Azure Functions workflow skill. Use this skill when the user needs Expert patterns for Azure Functions development including isolated and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
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Azure Functions workflow skill. Use this skill when the user needs Expert patterns for Azure Functions development including isolated and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off.
This public intake copy packages plugins/antigravity-awesome-skills/skills/azure-functions from https://github.com/sickn33/antigravity-awesome-skills into the native Omni Skills editorial shape without hiding its origin.
Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.
This intake keeps the copied upstream files intact and uses the external_source block in metadata.json plus ORIGIN.md as the provenance anchor for review.
Azure Functions Expert patterns for Azure Functions development including isolated worker model, Durable Functions orchestration, cold start optimization, and production patterns. Covers .NET, Python, and Node.js programming models.
Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Patterns, Sharp Edges, Use async pattern with Durable Functions, Use queue-based async pattern, Use webhook callback pattern, Use IHttpClientFactory (Recommended).
When to Use This Skill
Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.
User mentions or implies: azure function
User mentions or implies: azure functions
User mentions or implies: durable functions
User mentions or implies: azure serverless
User mentions or implies: function app
Use when the request clearly matches the imported source intent: Expert patterns for Azure Functions development including isolated.
Operating Table
Situation
Start here
Why it matters
First-time use
metadata.json
Confirms repository, branch, commit, and imported path through the external_source block before touching the copied workflow
Provenance review
ORIGIN.md
Gives reviewers a plain-language audit trail for the imported source
Workflow execution
SKILL.md
Starts with the smallest copied file that materially changes execution
Supporting context
SKILL.md
Adds the next most relevant copied source file without loading the entire package
Handoff decision
## Related Skills
Helps the operator switch to a stronger native skill when the task drifts
Workflow
This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.
Only one pre-warmed instance by default
Rapid scale-out still creates cold instances
Pre-warmed instances still run YOUR code initialization
Warmup trigger runs, but your code may still be slow
Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
Read the overview and provenance files before loading any copied upstream support files.
Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
Imported Workflow Notes
Imported: Use Durable Functions for long workflows
[Function("LongWorkflowOrchestrator")]
publicstaticasync Task<string> RunOrchestrator(
[OrchestrationTrigger] TaskOrchestrationContext context)
{
// Each activity has its own timeout// Workflow can run for daysawait context.CallActivityAsync("Step1", input);
await context.CallActivityAsync("Step2", input);
await context.CallActivityAsync("Step3", input);
return"Complete";
}
Imported: Install explicit packages for isolated worker
<!-- .csproj - Isolated worker packages --><PackageReferenceInclude="Microsoft.Azure.Functions.Worker"Version="1.20.0" /><PackageReferenceInclude="Microsoft.Azure.Functions.Worker.Sdk"Version="1.16.0" /><!-- Storage triggers/bindings --><PackageReferenceInclude="Microsoft.Azure.Functions.Worker.Extensions.Storage"Version="6.2.0" /><!-- Service Bus --><PackageReferenceInclude="Microsoft.Azure.Functions.Worker.Extensions.ServiceBus"Version="5.14.0" /><!-- Cosmos DB --><PackageReferenceInclude="Microsoft.Azure.Functions.Worker.Extensions.CosmosDB"Version="4.6.0" /><!-- Durable Functions --><PackageReferenceInclude="Microsoft.Azure.Functions.Worker.Extensions.DurableTask"Version="1.1.0" />
Imported: Verify function registration
# Check registered functions
func host start --verbose
# Look for:# "Found the following functions:"# If empty, check extensions and attributes
Premium Plan Still Has Cold Start on New Instances
Severity: MEDIUM
Situation: Using Premium plan expecting zero cold start
Symptoms:
Still experiencing cold starts despite Premium plan.
First request to new instance is slow.
Latency spikes during scale-out events.
Pre-warmed instances not being used.
