Worker Services logo

Worker Services

Organization
managedcode
worker-services

Build long-running .NET background services with `BackgroundService`, Generic Host, graceful shutdown, configuration, logging, and deployment patterns suited to workers and daemons. USE FOR: background services; scheduled workers; hosted services; worker extraction; graceful shutdown, health checks, and service hosting review. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

Overview

Publishermanagedcode
Repositorydotnet-skills
Skill nameworker-services
Stars
492
Forks
38
Bundled files
3
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by managedcode on GitHub. Read the source before you install it.

Installation

Install the Worker Services AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/managedcode/dotnet-skills/tree/main/catalog/Frameworks/Worker-Services/skills/worker-services
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/managedcode/dotnet-skills.git /tmp/dotnet-skills
mkdir -p .claude/skills
cp -r /tmp/dotnet-skills/catalog/Frameworks/Worker-Services/skills/worker-services .claude/skills/worker-services
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Worker Services in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Worker Services on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Worker Services is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

.NET Worker Services

Trigger On

  • building long-running background services or scheduled workers
  • adding hosted services to an app or extracting them into a worker process
  • reviewing graceful shutdown, cancellation, queue processing, or health behavior

Documentation

References

  • patterns.md - BackgroundService patterns, graceful shutdown, and health check implementations
  • anti-patterns.md - Common worker service mistakes and how to avoid them

Workflow

  1. Use BackgroundService as your base class:

    • Provides standard StartAsync/StopAsync handling
    • Focus on implementing ExecuteAsync only
    • Proper cancellation token management built-in
  2. Handle scoped dependencies correctly:

    • Create service scopes for scoped services
    • No scope is created by default in hosted services
  3. Implement graceful shutdown:

    • Propagate cancellation tokens throughout
    • Complete work promptly when token fires
    • Avoid ungraceful shutdown at timeout
  4. Keep execution loop thin:

    • Move business logic to testable services
    • Handle exceptions to prevent service crashes
    • Use PeriodicTimer for scheduled work
  5. Add observability:

    • Use health checks for readiness/liveness
    • Expose metrics and structured logging
    • Consider distributed locks for multi-instance

Current Upstream Notes

  • .NET runtime v10.0.11 is servicing. For workers, rerun cgroup-v2 memory-limit detection, cancellation, graceful shutdown, long-running thread-static and GC paths, NativeAOT/WASM startup where relevant, and Windows directory enumeration after upgrading rather than changing architecture by default.
  • Use the refreshed Worker Services and hosted-service Learn pages for exact current hosting and health-check APIs when adding new worker entry points.

Basic BackgroundService Pattern

Simple Worker

csharp
public class Worker : BackgroundService
{
    private readonly ILogger<Worker> _logger;

    public Worker(ILogger<Worker> logger)
    {
        _logger = logger;
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        _logger.LogInformation("Worker starting");

        while (!stoppingToken.IsCancellationRequested)
        {
            try
            {
                _logger.LogInformation("Worker running at: {Time}", DateTimeOffset.Now);
                await DoWorkAsync(stoppingToken);
                await Task.Delay(TimeSpan.FromSeconds(5), stoppingToken);
            }
            catch (OperationCanceledException) when (stoppingToken.IsCancellationRequested)
            {
                // Graceful shutdown, not an error
                break;
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, "Error in worker iteration");
                // Continue or break based on error severity
            }
        }

        _logger.LogInformation("Worker stopping");
    }

    private async Task DoWorkAsync(CancellationToken cancellationToken)
    {
        // Business logic here
    }
}

Using PeriodicTimer (Recommended)

csharp
public class TimedWorker : BackgroundService
{
    private readonly ILogger<TimedWorker> _logger;
    private readonly IServiceScopeFactory _scopeFactory;
    private readonly TimeSpan _period = TimeSpan.FromMinutes(1);

    public TimedWorker(ILogger<TimedWorker> logger, IServiceScopeFactory scopeFactory)
    {
        _logger = logger;
        _scopeFactory = scopeFactory;
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        using var timer = new PeriodicTimer(_period);

        while (await timer.WaitForNextTickAsync(stoppingToken))
        {
            try
            {
                await using var scope = _scopeFactory.CreateAsyncScope();
                var processor = scope.ServiceProvider.GetRequiredService<IDataProcessor>();
                await processor.ProcessAsync(stoppingToken);
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, "Error processing scheduled task");
            }
        }
    }
}

