If exceeded: Request increase via az quota update

Unsupported Providers (BadRequest error):

Not all providers support quota API. If az quota list fails with BadRequest, use fallback:

Get current usage:

# Option A: Azure Resource Graph (recommended)
az extension add --name resource-graph
az graph query -q "resources | where type == '{type}' and location == '{loc}' | count"

# Option B: Resource list
az resource list --subscription "{id}" --resource-type "{Type}" --location "{loc}" | jq 'length'

Get limit from service documentation
Calculate: Available = Documented Limit - Current Usage

Known Support Status:

❌ Microsoft.DocumentDB (Cosmos DB)
✅ Microsoft.Compute, Microsoft.Network, Microsoft.App, Microsoft.Storage, Microsoft.MachineLearningServices

Workflow

Phase 1: Identify & Check Hard Limits

Analyze app requirements and select Azure services
Determine resource counts, sizes, tiers, throughput
Check hard limits via azure-provisioning-limit skill or documentation
Validate plan against limits; redesign if needed

Phase 2: Check Quotas After Region Selection

Get customer subscription and region preference
For each service/region, check quota:
- Use az quota usage list and az quota show
- Calculate available capacity
If quota exceeded: request increase or choose different region

Phase 3: Validate Region

Confirm sufficient quota in selected region
Request increases if needed
Only proceed after validation complete

Limit Scopes

Scope	Example
Subscription	50 Cosmos DB accounts (any region)
Regional	250 storage accounts per region
Resource	500 apps per Container Apps environment

Service Patterns

Service	Hard Limits (examples)	Quota Check	Notes
Cosmos DB	Item: 2MB, Partition key: 2KB, Serverless storage: 50GB	❌ Not supported. Use Resource Graph + docs. Default: 50 accounts/region	Query: `az graph query -q "resources \| where type == 'microsoft.documentdb/databaseaccounts' and location == 'eastus' \| count"`
AKS	Pods/node (Azure CNI): 250, Node pools/cluster: 100	✅ `az quota` supported	Provider: Microsoft.ContainerService
Storage	Block blob: 190.7 TiB, Page blob: 8 TiB	✅ Quota: `StorageAccounts` (limit: 250/region)	Provider: Microsoft.Storage
Container Apps	Revisions/app: 100, HTTP timeout: 240s	✅ Quota: `ManagedEnvironmentCount` (limit: 50/region)	Provider: Microsoft.App
Functions	Timeout (Consumption): 10 min, Queue msg: 64KB	✅ Check function apps quota	Provider: Microsoft.Web

CLI Reference

Prerequisites: az extension add --name quota

Discovery: List quotas to find resource names

az quota list --scope /subscriptions/{id}/providers/{provider}/locations/{location}

Check Usage:

az quota usage show --resource-name {quota-name} --scope /subscriptions/{id}/providers/{provider}/locations/{location}

Check Limit:

az quota show --resource-name {quota-name} --scope /subscriptions/{id}/providers/{provider}/locations/{location}

Request Increase:

az quota update --resource-name {quota-name} --scope /subscriptions/{id}/providers/{provider}/locations/{location} --limit-object value={new-limit} --resource-type {type}

azure-prepare Integration

When to Check:

After selecting services - Check hard limits
After customer selects region - Check quotas
Before generating infrastructure code - Validate availability

Required Steps:

Phase 1 - Planning:

Select Azure services
Check hard limits (service documentation)
Create provisioning limit checklist (leave quota columns as "TBD")

Phase 2 - Execution:

Get subscription and region preference
Must invoke azure-quotas skill - Process ONE resource type at a time: a. Try az quota list first (required) b. If supported: Use az quota usage show and az quota show c. If NOT supported (BadRequest): Use Resource Graph + service docs d. Calculate available capacity e. Document in checklist (no "TBD" entries allowed) f. If insufficient: Request increase or change region

Phase 3 - Generate Artifacts:

Only proceed after Phase 2 complete (all quotas validated)

Error Messages

Error	Type	Action
"Quota exceeded"	Quota	Use azure-quotas to request increase
"(BadRequest) Bad request"	Unsupported provider	Use service limits docs
"Limit exceeded"	Hard Limit	Redesign or change tier
"Maximum size exceeded"	Hard Limit	Split data or use alternative storage
"Too many requests"	Rate Limit	Implement retry logic or increase tier
"Cannot exceed X"	Hard Limit	Stay within limit or use multiple resources
"Subscription limit reached"	Quota	Request quota increase using azure-quotas skill
"Regional capacity"	Quota	Choose different region or request increase

Best Practices

MUST use Azure CLI quota API first: az quota commands are MANDATORY as the primary method for checking quotas - only use fallback methods (REST API, Portal, docs) when quota API returns BadRequest
Don't trust "No Limit" values: If REST API or Portal shows "No Limit" or unlimited, verify with official service documentation - it likely means the quota API doesn't support that resource type, not that capacity is unlimited
Always check after customer selects region: Validates availability and allows time for quota requests
Use the discovery workflow: Never assume quota resource names - always run az quota list first to discover correct names
Check both usage and limit: Run az quota usage show AND az quota show to calculate available capacity
Handle unsupported providers gracefully: If you get BadRequest error, fall back to official documentation (Azure Resource Graph + docs)
Request quota increases proactively: If selected region lacks capacity, submit request before deployment
Have alternative regions ready: If quota increase denied, suggest backup regions
Document capacity assumptions: Note quota availability and source in .azure/deployment-plan.md
Design for limits: Architecture should account for both hard limits and quotas
Monitor usage trends: Regular quota checks help predict future needs
Use lower environments wisely: Dev/test environments count against quotas

Quick Reference Limits

For complete quota checking workflow and commands, invoke the azure-quotas skill.

Note: These are typical default limits. Always verify actual quotas using az quota show for your specific subscription and region.

Common quotas to check:

Subscription Level

Cosmos DB accounts: 50 per region (check via docs - quota API not supported)
SQL logical servers: 250 per region
Service Bus namespaces: 100-1,000 (tier dependent)

Regional Level

Storage accounts: 250 per region (quota resource name: StorageAccounts)
AKS clusters: 5,000 per region (quota resource name: varies by configuration)
Container Apps environments: 50 per region (quota resource name: ManagedEnvironmentCount)
Function apps: 200 per region (Consumption)

Resource Level

Cosmos DB containers per account: Unlimited (subject to storage)
Apps per Container Apps environment: 500
Databases per SQL server: 500
Queues/topics per Service Bus namespace: 10,000

azure-quotas skill - Complete quota checking workflow and CLI commands (invoke the azure-quotas skill)
Azure subscription limits - Official Microsoft documentation
Azure Quotas Overview - Understanding quotas and limits
azure-context.md - How to confirm subscription and region
architecture.md - Architecture planning workflow

Example: Complete Check Workflow

# Scenario: Deploying app with Cosmos DB, Storage, and Container Apps
# Customer selected region: East US

# 1. Check Hard Limits (from azure-provisioning-limit skill)
# Cosmos DB: Item size max 2 MB ✓
# Storage: Blob size max 190.7 TiB ✓
# Container Apps: Timeout 240 sec ✓

# 2. Get Customer's Region Preference
# Customer: "I prefer East US"

# 3. Check Quotas for Customer's Selected Region (East US)

# 3a. Cosmos DB - NOT SUPPORTED by quota API
az quota list \
  --scope /subscriptions/abc-123/providers/Microsoft.DocumentDB/locations/eastus
# Error: (BadRequest) Bad request

# Fallback: Get current usage with Azure Resource Graph
# Install extension first (if needed)
az extension add --name resource-graph

az graph query -q "resources | where type == 'microsoft.documentdb/databaseaccounts' and location == 'eastus' | count"
# Result: 3 database accounts currently deployed