Why this breaks:
Premium plan provides pre-warmed instances, but:
Only one pre-warmed instance by default
Rapid scale-out still creates cold instances
Pre-warmed instances still run YOUR code initialization
Warmup trigger runs, but your code may still be slow
Pre-warmed means the runtime is ready, not your application.
Recommended fix:
Imported: Patterns
Isolated Worker Model (.NET)
Modern .NET execution model with process isolation
When to use: Building new .NET Azure Functions apps
Template
// Program.cs - Isolated Worker Model
using Microsoft.Azure.Functions.Worker;
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
var host = new HostBuilder()
.ConfigureFunctionsWorkerDefaults()
.ConfigureServices(services =>
{
// Add Application Insights
services.AddApplicationInsightsTelemetryWorkerService();
services.ConfigureFunctionsApplicationInsights();
When to use: Need sequential workflow with automatic retry
Template
// C# Isolated Worker - Function Chaining
using Microsoft.Azure.Functions.Worker;
using Microsoft.DurableTask;
using Microsoft.DurableTask.Client;
public class OrderWorkflow
{
[Function("OrderOrchestrator")]
public static async Task RunOrchestrator(
[OrchestrationTrigger] TaskOrchestrationContext context)
{
var order = context.GetInput();
// Functions execute sequentially, state persisted between each
var validated = await context.CallActivityAsync<ValidatedOrder>(
"ValidateOrder", order);
var payment = await context.CallActivityAsync<PaymentResult>(
"ProcessPayment", validated);
var shipped = await context.CallActivityAsync<ShippingResult>(
"ShipOrder", new ShipRequest { Order = validated, Payment = payment });
var notification = await context.CallActivityAsync<bool>(
"SendNotification", shipped);
return new OrderResult
{
OrderId = order.Id,
Status = "Completed",
TrackingNumber = shipped.TrackingNumber
};
}
[Function("ValidateOrder")]
public static async Task<ValidatedOrder> ValidateOrder(
[ActivityTrigger] Order order, FunctionContext context)
{
var logger = context.GetLogger<OrderWorkflow>();
logger.LogInformation("Validating order {OrderId}", order.Id);
// Validation logic...
return new ValidatedOrder { /* ... */ };
}
[Function("ProcessPayment")]
public static async Task<PaymentResult> ProcessPayment(
[ActivityTrigger] ValidatedOrder order, FunctionContext context)
{
// Payment processing with built-in retry...
return new PaymentResult { /* ... */ };
}
[Function("OrderWorkflow_HttpStart")]
public static async Task<HttpResponseData> HttpStart(
[HttpTrigger(AuthorizationLevel.Function, "post")] HttpRequestData req,
[DurableClient] DurableTaskClient client,
FunctionContext context)
{
var order = await req.ReadFromJsonAsync<Order>();
string instanceId = await client.ScheduleNewOrchestrationInstanceAsync(
"OrderOrchestrator", order);
return client.CreateCheckStatusResponse(req, instanceId);
}
}
Notes
State automatically persisted between activities
Automatic retry on transient failures
Survives process restarts
Built-in status endpoint for monitoring
Durable Functions - Fan-Out/Fan-In
Parallel execution with result aggregation
When to use: Processing multiple items in parallel
Template
// C# Isolated Worker - Fan-Out/Fan-In
using Microsoft.Azure.Functions.Worker;
using Microsoft.DurableTask;
public class ParallelProcessing
{
[Function("ProcessImagesOrchestrator")]
public static async Task RunOrchestrator(
[OrchestrationTrigger] TaskOrchestrationContext context)
{
var images = context.GetInput<List>();
// Fan-out: Start all tasks in parallel
var tasks = images.Select(image =>
context.CallActivityAsync<ImageResult>("ProcessImage", image));
// Fan-in: Wait for all tasks to complete
var results = await Task.WhenAll(tasks);
// Aggregate results
var successful = results.Count(r => r.Success);
var failed = results.Count(r => !r.Success);
return new ProcessingResult
{
TotalProcessed = results.Length,
Successful = successful,
Failed = failed,
Results = results.ToList()
};
}
[Function("ProcessImage")]
public static async Task<ImageResult> ProcessImage(
[ActivityTrigger] string imageUrl, FunctionContext context)
{
var logger = context.GetLogger<ParallelProcessing>();
logger.LogInformation("Processing image: {Url}", imageUrl);
try
{
// Image processing logic...