Handling Scoped Dependencies

Correct Pattern with Scope Factory

csharp
public class ScopedWorker : BackgroundService
{
    private readonly IServiceScopeFactory _scopeFactory;
    private readonly ILogger<ScopedWorker> _logger;

    public ScopedWorker(IServiceScopeFactory scopeFactory, ILogger<ScopedWorker> logger)
    {
        _scopeFactory = scopeFactory;
        _logger = logger;
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        while (!stoppingToken.IsCancellationRequested)
        {
            // Create scope for each unit of work
            await using var scope = _scopeFactory.CreateAsyncScope();

            var dbContext = scope.ServiceProvider.GetRequiredService<AppDbContext>();
            var service = scope.ServiceProvider.GetRequiredService<IScopedService>();

            await service.ProcessAsync(dbContext, stoppingToken);
            await Task.Delay(TimeSpan.FromSeconds(10), stoppingToken);
        }
    }
}

Queue Processing Pattern

Message Queue Worker

csharp
public class QueueWorker : BackgroundService
{
    private readonly ILogger<QueueWorker> _logger;
    private readonly IServiceScopeFactory _scopeFactory;
    private readonly IBackgroundTaskQueue _taskQueue;

    public QueueWorker(
        ILogger<QueueWorker> logger,
        IServiceScopeFactory scopeFactory,
        IBackgroundTaskQueue taskQueue)
    {
        _logger = logger;
        _scopeFactory = scopeFactory;
        _taskQueue = taskQueue;
    }

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        _logger.LogInformation("Queue Worker started");

        while (!stoppingToken.IsCancellationRequested)
        {
            var workItem = await _taskQueue.DequeueAsync(stoppingToken);

            try
            {
                await using var scope = _scopeFactory.CreateAsyncScope();
                await workItem(scope.ServiceProvider, stoppingToken);
            }
            catch (Exception ex)
            {
                _logger.LogError(ex, "Error processing queued work item");
                // Handle poison message - retry, dead-letter, etc.
            }
        }
    }
}

// Task queue interface
public interface IBackgroundTaskQueue
{
    ValueTask QueueBackgroundWorkItemAsync(
        Func<IServiceProvider, CancellationToken, ValueTask> workItem);

    ValueTask<Func<IServiceProvider, CancellationToken, ValueTask>> DequeueAsync(
        CancellationToken cancellationToken);
}

Health Checks for Workers

Adding Health Check Endpoint

csharp
// Program.cs
var builder = Host.CreateApplicationBuilder(args);

builder.Services.AddHostedService<Worker>();

// Add health checks
builder.Services.AddHealthChecks()
    .AddCheck<WorkerHealthCheck>("worker_health")
    .AddResourceUtilizationHealthCheck();

// Add HTTP endpoint for health checks
builder.Services.AddHealthChecksUI();

// Or use simple TCP listener for Kubernetes
builder.Services.AddSingleton<TcpHealthProbeService>();
builder.Services.AddHostedService(sp => sp.GetRequiredService<TcpHealthProbeService>());

var host = builder.Build();
host.Run();

Custom Health Check

csharp
public class WorkerHealthCheck : IHealthCheck
{
    private readonly WorkerState _workerState;

    public WorkerHealthCheck(WorkerState workerState)
    {
        _workerState = workerState;
    }

    public Task<HealthCheckResult> CheckHealthAsync(
        HealthCheckContext context,
        CancellationToken cancellationToken = default)
    {
        if (_workerState.LastSuccessfulRun > DateTime.UtcNow.AddMinutes(-5))
        {
            return Task.FromResult(HealthCheckResult.Healthy(
                $"Last successful run: {_workerState.LastSuccessfulRun}"));
        }

        return Task.FromResult(HealthCheckResult.Unhealthy(
            $"No successful run since: {_workerState.LastSuccessfulRun}"));
    }
}

// Shared state
public class WorkerState
{
    public DateTime LastSuccessfulRun { get; set; } = DateTime.UtcNow;
    public bool IsProcessing { get; set; }
}

