Test Driven Development

Test-Driven Development (TDD)

Optimized for React 19+, Next.js 16+, Node.js 22+, TypeScript 5.5+, and Testing Library 16+.

Overview

Write the test first. Watch it fail. Write minimal code to pass.

Core principle: If you didn't watch the test fail, you don't know if it tests the right thing.

Violating the letter of the rules is violating the spirit of the rules.

• Leverage native parallel subagent dispatch and 200k+ context windows where available.

When to Use

Use symptom -> action triggers: when one matches, apply this skill and verify with the protocol below.

Always:

• New features
• Bug fixes
• Refactoring
• Behavior changes

Exceptions (ask your human partner):

• Throwaway prototypes
• Generated code
• Configuration files

Thinking "skip TDD just this once"? Stop. That's rationalization.

The Iron Law

NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST

Increment patch on wording/clarity fixes. Increment minor when adding a new verification step, example, or anti-pattern. Major only on breaking changes to core workflow.

Write code before the test? Delete it. Start over.

No exceptions:

• Don't keep it as "reference"
• Don't "adapt" it while writing tests
• Don't look at it
• Delete means delete

Implement fresh from tests. Period.

Red-Green-Refactor

digraph tdd_cycle {
    rankdir=LR;
    red [label="RED\nWrite failing test", shape=box, style=filled, fillcolor="#ffcccc"];
    verify_red [label="Verify fails\ncorrectly", shape=diamond];
    green [label="GREEN\nMinimal code", shape=box, style=filled, fillcolor="#ccffcc"];
    verify_green [label="Verify passes\nAll green", shape=diamond];
    refactor [label="REFACTOR\nClean up", shape=box, style=filled, fillcolor="#ccccff"];
    next [label="Next", shape=ellipse];

    red -> verify_red;
    verify_red -> green [label="yes"];
    verify_red -> red [label="wrong\nfailure"];
    green -> verify_green;
    verify_green -> refactor [label="yes"];
    verify_green -> green [label="no"];
    refactor -> verify_green [label="stay\ngreen"];
    verify_green -> next;
    next -> red;
}

RED - Write Failing Test

Write one minimal test showing what should happen.

<Good>

test('retries failed operations 3 times', async () => {
  let attempts = 0;
  const operation = () => {
    attempts++;
    if (attempts < 3) throw new Error('fail');
    return 'success';
  };

  const result = await retryOperation(operation);

  expect(result).toBe('success');
  expect(attempts).toBe(3);
});

Clear name, tests real behavior, one thing </Good>

<Bad>

test('retry works', async () => {
  const mock = jest.fn()
    .mockRejectedValueOnce(new Error())
    .mockRejectedValueOnce(new Error())
    .mockResolvedValueOnce('success');
  await retryOperation(mock);
  expect(mock).toHaveBeenCalledTimes(3);
});

Vague name, tests mock not code </Bad>

Requirements:

• One behavior
• Clear name
• Real code (no mocks unless unavoidable)

Verify RED - Watch It Fail

MANDATORY. Never skip.

npm test path/to/test.test.ts

Confirm:

• Test fails (not errors)
• Failure message is expected
• Fails because feature missing (not typos)

Test passes? You're testing existing behavior. Fix test.

Test errors? Fix error, re-run until it fails correctly.

GREEN - Minimal Code

Write simplest code to pass the test.

<Good>

async function retryOperation<T>(fn: () => Promise<T>): Promise<T> {
  for (let i = 0; i < 3; i++) {
    try {
      return await fn();
    } catch (e) {
      if (i === 2) throw e;
    }
  }
  throw new Error('unreachable');
}

Just enough to pass </Good>

<Bad>

async function retryOperation<T>(
  fn: () => Promise<T>,
  options?: {
    maxRetries?: number;
    backoff?: 'linear' | 'exponential';
    onRetry?: (attempt: number) => void;
  }
): Promise<T> {
  // YAGNI
}

Over-engineered </Bad>

Don't add features, refactor other code, or "improve" beyond the test.

Verify GREEN - Watch It Pass

MANDATORY.

npm test path/to/test.test.ts

Confirm:

• Test passes
• Other tests still pass
• Output pristine (no errors, warnings)

Test fails? Fix code, not test.

Other tests fail? Fix now.

REFACTOR - Clean Up

After green only:

• Remove duplication
• Improve names
• Extract helpers

Keep tests green. Don't add behavior.

Repeat

Next failing test for next feature.