await Task.Delay(1000); // Simulated work
return new ImageResult
{
Url = imageUrl,
Success = true,
ProcessedUrl = $"processed-{imageUrl}"
};
}
catch (Exception ex)
{
logger.LogError(ex, "Failed to process {Url}", imageUrl);
return new ImageResult { Url = imageUrl, Success = false };
}
}
// Python equivalent
// @app.orchestration_trigger(context_name="context")
// def process_images_orchestrator(context: df.DurableOrchestrationContext):
// images = context.get_input()
//
// # Fan-out: Create parallel tasks
// tasks = [context.call_activity("ProcessImage", img) for img in images]
//
// # Fan-in: Wait for all
// results = yield context.task_all(tasks)
//
// return {"processed": len(results), "results": results}
}
Notes
Parallel execution for independent tasks
Results aggregated when all complete
Memory efficient - only stores task IDs
Up to thousands of parallel activities
Cold Start Optimization
Minimize cold start latency in production
When to use: Need fast response times in production
Template
// 1. Use Premium Plan with pre-warmed instances
// host.json
{
"version": "2.0",
"extensions": {
"durableTask": {
"hubName": "MyTaskHub"
}
},
"functionTimeout": "00:30:00"
}
// Pre-initialize expensive resources
// Database connections, HttpClients, etc.
}
// 3. Use static/singleton clients with DI
public class Startup
{
public void ConfigureServices(IServiceCollection services)
{
// HttpClientFactory prevents socket exhaustion
services.AddHttpClient<IMyApiClient, MyApiClient>(client =>
{
client.BaseAddress = new Uri("https://api.example.com");
client.Timeout = TimeSpan.FromSeconds(30);
});
// Singleton for expensive initialization
services.AddSingleton<IExpensiveService>(sp =>
{
// Initialize once, reuse across invocations
return new ExpensiveService();
});
}
// Alternative: Queue-based pattern without Durable Functions
[Function("StartWork")]
[QueueOutput("work-queue")]
public static async Task StartWork(
[HttpTrigger(AuthorizationLevel.Function, "post")] HttpRequestData req,
FunctionContext context)
{
var input = await req.ReadFromJsonAsync();
var workId = Guid.NewGuid().ToString();
// Queue the work, return immediately
var workItem = new WorkItem
{
Id = workId,
Request = input
};
// Return work ID for status checking
var response = req.CreateResponse(HttpStatusCode.Accepted);
await response.WriteAsJsonAsync(new
{
workId = workId,
statusUrl = $"/api/status/{workId}"
});
return workItem;
}
[Function("ProcessWork")]
public static async Task ProcessWork(
[QueueTrigger("work-queue")] WorkItem work,
FunctionContext context)
{
// Long-running processing here
// Update status in storage for polling
}
Notes
HTTP timeout is 230 seconds regardless of plan
Use Durable Functions for async patterns
Return immediately with status endpoint
Client polls for completion
Examples
Example 1: Ask for the upstream workflow directly
Use @azure-functions-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
Explanation: This is the safest starting point when the operator needs the imported workflow, but not the entire repository.
Example 2: Ask for a provenance-grounded review
Review @azure-functions-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
Explanation: Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.
Example 3: Narrow the copied support files before execution
Use @azure-functions-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
Explanation: This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.
Example 4: Build a reviewer packet
Review @azure-functions-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.
Explanation: This is useful when the PR is waiting for human review and you want a repeatable audit packet.
Best Practices
Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.
Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
Treat generated examples as scaffolding; adapt them to the concrete task before execution.
Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.
