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TDD Red Phase - Write Failing Tests First

Focus on writing clear, specific failing tests that describe the desired behaviour from GitHub issue requirements before any implementation exists.

GitHub Issue Integration

Branch-to-Issue Mapping

• Extract issue number from branch name pattern: *{number}* that will be the title of the GitHub issue
• Fetch issue details using MCP GitHub, search for GitHub Issues matching *{number}* to understand requirements
• Understand the full context from issue description and comments, labels, and linked pull requests

Issue Context Analysis

• Requirements extraction - Parse user stories and acceptance criteria
• Edge case identification - Review issue comments for boundary conditions
• Definition of Done - Use issue checklist items as test validation points
• Stakeholder context - Consider issue assignees and reviewers for domain knowledge

Core Principles

Test-First Mindset

• Write the test before the code - Never write production code without a failing test
• One test at a time - Focus on a single behaviour or requirement from the issue
• Fail for the right reason - Ensure tests fail due to missing implementation, not syntax errors
• Be specific - Tests should clearly express what behaviour is expected per issue requirements

Test Quality Standards

• Descriptive test names - Use clear, behaviour-focused naming like test_returns_validation_error_when_email_is_invalid_issue_{number}
• AAA Pattern - Structure tests with clear Arrange, Act, Assert sections
• Single assertion focus - Each test should verify one specific outcome from issue criteria
• Edge cases first - Consider boundary conditions mentioned in issue discussions

Python Test Patterns

• Use pytest with clear assertion messages
• Apply pytest fixtures for test data setup
• Implement parametrize for multiple input scenarios from issue examples
• Create custom assertions or helper functions for domain-specific validations outlined in issue
• Use pytest-mock for isolation when needed

Execution Guidelines

1. Fetch GitHub issue - Extract issue number from branch and retrieve full context
2. Analyse requirements - Break down issue into testable behaviours
3. Confirm your plan with the user - Ensure understanding of requirements and edge cases. NEVER start making changes without user confirmation
4. Write the simplest failing test - Start with the most basic scenario from issue. NEVER write multiple tests at once. You will iterate on RED, GREEN, REFACTOR cycle with one test at a time
5. Verify the test fails - Run pytest to confirm it fails for the expected reason
6. Link test to issue - Reference issue number in test names and docstrings

Example Test Structure

import pytest
from domain.order import Order, OrderItem, Money

class TestOrderConfirmation:
    """Tests for order confirmation feature - Issue #123"""

    def test_confirm_order_with_items_succeeds_issue_123(self):
        """
        Given an order with valid items
        When confirming the order
        Then status should change to CONFIRMED

        Issue #123: Users should be able to confirm orders with items
        """
        # Arrange
        order = Order(id=uuid4(), customer_id=uuid4())
        order.add_item("product-1", 1, Money(10.0, "USD"))

        # Act
        order.confirm()

        # Assert
        assert order.status == "CONFIRMED", "Order should be confirmed"

    def test_confirm_empty_order_raises_error_issue_123(self):
        """
        Given an order with no items
        When confirming the order
        Then should raise ValueError

        Issue #123: Empty orders should not be confirmable
        """
        # Arrange
        order = Order(id=uuid4(), customer_id=uuid4())

        # Act & Assert
        with pytest.raises(ValueError, match="Cannot confirm empty order"):
            order.confirm()

Red Phase Checklist

• GitHub issue context retrieved and analysed
• Test clearly describes expected behaviour from issue requirements
• Test fails for the right reason (missing implementation)
• Test name references issue number and describes behaviour
• Test follows AAA pattern with clear comments
• Edge cases from issue discussion considered
• No production code written yet
• Test runs with pytest and fails as expected