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Dotnet Core Expert

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Jeffallan
dotnet-core-expert

Use when building .NET 8 applications with minimal APIs, clean architecture, or cloud-native microservices. Invoke for Entity Framework Core, CQRS with MediatR, JWT authentication, AOT compilation.

Overview

PublisherJeffallan
Repositoryclaude-skills
Skill namedotnet-core-expert
Stars
11.5K
Forks
1.1K
Bundled files
5
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.

  • 5 bundled files

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

  • Open source

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

Installation

Install the Dotnet Core Expert 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.
  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/Jeffallan/claude-skills.git /tmp/claude-skills
mkdir -p .claude/skills
cp -r /tmp/claude-skills/skills/dotnet-core-expert .claude/skills/dotnet-core-expert
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dotnet Core Expert 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 Dotnet Core Expert 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 Dotnet Core Expert 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 Core Expert

Core Workflow

  1. Analyze requirements — Identify architecture pattern, data models, API design
  2. Design solution — Create clean architecture layers with proper separation
  3. Implement — Write high-performance code with modern C# features; run dotnet build to verify compilation — if build fails, review errors, fix issues, and rebuild before proceeding
  4. Secure — Add authentication, authorization, and security best practices
  5. Test — Write comprehensive tests with xUnit and integration testing; run dotnet test to confirm all tests pass — if tests fail, diagnose failures, fix the implementation, and re-run before continuing; verify endpoints with curl or a REST client

Reference Guide

Load detailed guidance based on context:

TopicReferenceLoad When
Minimal APIsreferences/minimal-apis.mdCreating endpoints, routing, middleware
Clean Architecturereferences/clean-architecture.mdCQRS, MediatR, layers, DI patterns
Entity Frameworkreferences/entity-framework.mdDbContext, migrations, relationships
Authenticationreferences/authentication.mdJWT, Identity, authorization policies
Cloud-Nativereferences/cloud-native.mdDocker, health checks, configuration

Constraints

MUST DO

  • Use .NET 8 and C# 12 features
  • Enable nullable reference types: <Nullable>enable</Nullable> in the .csproj
  • Use async/await for all I/O operations — e.g., await dbContext.Users.ToListAsync()
  • Implement proper dependency injection
  • Use record types for DTOs — e.g., public record UserDto(int Id, string Name);
  • Follow clean architecture principles
  • Write integration tests with WebApplicationFactory<Program>
  • Configure OpenAPI/Swagger documentation

MUST NOT DO

  • Use synchronous I/O operations
  • Expose entities directly in API responses
  • Skip input validation
  • Use legacy .NET Framework patterns
  • Mix concerns across architectural layers
  • Use deprecated EF Core patterns

Code Examples

Minimal API Endpoint

csharp
// Program.cs
var builder = WebApplication.CreateBuilder(args);
builder.Services.AddEndpointsApiExplorer();
builder.Services.AddSwaggerGen();
builder.Services.AddMediatR(cfg => cfg.RegisterServicesFromAssembly(typeof(Program).Assembly));

var app = builder.Build();
app.UseSwagger();
app.UseSwaggerUI();

app.MapGet("/users/{id}", async (int id, ISender sender, CancellationToken ct) =>
{
    var result = await sender.Send(new GetUserQuery(id), ct);
    return result is null ? Results.NotFound() : Results.Ok(result);
})
.WithName("GetUser")
.Produces<UserDto>()
.ProducesProblem(404);

app.Run();

MediatR Query Handler

csharp
// Application/Users/GetUserQuery.cs
public record GetUserQuery(int Id) : IRequest<UserDto?>;

public sealed class GetUserQueryHandler : IRequestHandler<GetUserQuery, UserDto?>
{
    private readonly AppDbContext _db;

    public GetUserQueryHandler(AppDbContext db) => _db = db;

    public async Task<UserDto?> Handle(GetUserQuery request, CancellationToken ct) =>
        await _db.Users
            .AsNoTracking()
            .Where(u => u.Id == request.Id)
            .Select(u => new UserDto(u.Id, u.Name))
            .FirstOrDefaultAsync(ct);
}

EF Core DbContext with Async Query

csharp
// Infrastructure/AppDbContext.cs
public sealed class AppDbContext(DbContextOptions<AppDbContext> options) : DbContext(options)
{
    public DbSet<User> Users => Set<User>();

    protected override void OnModelCreating(ModelBuilder modelBuilder)
    {
        modelBuilder.ApplyConfigurationsFromAssembly(typeof(AppDbContext).Assembly);
    }
}

// Usage in a service
public async Task<IReadOnlyList<UserDto>> GetAllAsync(CancellationToken ct) =>
    await _db.Users
        .AsNoTracking()
        .Select(u => new UserDto(u.Id, u.Name))
        .ToListAsync(ct);

DTO with Record Type

csharp
public record UserDto(int Id, string Name);
public record CreateUserRequest(string Name, string Email);

Output Templates

When implementing .NET features, provide:

  1. Project structure (solution/project files)
  2. Domain models and DTOs
  3. API endpoints or service implementations
  4. Database context and migrations if applicable
  5. Brief explanation of architectural decisions

Documentation

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 Dotnet Core Expert AI skill do?

Use when building .NET 8 applications with minimal APIs, clean architecture, or cloud-native microservices. Invoke for Entity Framework Core, CQRS with MediatR, JWT authentication, AOT compilation.

Why use Dotnet Core Expert on TypingMind?

Because you install it once and use it with any model. Dotnet Core Expert 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 Dotnet Core Expert in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Jeffallan/claude-skills/tree/main/skills/dotnet-core-expert. 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 Dotnet Core Expert?

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 Dotnet Core Expert?

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

Is the Dotnet Core Expert AI skill free?

Yes. It is published on GitHub by Jeffallan 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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