Troubleshooting
Problem: The operator skipped the imported context and answered too generically
Symptoms: The result ignores the upstream workflow in plugins/antigravity-awesome-skills/skills/azure-functions, fails to mention provenance, or does not use any copied source files at all.
Solution: Re-open metadata.json, ORIGIN.md, and the most relevant copied upstream files. Check the external_source block first, then restate the provenance before continuing.
Problem: The imported workflow feels incomplete during review
Symptoms: Reviewers can see the generated SKILL.md, but they cannot quickly tell which references, examples, or scripts matter for the current task.
Solution: Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.
Problem: The task drifted into a different specialization
Symptoms: The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
Solution: Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.
Related Skills
@00-andruia-consultant - Use when the work is better handled by that native specialization after this imported skill establishes context.
@00-andruia-consultant-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith - Use when the work is better handled by that native specialization after this imported skill establishes context.
@10-andruia-skill-smith-v2 - Use when the work is better handled by that native specialization after this imported skill establishes context.
Additional Resources
Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.
Resource family
What it gives the reviewer
Example path
references
copied reference notes, guides, or background material from upstream
references/n/a
examples
worked examples or reusable prompts copied from upstream
examples/n/a
scripts
upstream helper scripts that change execution or validation
scripts/n/a
agents
routing or delegation notes that are genuinely part of the imported package
agents/n/a
assets
supporting assets or schemas copied from the source package
assets/n/a
Imported Reference Notes
Imported: Sharp Edges
HTTP Timeout is 230 Seconds Regardless of Plan
Severity: HIGH
Situation: HTTP-triggered functions with long processing time
Symptoms:
504 Gateway Timeout after ~4 minutes.
Request terminates before function completes.
Client receives timeout even though function continues.
host.json timeout setting has no effect for HTTP.
Why this breaks:
The Azure Load Balancer has a hard-coded 230-second idle timeout for HTTP
requests. This applies regardless of your function app timeout setting.
Even if you set functionTimeout to 30 minutes in host.json, HTTP triggers
will timeout after 230 seconds from the client's perspective.
The function may continue running after timeout, but the client won't
receive the response.
Recommended fix:
Imported: Use async pattern with Durable Functions
[Function("StartWork")]
publicstaticasync Task<HttpResponseData> StartWork(
[HttpTrigger(AuthorizationLevel.Function, "post")] HttpRequestData req,
[QueueOutput("work-queue")] out WorkItem workItem)
{
var workId = Guid.NewGuid().ToString();
workItem = new WorkItem { Id = workId, /* ... */ };
var response = req.CreateResponse(HttpStatusCode.Accepted);
await response.WriteAsJsonAsync(new {
id = workId,
statusUrl = $"/api/status/{workId}"
});
return response;
}
Imported: Use webhook callback pattern
// Client provides callback URL// Function queues work, returns 202 Accepted// When done, POST result to callback URL
Socket Exhaustion from HttpClient Instantiation
Severity: HIGH
Situation: Creating HttpClient instances inside function code
Symptoms:
SocketException: "Unable to connect to remote server"
"An attempt was made to access a socket in a way forbidden"
Sporadic connection failures under load.
Works locally but fails in production.
Why this breaks:
Creating a new HttpClient for each request creates a new socket connection.
Sockets linger in TIME_WAIT state for 240 seconds after closing.
In a serverless environment with high throughput, you quickly exhaust
available sockets. This affects all network clients, not just HttpClient.
Azure Functions shares network resources among multiple customers,
making this even more critical.
publicstaticclassMyFunction
{
// Static HttpClient, reused across invocationsprivatestaticreadonly HttpClient _httpClient = new HttpClient
{
Timeout = TimeSpan.FromSeconds(30)
};
[Function("MyFunction")]
publicstaticasync Task Run(...)
{
var result = await _httpClient.GetAsync("...");
}
}
Imported: Same pattern for Azure SDK clients
// Also applies to:// - BlobServiceClient// - CosmosClient// - ServiceBusClient// Use DI or static instances
Blocking Async Calls Cause Thread Starvation
Severity: HIGH
Situation: Using .Result, .Wait(), or Thread.Sleep in async code
Symptoms:
Deadlocks under load.
