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Write unit tests for a chosen function with a Copilot prompt file

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Overview

A prompt file from GitHub's Copilot customization library that studies the function or method you have selected and writes focused unit tests. It covers normal behaviour, invalid and boundary inputs, error handling and side effects, asking which function and test framework to use and aiming for 5 to 8 independent tests.

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Prompt
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---
agent: 'agent'
description: 'Generate unit tests for selected functions or methods'
---

## Task

Analyze the selected function/method and generate focused unit tests that thoroughly validate its behavior.

## Test Generation Strategy

1. **Core Functionality Tests**
   - Test the main purpose/expected behavior
   - Verify return values with typical inputs
   - Test with realistic data scenarios

2. **Input Validation Tests**
   - Test with invalid input types
   - Test with null/undefined values
   - Test with empty strings/arrays/objects
   - Test boundary values (min/max, zero, negative numbers)

3. **Error Handling Tests**
   - Test expected exceptions are thrown
   - Verify error messages are meaningful
   - Test graceful handling of edge cases

4. **Side Effects Tests** (if applicable)
   - Verify external calls are made correctly
   - Test state changes
   - Validate interactions with dependencies

## Test Structure Requirements

- Use existing project testing framework and patterns
- Follow AAA pattern: Arrange, Act, Assert
- Write descriptive test names that explain the scenario
- Group related tests in describe/context blocks
- Mock external dependencies cleanly

Target function: ${input:function_name:Which function or method should be tested?}
Testing framework: ${input:framework:Which framework? (jest/vitest/mocha/pytest/rspec/etc)}

## Guidelines

- Generate 5-8 focused test cases covering the most important scenarios
- Include realistic test data, not just simple examples
- Add comments for complex test setup or assertions
- Ensure tests are independent and can run in any order
- Focus on testing behavior, not implementation details

Create tests that give confidence the function works correctly and help catch regressions.

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