csharp-nunit
$
npx mdskill add github/awesome-copilot/csharp-nunitProvides NUnit best practices for unit testing, including data-driven tests, to help developers write effective C# tests.
- Helps developers set up and structure NUnit test projects with clear conventions and patterns.
- Integrates with Microsoft.NET.Test.Sdk, NUnit, and NUnit3TestAdapter packages for .NET testing.
- Recommends practices based on established NUnit attributes and the Arrange-Act-Assert pattern.
- Delivers results as structured guidance on test organization, methods, and data-driven approaches.
SKILL.md
.github/skills/csharp-nunitView on GitHub ↗
---
name: csharp-nunit
description: 'Get best practices for NUnit unit testing, including data-driven tests'
---
# NUnit Best Practices
Your goal is to help me write effective unit tests with NUnit, covering both standard and data-driven testing approaches.
## Project Setup
- Use a separate test project with naming convention `[ProjectName].Tests`
- Reference Microsoft.NET.Test.Sdk, NUnit, and NUnit3TestAdapter packages
- Create test classes that match the classes being tested (e.g., `CalculatorTests` for `Calculator`)
- Use .NET SDK test commands: `dotnet test` for running tests
## Test Structure
- Apply `[TestFixture]` attribute to test classes
- Use `[Test]` attribute for test methods
- Follow the Arrange-Act-Assert (AAA) pattern
- Name tests using the pattern `MethodName_Scenario_ExpectedBehavior`
- Use `[SetUp]` and `[TearDown]` for per-test setup and teardown
- Use `[OneTimeSetUp]` and `[OneTimeTearDown]` for per-class setup and teardown
- Use `[SetUpFixture]` for assembly-level setup and teardown
## Standard Tests
- Keep tests focused on a single behavior
- Avoid testing multiple behaviors in one test method
- Use clear assertions that express intent
- Include only the assertions needed to verify the test case
- Make tests independent and idempotent (can run in any order)
- Avoid test interdependencies
## Data-Driven Tests
- Use `[TestCase]` for inline test data
- Use `[TestCaseSource]` for programmatically generated test data
- Use `[Values]` for simple parameter combinations
- Use `[ValueSource]` for property or method-based data sources
- Use `[Random]` for random numeric test values
- Use `[Range]` for sequential numeric test values
- Use `[Combinatorial]` or `[Pairwise]` for combining multiple parameters
## Assertions
- Use `Assert.That` with constraint model (preferred NUnit style)
- Use constraints like `Is.EqualTo`, `Is.SameAs`, `Contains.Item`
- Use `Assert.AreEqual` for simple value equality (classic style)
- Use `CollectionAssert` for collection comparisons
- Use `StringAssert` for string-specific assertions
- Use `Assert.Throws<T>` or `Assert.ThrowsAsync<T>` to test exceptions
- Use descriptive messages in assertions for clarity on failure
## Mocking and Isolation
- Consider using Moq or NSubstitute alongside NUnit
- Mock dependencies to isolate units under test
- Use interfaces to facilitate mocking
- Consider using a DI container for complex test setups
## Test Organization
- Group tests by feature or component
- Use categories with `[Category("CategoryName")]`
- Use `[Order]` to control test execution order when necessary
- Use `[Author("DeveloperName")]` to indicate ownership
- Use `[Description]` to provide additional test information
- Consider `[Explicit]` for tests that shouldn't run automatically
- Use `[Ignore("Reason")]` to temporarily skip tests
More from github/awesome-copilot
- acquire-codebase-knowledgeUse this skill when the user explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.
- acreadiness-assessRun the AgentRC readiness assessment on the current repository and produce a static HTML dashboard at reports/index.html. Wraps `npx github:microsoft/agentrc readiness` and hands off rendering to the @ai-readiness-reporter custom agent. Supports policies (--policy) for org-specific scoring. Use when asked to assess, audit, or score the AI readiness of a repo.
- acreadiness-generate-instructionsGenerate tailored AI agent instruction files via AgentRC instructions command. Produces .github/copilot-instructions.md (default, recommended for Copilot in VS Code) plus optional per-area .instructions.md files with applyTo globs for monorepos. Use after running /acreadiness-assess to close gaps in the AI Tooling pillar.
- acreadiness-policyHelp the user pick, write, or apply an AgentRC policy. Policies customise readiness scoring by disabling irrelevant checks, overriding impact/level, setting pass-rate thresholds, or chaining org baselines with team overrides. Use when the user asks about strict mode, AI-only scoring, custom weights, CI gating, or wants org-wide standardisation.
- add-educational-comments'Add educational comments to the file specified, or prompt asking for file to comment if one is not provided.'
- adobe-illustrator-scriptingWrite, debug, and optimize Adobe Illustrator automation scripts using ExtendScript (JavaScript/JSX). Use when creating or modifying scripts that manipulate documents, layers, paths, text frames, colors, symbols, artboards, or any Illustrator DOM objects. Covers the complete JavaScript object model, coordinate system, measurement units, export workflows, and scripting best practices.
- agent-governance|
- agent-owasp-compliance|
- agent-supply-chain|
- agentic-eval|