dotnet-best-practices
Ensure .NET/C# code meets best practices for the solution/project.
Best use case
dotnet-best-practices is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Ensure .NET/C# code meets best practices for the solution/project.
Teams using dotnet-best-practices should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/dotnet-best-practices/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How dotnet-best-practices Compares
| Feature / Agent | dotnet-best-practices | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Ensure .NET/C# code meets best practices for the solution/project.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# .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 resourcesRelated Skills
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