Graceful Shutdown Pattern

Proper Shutdown Handling

csharp
public class GracefulWorker : BackgroundService
{
    private readonly ILogger<GracefulWorker> _logger;
    private int _currentWorkItemId;

    protected override async Task ExecuteAsync(CancellationToken stoppingToken)
    {
        _logger.LogInformation("Worker starting");

        while (!stoppingToken.IsCancellationRequested)
        {
            _currentWorkItemId = GetNextWorkItemId();

            try
            {
                // Pass cancellation token to all async operations
                await ProcessWorkItemAsync(_currentWorkItemId, stoppingToken);
            }
            catch (OperationCanceledException) when (stoppingToken.IsCancellationRequested)
            {
                _logger.LogInformation(
                    "Shutdown requested, stopping after work item {Id}", _currentWorkItemId);
                break;
            }
        }
    }

    public override async Task StopAsync(CancellationToken cancellationToken)
    {
        _logger.LogInformation("Worker stopping gracefully");
        await base.StopAsync(cancellationToken);
        _logger.LogInformation("Worker stopped");
    }
}

Windows Service Deployment

Configuring as Windows Service

csharp
// Program.cs
var builder = Host.CreateApplicationBuilder(args);

builder.Services.AddWindowsService(options =>
{
    options.ServiceName = "My Worker Service";
});

builder.Services.AddHostedService<Worker>();

var host = builder.Build();
host.Run();

Project File Settings

xml
<Project Sdk="Microsoft.NET.Sdk.Worker">
  <PropertyGroup>
    <TargetFramework>net8.0</TargetFramework>
    <RuntimeIdentifier>win-x64</RuntimeIdentifier>
    <PublishSingleFile>true</PublishSingleFile>
    <SelfContained>true</SelfContained>
  </PropertyGroup>
</Project>

Best Practices

  1. Use BackgroundService as base class - Handles StartAsync/StopAsync boilerplate and cancellation management
  2. Create scopes for scoped dependencies - Use IServiceScopeFactory to resolve scoped services like DbContext
  3. Propagate cancellation tokens everywhere - Pass to all async methods for responsive shutdown
  4. Wrap work in try-catch - Unhandled exceptions stop the service completely
  5. Use PeriodicTimer for timed tasks - Cleaner than Task.Delay with proper cancellation support
  6. Add health checks - Essential for Kubernetes liveness/readiness probes
  7. Avoid blocking StartAsync - Long initialization delays other hosted services
  8. Call base methods when overriding - Always call await base.StartAsync() and await base.StopAsync()
  9. Publish as single file for Windows Service - Reduces deployment complexity and errors
  10. Consider scaling requirements - Separate worker projects if independent scaling is needed

Anti-Patterns to Avoid

Anti-PatternWhy It's BadBetter Approach
Ad-hoc while(true) loopsNo graceful shutdown, poor lifecycleUse BackgroundService
Ignoring cancellation tokenUngraceful shutdown, resource leaksPropagate token to all async calls
Injecting scoped services directlyCaptive dependencies, memory leaksUse IServiceScopeFactory
Unhandled exceptions in ExecuteAsyncSilently stops the workerWrap in try-catch, log, continue
Long-running StartAsyncBlocks other services from startingMove work to ExecuteAsync
async void methodsCrashes process on exceptionUse async Task
Missing health checksNo visibility into worker statusImplement IHealthCheck
Polling with tight loopsCPU waste, no responsivenessUse PeriodicTimer or event-driven
Not overriding StopAsyncMissed cleanup opportunityOverride for graceful cleanup
Singleton DbContextNot thread-safe, stale dataCreate scopes per operation

Deliver

  • well-behaved worker processes and hosted services
  • predictable startup and shutdown behavior
  • proper scoped dependency handling
  • health checks for production observability
  • retry and poison-message handling for queue work

Validate

  • cancellation token propagated and shutdown honored
  • scoped services resolved within proper scopes
  • exception handling prevents service crashes
  • health checks report accurate worker status
  • runtime behavior visible through logs or telemetry
  • no blocking calls in async context

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Worker Services AI skill do?

Build long-running .NET background services with `BackgroundService`, Generic Host, graceful shutdown, configuration, logging, and deployment patterns suited to workers and daemons. USE FOR: background services; scheduled workers; hosted services; worker extraction; graceful shutdown, health checks, and service hosting review. DO NOT USE FOR: unrelated stacks; generic tasks that do not need this specific guidance. INVOKES: inspect the repository context, edit targeted files, and run relevant build, test, lint, or validation commands when changes are made.

Why use Worker Services on TypingMind?

Because you install it once and use it with any model. Worker Services is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Worker Services in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/managedcode/dotnet-skills/tree/main/catalog/Frameworks/Worker-Services/skills/worker-services. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Worker Services?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Worker Services?

As many as you like. As long as a model supports skills, you can use Worker Services with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Worker Services AI skill free?

Yes. It is published on GitHub by managedcode under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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