---
title: "Agent Skill to Dotnet Best Practices"
platform: "Promptally"
canonical_url: "https://app.promptally.dev/p/skill-dotnet-best-practices"
modality: "SKILL"
category: "Fullstack & Backend Engineering"
compatible_models: [Universal / Model Agnostic]
access_tier: "Free Public Artifact (No Auth Required)"
license: "MIT"
---

# Agent Skill to Dotnet Best Practices

**Summary:** Agent Skill to Dotnet Best Practices is a verified SKILL blueprint on Promptally in Fullstack & Backend Engineering optimized for leading AI models. Ensure .NET/C code meets best practices for the solution/project. Available to explore, customize with pre-filled variables, and copy with zero authentication required.

## Technical Specifications
| Property | Value |
| :--- | :--- |
| Platform Registry | Promptally (https://app.promptally.dev) |
| Modality | SKILL |
| Category | Fullstack & Backend Engineering |
| Compatible Engines | Universal / Model Agnostic |
| Dynamic Variables | None (Static Blueprint) |
| Approx. Token Length | 808 |
| Access Tier | Free Public Artifact (No Auth Required) |
| License | MIT |

### Pre-Filled Template & Production Source

```md
---
name: dotnet-best-practices
description: 'Ensure .NET/C# code meets best practices for the solution/project.'
---

# .NET/C# Best Practices

Your task is to ensure .NET/C# code in ${selection} meets the best practices specific to this solution/project. This includes:

## Documentation & Structure

- Create comprehensive XML documentation comments for all public classes, interfaces, methods, and properties
- Include parameter descriptions and return value descriptions in XML comments
- Follow the established namespace structure: {Core|Console|App|Service}.{Feature}

## Design Patterns & Architecture

- Use primary constructor syntax for dependency injection (e.g., `public class MyClass(IDependency dependency)`)
- Implement the Command Handler pattern with generic base classes (e.g., `CommandHandler<TOptions>`)
- Use interface segregation with clear naming conventions (prefix interfaces with 'I')
- Follow the Factory pattern for complex object creation.

## Dependency Injection & Services

- Use constructor dependency injection with null checks via ArgumentNullException
- Register services with appropriate lifetimes (Singleton, Scoped, Transient)
- Use Microsoft.Extensions.DependencyInjection patterns
- Implement service interfaces for testability

## Resource Management & Localization

- Use ResourceManager for localized messages and error strings
- Separate LogMessages and ErrorMessages resource files
- Access resources via `_resourceManager.GetString("MessageKey")`

## Async/Await Patterns

- Use async/await for all I/O operations and long-running tasks
- Return Task or Task<T> from async methods
- Use ConfigureAwait(false) where appropriate
- Handle async exceptions properly

## Testing Standards

- Use MSTest framework with FluentAssertions for assertions
- Follow AAA pattern (Arrange, Act, Assert)
- Use Moq for mocking dependencies
- Test both success and failure scenarios
- Include null parameter validation tests

## Configuration & Settings

- Use strongly-typed configuration classes with data annotations
- Implement validation attributes (Required, NotEmptyOrWhitespace)
- Use IConfiguration binding for settings
- Support appsettings.json configuration files

## Semantic Kernel & AI Integration

- Use Microsoft.SemanticKernel for AI operations
- Implement proper kernel configuration and service registration
- Handle AI model settings (ChatCompletion, Embedding, etc.)
- Use structured output patterns for reliable AI responses

## Error Handling & Logging

- Use structured logging with Microsoft.Extensions.Logging
- Include scoped logging with meaningful context
- Throw specific exceptions with descriptive messages
- Use try-catch blocks for expected failure scenarios

## Performance & Security

- Use C# 12+ features and .NET 8 optimizations where applicable
- Implement proper input validation and sanitization
- Use parameterized queries for database operations
- Follow secure coding practices for AI/ML operations

## Code Quality

- Ensure SOLID principles compliance
- Avoid code duplication through base classes and utilities
- Use meaningful names that reflect domain concepts
- Keep methods focused and cohesive
- Implement proper disposal patterns for resources

```

## Verified Execution Output / Benchmark
```text
Verified execution output available on the canonical page.
```

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