Requests hang indefinitely.
"A task was canceled" exceptions.
Works with low concurrency, fails with high.
Why this breaks:
Azure Functions thread pool is limited. Blocking calls (.Result, .Wait())
hold a thread hostage while waiting, preventing other work.
Thread.Sleep blocks a thread that could be handling other requests.
With multiple concurrent executions, you quickly run out of threads,
causing deadlocks and timeouts.
Recommended fix:
Imported: Always use async/await
// BAD - blocks threadvar result = httpClient.GetAsync(url).Result;
someTask.Wait();
Thread.Sleep(5000);
// GOOD - yields threadvar result = await httpClient.GetAsync(url);
await someTask;
await Task.Delay(5000);
Imported: Fix synchronous method calls
// BAD - sync over asyncpublicvoidProcessData()
{
var data = GetDataAsync().Result; // Blocks!
}
// GOOD - async all the waypublicasync Task ProcessDataAsync()
{
var data = await GetDataAsync();
}
Imported: Configure async in console/startup
// If you must call async from sync contextpublicstaticvoidMain(string[] args)
{
// Use GetAwaiter().GetResult() at entry point only
MainAsync(args).GetAwaiter().GetResult();
}
privatestaticasync Task MainAsync(string[] args)
{
// Async code here
}
Consumption Plan 10-Minute Timeout Limit
Severity: MEDIUM
Situation: Running long processes on Consumption plan
Symptoms:
Function terminates after 10 minutes.
"Function timed out" in logs.
Incomplete processing with no error caught.
Works in development (with longer timeout) but fails in production.
Why this breaks:
Consumption plan has a hard limit of 10 minutes execution time.
Default is 5 minutes if not configured.
This cannot be increased beyond 10 minutes on Consumption plan.
Long-running work requires Premium plan or different architecture.
Recommended fix:
Imported: Configure maximum timeout (Consumption)
// host.json{"version":"2.0","functionTimeout":"00:10:00"// Max for Consumption}
Imported: Upgrade to Premium plan for longer timeouts
// Premium plan - 30 min default, unbounded available{"version":"2.0","functionTimeout":"00:30:00"// Or remove for unbounded}
Imported: Break work into smaller chunks
// Queue-based chunking
[Function("ProcessChunk")]
[QueueOutput("work-queue")]
publicstatic IEnumerable<WorkChunk> ProcessChunk(
[QueueTrigger("work-queue")] WorkChunk chunk)
{
var results = Process(chunk);
// Queue next chunks if more workif (chunk.HasMore)
{
yieldreturn chunk.Next();
}
}
.NET In-Process Model Deprecated November 2026
Severity: HIGH
Situation: Creating new .NET functions or maintaining existing
Symptoms:
Using in-process model in new projects.
Dependency conflicts with host runtime.
Cannot use latest .NET versions.
Future migration burden.
Why this breaks:
The in-process model runs your code in the same process as the
Azure Functions host. This causes:
Assembly version conflicts
Limited to LTS .NET versions
No access to latest .NET features
Tighter coupling with host runtime
Support ends November 10, 2026. After this date, in-process apps
may stop working or receive no security updates.
Recommended fix:
Imported: Use isolated worker for new projects
# Create new isolated worker project
func init MyFunctionApp --worker-runtime dotnet-isolated
# Or with .NET 8
dotnet new func --name MyFunctionApp --framework net8.0
Imported: Key migration changes
FunctionName → Function attribute
HttpRequest → HttpRequestData
IActionResult → HttpResponseData
ILogger injection → constructor injection
Add Program.cs with HostBuilder
ILogger Not Outputting to Console or AppInsights
Severity: MEDIUM
Situation: Using dependency-injected ILogger in isolated worker
Symptoms:
Logs not appearing in local console.
Logs not appearing in Application Insights.