Good Tests

Why Order Matters

"I'll write tests after to verify it works"

Tests written after code pass immediately. Passing immediately proves nothing:

• Might test wrong thing
• Might test implementation, not behavior
• Might miss edge cases you forgot
• You never saw it catch the bug

Test-first forces you to see the test fail, proving it actually tests something.

"I already manually tested all the edge cases"

Manual testing is ad-hoc. You think you tested everything but:

• No record of what you tested
• Can't re-run when code changes
• Easy to forget cases under pressure
• "It worked when I tried it" ≠ comprehensive

Automated tests are systematic. They run the same way every time.

"Deleting X hours of work is wasteful"

Sunk cost fallacy. The time is already gone. Your choice now:

• Delete and rewrite with TDD (X more hours, high confidence)
• Keep it and add tests after (30 min, low confidence, likely bugs)

The "waste" is keeping code you can't trust. Working code without real tests is technical debt.

"TDD is dogmatic, being pragmatic means adapting"

TDD IS pragmatic:

• Finds bugs before commit (faster than debugging after)
• Prevents regressions (tests catch breaks immediately)
• Documents behavior (tests show how to use code)
• Enables refactoring (change freely, tests catch breaks)

"Pragmatic" shortcuts = debugging in production = slower.

"Tests after achieve the same goals - it's spirit not ritual"

No. Tests-after answer "What does this do?" Tests-first answer "What should this do?"

Tests-after are biased by your implementation. You test what you built, not what's required. You verify remembered edge cases, not discovered ones.

Tests-first force edge case discovery before implementing. Tests-after verify you remembered everything (you didn't).

30 minutes of tests after ≠ TDD. You get coverage, lose proof tests work.

Common Rationalizations

Red Flags - STOP and Start Over

• Code before test
• Test after implementation
• Test passes immediately
• Can't explain why test failed
• Tests added "later"
• Rationalizing "just this once"
• "I already manually tested it"
• "Tests after achieve the same purpose"
• "It's about spirit not ritual"
• "Keep as reference" or "adapt existing code"
• "Already spent X hours, deleting is wasteful"
• "TDD is dogmatic, I'm being pragmatic"
• "This is different because..."

All of these mean: Delete code. Start over with TDD.

Anti-Patterns

• Starting work before the plan or gate is clear: Execution drifts when success criteria are implied instead of explicit.
• Treating verification as optional cleanup: The last mile is where regressions and missing updates are usually hiding.
• Mixing planning, implementation, and release work in one jump: You lose the causal chain that explains why a change is safe.

Verification Protocol

Before claiming "skill applied successfully":

1. Pass/fail: The Test Driven Development workflow starts from explicit success criteria, constraints, and stop conditions. 2. Pass/fail: Required evidence is collected before any completion, approval, or readiness claim. 3. Pass/fail: The next action follows the documented gate order without skipping review or verification steps. 4. Pressure-test scenario: Apply the workflow under time pressure with one failing check and one tempting shortcut. 5. Success metric: Zero rationalizations; blocked, failed, or unverified work is reported as such.

Modern Before and After Example

// Before
export async function updateOrderStatus(orderId: string) {
  await db.order.update({ where: { id: orderId }, data: { status: 'paid' } });
}

// After
test('updateOrderStatus marks the order as paid', async () => {
  await updateOrderStatus('ord_42');
  await expect(getOrder('ord_42')).resolves.toMatchObject({ status: 'paid' });
});

The contrast should stay obvious: implementation-first code can look finished, while the test-first version proves the behavior you actually needed before the production change lands.

Modern Frontend Testing Examples

Server Components

test('renders order details from a server component', async () => {
  const ui = await OrderSummary({ orderId: 'ord_42' });
  render(ui);
  expect(screen.getByText('ord_42')).toBeInTheDocument();
});

Error Boundaries

test('shows the fallback when the widget throws', () => {
  render(
    <ErrorBoundary fallback={<p>Retry later</p>}>
      <BrokenWidget />
    </ErrorBoundary>
  );
  expect(screen.getByText('Retry later')).toBeInTheDocument();
});

Accessibility Testing Tools

test('checkout form has no obvious accessibility violations', async () => {
  const { container } = render(<CheckoutForm />);
  expect(await axe(container)).toHaveNoViolations();
});

Example: Bug Fix

Bug: Empty email accepted

RED

test('rejects empty email', async () => {
  const result = await submitForm({ email: '' });
  expect(result.error).toBe('Email required');
});

Verify RED

$ npm test
FAIL: expected 'Email required', got undefined

GREEN

function submitForm(data: FormData) {
  if (!data.email?.trim()) {
    return { error: 'Email required' };
  }
  // ...
}

Verify GREEN

$ npm test
PASS

REFACTOR Extract validation for multiple fields if needed.

