github/awesome-copilot · Official

dotnet-best-practices

Ensure .NET/C# code meets best practices for the solution/project.

All-time #1145 Trending #3255 First seen Feb 25, 2026
8-week activity · all time api

Installation

$ npx skills add github/awesome-copilot --skill dotnet-best-practices

Summary

  • Validate .NET/C# code against comprehensive best practices for your solution and project.
  • Covers 10+ practice areas including XML documentation, design patterns, dependency injection, async/await, testing standards, and error handling Enforces specific patterns: primary constructors for DI, Command Handler pattern with generics, interface segregation, and Factory pattern for object creation Includes resource management with ResourceManager for localization, structured logging via Microsoft.Extensions.Logging, and Semantic Kernel integration for AI operations Requires MSTest with FluentAssertions for testing, strongly-typed configuration with data annotations, and C# 12+ / .NET 8 feature adoption

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

Claude Code Not declared
Cursor Not declared
Codex Not declared
GitHub Copilot Declared
Windsurf Not declared
Gemini CLI Not declared
Cline Not declared
OpenCode Not declared

Repository health

Stars 38.8K
License LICENSE
Default branch main
Open issues 21
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Declared agents github-copilot

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 3,230 B
  • docs SUMMARY.md 95 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 14,800 installs

SKILL.md

.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