# Or use Azure CLI resource list
az resource list \
  --subscription "abc-123" \
  --resource-type "Microsoft.DocumentDB/databaseAccounts" \
  --location "eastus" | jq 'length'
# Result: 3

# Get limit from documentation: 50 database accounts per region
# Calculate: Available = 50 - 3 = 47 ✓
# Document as: "Fetched from: Azure Resource Graph + Official docs"

# 3b. Storage Accounts
# Step 1: Discover resource name
az quota list \
  --scope /subscriptions/abc-123/providers/Microsoft.Storage/locations/eastus

# Step 2: Check usage (use discovered name "StorageAccounts")
az quota usage show \
  --resource-name StorageAccounts \
  --scope /subscriptions/abc-123/providers/Microsoft.Storage/locations/eastus
# Current: 180

# Step 3: Check limit
az quota show \
  --resource-name StorageAccounts \
  --scope /subscriptions/abc-123/providers/Microsoft.Storage/locations/eastus
# Limit: 250
# Available: 250 - 180 = 70 ✓

# 3c. Container Apps
# Step 1: Discover resource name
az quota list \
  --scope /subscriptions/abc-123/providers/Microsoft.App/locations/eastus
# Shows: "ManagedEnvironmentCount"

# Step 2: Check usage
az quota usage show \
  --resource-name ManagedEnvironmentCount \
  --scope /subscriptions/abc-123/providers/Microsoft.App/locations/eastus
# Current: 8

# Step 3: Check limit
az quota show \
  --resource-name ManagedEnvironmentCount \
  --scope /subscriptions/abc-123/providers/Microsoft.App/locations/eastus
# Limit: 50
# Available: 50 - 8 = 42 ✓

# 4. Validate Availability
# ✅ All services have sufficient quota in East US
# ✅ Proceed with deployment

# Alternative: If quotas were insufficient
# ❌ Container Apps: 49/50 (only 1 available, need 3)
# Action: Request quota increase
# 
# az quota update \
#   --resource-name ManagedEnvironmentCount \
#   --scope /subscriptions/abc-123/providers/Microsoft.App/locations/eastus \
#   --limit-object value=100 \
#   --resource-type Microsoft.App/managedEnvironments

Remember: Checking limits and quotas early prevents deployment failures and ensures smooth infrastructure provisioning.

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 Python

Security

What our scanner noticed· Medium risk

Instructions that use the network
Downloads piped into a shell
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-prepare · commit 0696600

Licence

MIT License (redistribution allowed)

LICENSE (added by AutoGineer from .github/plugins/azure-skills/LICENSE)
ATTRIBUTION.md (written by AutoGineer)

Synced

2026-11-09

Also distributed in

microsoft/azure-skills

AutoGineer is not affiliated with or endorsed by Microsoft or Microsoft.

Download ZIP

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

From the author

AutoGineer summary

What it does

When to use it

Advantages

Usage examples

Install

Documentation by Microsoft

Azure Prepare

Triggers

Rules

❌ PLAN-FIRST WORKFLOW — MANDATORY

❌ STEP 0: Specialized Technology Check — MANDATORY FIRST ACTION

Check 1: Prompt keywords

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

Phase 2: Execution (Only After Plan Approval)

Outputs

SDK Quick References

Next

Files

references/resources-limits-quotas.md

Azure Resource Limits and Quotas

Types

Hard Limits

Quotas

Workflow

Limit Scopes

Service Patterns

CLI Reference

azure-prepare Integration

Error Messages

Best Practices

Quick Reference Limits

Subscription Level

Regional Level

Resource Level

Related Documentation

Example: Complete Check Workflow

Requirements and compatibility

Security

Attribution and licence

Related skills

Modal

Cloud Infrastructure Network Engineer

Deployment Validation Cloud Architect

Airflow Dag Patterns

Cost Optimization

Hybrid Cloud Networking

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