Verification Checklist

Before marking work complete:

• [ ] Every new function/method has a test
• [ ] Watched each test fail before implementing
• [ ] Each test failed for expected reason (feature missing, not typo)
• [ ] Wrote minimal code to pass each test
• [ ] All tests pass
• [ ] Output pristine (no errors, warnings)
• [ ] Tests use real code (mocks only if unavoidable)
• [ ] Edge cases and errors covered

Can't check all boxes? You skipped TDD. Start over.

When Stuck

Debugging Integration

Bug found? Write failing test reproducing it. Follow TDD cycle. Test proves fix and prevents regression.

Never fix bugs without a test.

Testing Anti-Patterns

When adding mocks or test utilities, read @testing-anti-patterns.md to avoid common pitfalls:

• Testing mock behavior instead of real behavior
• Adding test-only methods to production classes
• Mocking without understanding dependencies

Final Rule

Production code → test exists and failed first
Otherwise → not TDD

No exceptions without your human partner's permission.

<!-- PORTABILITY:START -->

Cross-Client Portability

This skill is written to stay usable across GitHub Copilot, Claude Code, Codex, and Gemini CLI.

• GitHub Copilot: keep the folder in a Copilot-visible skill or plugin path, or wrap the workflow as project instructions if the host does not support portable skill folders directly.
• Claude Code: keep the folder in a local skills directory or a compatible plugin or marketplace source.
• Codex: install or sync the folder into $CODEX_HOME/skills/<skill-name> and restart Codex after major changes.
• Gemini CLI: this repository generates a project command named /skills:test-driven-development from this skill. Rebuild commands with python scripts/export-gemini-skill.py test-driven-development and then run /commands reload inside Gemini CLI.

<!-- PORTABILITY:END -->

<!-- MCP:START -->

MCP Availability And Fallback

Preferred MCP Server: None required

• Fallback prompt: "Use the Test-Driven Development (TDD) skill without MCP. Rely on the local SKILL.md, bundled references or scripts, and manual verification. Show the exact commands, evidence, and final checks you used before concluding."
• If the current host does not expose a matching server, use the bundled references, scripts, native toolchain, and manual workflow already described in this skill.
• Treat direct local verification, rendered output, logs, tests, or screenshots as the fallback evidence path before completion.

<!-- MCP:END -->

Related Skills

• development-workflow: Use it when the workflow also needs planning, quality gates, and delivery tracking.
• code-quality: Use it when the workflow also needs two-stage review (spec compliance first, then code quality), maintainability, and refactoring guidance.
• systematic-debugging: Use it when the workflow also needs root-cause debugging before proposing fixes.
• verification-before-completion: Use it when the workflow also needs final evidence checks before claiming completion.

Changelog

[2026-04-25] - Version 1.2 Verification Protocol Refresh

Added

• Added a Verification Protocol section with skill-specific pass/fail checks, one pressure-test scenario, and a measurable success metric.
• Added guidance to leverage native parallel subagent dispatch and 200k+ context windows where available.

Changed

• Updated SKILL.md frontmatter to version: "1.2" and last_updated: 2026-04-25.
• Reframed activation guidance toward symptom -> action triggers and standardized two-stage review wording where applicable.

[2026-04-24] - Version 1.1 Refresh

Changed

• Updated the SKILL frontmatter version to 1.1 for the 2026-04-24 catalog refresh.
• Added a modern before/after example to make the implementation-first versus test-first contrast explicit.

All notable changes to this skill will be documented in this file.

[2026-04-24] - Skill Refresh

Changed

• Standardized the SKILL frontmatter with version metadata, last-updated date, tags, and a concise catalog description.
• Reformatted the portability and MCP guidance with a preferred server line, a copy-paste fallback prompt, and consistent bullet lists.
• Added a catalog-standard Anti-Patterns section and refreshed the Related Skills links at the end of the skill.
• Added current-version targeting and modern examples for Server Components, Error Boundaries, and accessibility testing tools.

Testing Anti-Patterns

Load this reference when: writing or changing tests, adding mocks, or tempted to add test-only methods to production code.

Overview

Tests must verify real behavior, not mock behavior. Mocks are a means to isolate, not the thing being tested.

Core principle: Test what the code does, not what the mocks do.

Following strict TDD prevents these anti-patterns.