Logs work with context.GetLogger() but not injected ILogger.
Must pass logger through all method calls.
Why this breaks:
In isolated worker model, the dependency-injected ILogger may not
be properly connected to the Azure Functions logging pipeline.
Local development especially affected - logs may go nowhere.
Application Insights requires explicit configuration.
The ILogger from FunctionContext works differently than
the injected ILogger.
Situation: Using triggers/bindings without installing extensions
Symptoms:
Function not triggering on events.
"No job functions found" warning.
Bindings not working despite correct configuration.
Works after adding extension package.
Why this breaks:
Azure Functions v2+ uses extension bundles for triggers and bindings.
If extensions aren't properly configured or packages aren't installed,
the function host can't recognize the bindings.
In isolated worker, you need explicit NuGet packages.
In in-process, you need Microsoft.Azure.WebJobs.Extensions.*.
Recommended fix:
Imported: Check extension bundle (most common)
// host.json - Extension bundles handle most cases{"version":"2.0","extensionBundle":{"id":"Microsoft.Azure.Functions.ExtensionBundle","version":"[4.*, 5.0.0)"}}
Imported: Configure pre-warmed instance count
# Increase pre-warmed instances (costs more)
az functionapp config set \
--name <app-name> \
--resource-group <rg> \
--prewarmed-instance-count 3
Imported: Optimize application initialization
// Lazy initialize heavy resourcesprivatestaticreadonly Lazy<ExpensiveClient> _client =
new Lazy<ExpensiveClient>(() => new ExpensiveClient());
// Connection pooling
services.AddDbContext<MyDbContext>(options =>
options.UseSqlServer(connectionString, sql =>
sql.MinPoolSize(5)));
Imported: Use always-ready instances (most expensive)
# Instances always running, no cold start
az functionapp config set \
--name <app-name> \
--resource-group <rg> \
--minimum-elastic-instance-count 2
Imported: Validation Checks
Hardcoded Connection String
Severity: ERROR
Connection strings must never be hardcoded
Message: Hardcoded connection string. Use Key Vault or App Settings.
Hardcoded API Key in Code
Severity: ERROR
API keys should use Key Vault or App Settings
Message: Hardcoded API key. Use Key Vault or environment variables.
Anonymous Authorization Level in Production
Severity: WARNING
Anonymous endpoints should be protected by other means
Message: Anonymous authorization. Ensure protected by API Management or other auth.
Blocking .Result Call
Severity: ERROR
Using .Result blocks threads and causes deadlocks
Message: Blocking .Result call. Use await instead.
Blocking .Wait() Call
Severity: ERROR
Using .Wait() blocks threads
Message: Blocking .Wait() call. Use await instead.
Thread.Sleep Usage
Severity: ERROR
Thread.Sleep blocks threads
Message: Thread.Sleep blocks threads. Use await Task.Delay() instead.
New HttpClient Instance
Severity: WARNING
Creating HttpClient per request causes socket exhaustion
Message: New HttpClient per request. Use IHttpClientFactory or static client.
HttpClient in Using Statement
Severity: WARNING
Disposing HttpClient causes socket exhaustion
Message: HttpClient in using statement. Use IHttpClientFactory for proper lifecycle.
In-Process FunctionName Attribute
Severity: INFO
In-process model deprecated November 2026
Message: In-process FunctionName attribute. Consider migrating to isolated worker.
Missing Function Attribute
Severity: WARNING
Isolated worker requires [Function] attribute
Message: HttpTrigger without [Function] attribute (isolated worker requires it).
Imported: Collaboration
Delegation Triggers
user needs AWS serverless -> aws-serverless (Lambda, API Gateway, SAM)
user needs GCP serverless -> gcp-cloud-run (Cloud Run, Cloud Functions)
user needs container-based deployment -> gcp-cloud-run (Azure Container Apps or Cloud Run)
user needs database design -> postgres-wizard (Azure SQL, Cosmos DB data modeling)
