/test-driven-development

name: test-driven-development
description: Drives development with tests using the red-green-refactor loop. Use when implementing any logic, fixing any bug, or changing any behavior. Use when you need to prove that code works, when a bug report arrives, or when you're about to modify existing functionality.

Test-Driven Development

Overview

Write a failing test before writing the code that makes it pass. For bug fixes, reproduce the bug with a test before attempting a fix. Tests are proof — "seems right" is not done. A codebase with good tests is an AI agent's superpower; a codebase without tests is a liability.

When to Use

• Implementing any new logic or behavior
• Fixing any bug (the Prove-It Pattern)
• Modifying existing functionality
• Adding edge case handling
• Any change that could break existing behavior

**When NOT to use:** Pure configuration changes, documentation updates, or static content changes that have no behavioral impact.

**Related:** For browser-based changes, combine TDD with runtime verification using Chrome DevTools MCP — see the Browser Testing section below.

Discover the Stack First

The TDD cycle is universal; the commands are not. Before writing the first test, discover how *this* repository tests, and use its commands for every RED, GREEN, and verification step:

• **Language and build system** — `package.json`, `pom.xml`/`build.gradle`, `pyproject.toml`, `go.mod`, `Cargo.toml`, `Gemfile`, a `Makefile`
• **Checked-in wrappers** — prefer `./gradlew`, `./mvnw`, `make test`, or a repo script over globally installed tools
• **Test framework and configuration** — and how it runs a single focused test vs the full suite
• **Existing conventions** — where tests live, how files are named, what patterns neighboring tests follow
• **Documented commands** — README, CONTRIBUTING, and CI workflows show the commands that actually gate merges

Run the repository's focused-test command during the loop and its full-suite command before completion. Never assume a default like `npm test` — a Gradle, Cargo, or pytest project has its own equivalent.

The examples below use TypeScript for illustration; the workflow is identical in any language once you've discovered the project's own tooling.

The TDD Cycle

    RED                GREEN              REFACTOR
 Write a test    Write minimal code    Clean up the
 that fails  ──→  to make it pass  ──→  implementation  ──→  (repeat)
      │                  │                    │
      ▼                  ▼                    ▼
   Test FAILS        Test PASSES         Tests still PASS

Step 1: RED — Write a Failing Test

Write the test first. It must fail. A test that passes immediately proves nothing.

// RED: This test fails because createTask doesn't exist yet
describe('TaskService', () => {
  it('creates a task with title and default status', async () => {
    const task = await taskService.createTask({ title: 'Buy groceries' });

    expect(task.id).toBeDefined();
    expect(task.title).toBe('Buy groceries');
    expect(task.status).toBe('pending');
    expect(task.createdAt).toBeInstanceOf(Date);
  });
});

Step 2: GREEN — Make It Pass

Write the minimum code to make the test pass. Don't over-engineer:

// GREEN: Minimal implementation
export async function createTask(input: { title: string }): Promise<Task> {
  const task = {
    id: generateId(),
    title: input.title,
    status: 'pending' as const,
    createdAt: new Date(),
  };
  await db.tasks.insert(task);
  return task;
}

Step 3: REFACTOR — Clean Up

With tests green, improve the code without changing behavior:

• Extract shared logic
• Improve naming
• Remove duplication
• Optimize if necessary

Run tests after every refactor step to confirm nothing broke.

The Prove-It Pattern (Bug Fixes)

When a bug is reported, **do not start by trying to fix it.** Start by writing a test that reproduces it.

Bug report arrives
       │
       ▼
  Write a test that demonstrates the bug
       │
       ▼
  Test FAILS (confirming the bug exists)
       │
       ▼
  Implement the fix
       │
       ▼
  Test PASSES (proving the fix works)
       │
       ▼
  Run full test suite (no regressions)

**Example:**

// Bug: "Completing a task doesn't update the completedAt timestamp"

// Step 1: Write the reproduction test (it should FAIL)
it('sets completedAt when task is completed', async () => {
  const task = await taskService.createTask({ title: 'Test' });
  const completed = await taskService.completeTask(task.id);

  expect(completed.status).toBe('completed');
  expect(completed.completedAt).toBeInstanceOf(Date);  // This fails → bug confirmed
});

// Step 2: Fix the bug
export async function completeTask(id: string): Promise<Task> {
  return db.tasks.update(id, {
    status: 'completed',
    completedAt: new Date(),  // This was missing
  });
}

// Step 3: Test passes → bug fixed, regression guarded

The Test Pyramid

Invest testing effort according to the pyramid — most tests should be small and fast, with progressively fewer tests at higher levels:

          ╱╲
         ╱  ╲         E2E Tests (~5%)
        ╱    ╲        Full user flows, real browser
       ╱──────╲
      ╱        ╲      Integration Tests (~15%)
     ╱          ╲     Component interactions, API boundaries
    ╱────────────╲
   ╱              ╲   Unit Tests (~80%)
  ╱                ╲  Pure logic, isolated, milliseconds each
 ╱──────────────────╲

**The Beyonce Rule:** If you liked it, you should have put a test on it. Infrastructure changes, refactoring, and migrations are not responsible for catching your bugs — your tests are. If a change breaks your code and you didn't have a test for it, that's on you.

Test Sizes (Resource Model)

Beyond the pyramid levels, classify tests by what resources they consume:

| Size | Constraints | Speed | Example | |------|------------|-------|---------| | *