The Iron Laws

1. NEVER test mock behavior
2. NEVER add test-only methods to production classes
3. NEVER mock without understanding dependencies

Anti-Pattern 1: Testing Mock Behavior

The violation:

// ❌ BAD: Testing that the mock exists
test('renders sidebar', () => {
  render(<Page />);
  expect(screen.getByTestId('sidebar-mock')).toBeInTheDocument();
});

Why this is wrong:

• You're verifying the mock works, not that the component works
• Test passes when mock is present, fails when it's not
• Tells you nothing about real behavior

your human partner's correction: "Are we testing the behavior of a mock?"

The fix:

// ✅ GOOD: Test real component or don't mock it
test('renders sidebar', () => {
  render(<Page />);  // Don't mock sidebar
  expect(screen.getByRole('navigation')).toBeInTheDocument();
});

// OR if sidebar must be mocked for isolation:
// Don't assert on the mock - test Page's behavior with sidebar present

Gate Function

BEFORE asserting on any mock element:
  Ask: "Am I testing real component behavior or just mock existence?"

  IF testing mock existence:
    STOP - Delete the assertion or unmock the component

  Test real behavior instead

Anti-Pattern 2: Test-Only Methods in Production

The violation:

// ❌ BAD: destroy() only used in tests
class Session {
  async destroy() {  // Looks like production API!
    await this._workspaceManager?.destroyWorkspace(this.id);
    // ... cleanup
  }
}

// In tests
afterEach(() => session.destroy());

Why this is wrong:

• Production class polluted with test-only code
• Dangerous if accidentally called in production
• Violates YAGNI and separation of concerns
• Confuses object lifecycle with entity lifecycle

The fix:

// ✅ GOOD: Test utilities handle test cleanup
// Session has no destroy() - it's stateless in production

// In test-utils/
export async function cleanupSession(session: Session) {
  const workspace = session.getWorkspaceInfo();
  if (workspace) {
    await workspaceManager.destroyWorkspace(workspace.id);
  }
}

// In tests
afterEach(() => cleanupSession(session));

Gate Function

BEFORE adding any method to production class:
  Ask: "Is this only used by tests?"

  IF yes:
    STOP - Don't add it
    Put it in test utilities instead

  Ask: "Does this class own this resource's lifecycle?"

  IF no:
    STOP - Wrong class for this method

Anti-Pattern 3: Mocking Without Understanding

The violation:

// ❌ BAD: Mock breaks test logic
test('detects duplicate server', () => {
  // Mock prevents config write that test depends on!
  vi.mock('ToolCatalog', () => ({
    discoverAndCacheTools: vi.fn().mockResolvedValue(undefined)
  }));

  await addServer(config);
  await addServer(config);  // Should throw - but won't!
});

Why this is wrong:

• Mocked method had side effect test depended on (writing config)
• Over-mocking to "be safe" breaks actual behavior
• Test passes for wrong reason or fails mysteriously

The fix:

// ✅ GOOD: Mock at correct level
test('detects duplicate server', () => {
  // Mock the slow part, preserve behavior test needs
  vi.mock('MCPServerManager'); // Just mock slow server startup

  await addServer(config);  // Config written
  await addServer(config);  // Duplicate detected ✓
});

Gate Function

BEFORE mocking any method:
  STOP - Don't mock yet

  1. Ask: "What side effects does the real method have?"
  2. Ask: "Does this test depend on any of those side effects?"
  3. Ask: "Do I fully understand what this test needs?"

  IF depends on side effects:
    Mock at lower level (the actual slow/external operation)
    OR use test doubles that preserve necessary behavior
    NOT the high-level method the test depends on

  IF unsure what test depends on:
    Run test with real implementation FIRST
    Observe what actually needs to happen
    THEN add minimal mocking at the right level

  Red flags:
    - "I'll mock this to be safe"
    - "This might be slow, better mock it"
    - Mocking without understanding the dependency chain

Anti-Pattern 4: Incomplete Mocks

The violation:

// ❌ BAD: Partial mock - only fields you think you need
const mockResponse = {
  status: 'success',
  data: { userId: '123', name: 'Alice' }
  // Missing: metadata that downstream code uses
};

// Later: breaks when code accesses response.metadata.requestId

Why this is wrong:

• Partial mocks hide structural assumptions - You only mocked fields you know about
• Downstream code may depend on fields you didn't include - Silent failures
• Tests pass but integration fails - Mock incomplete, real API complete
• False confidence - Test proves nothing about real behavior

The Iron Rule: Mock the COMPLETE data structure as it exists in reality, not just fields your immediate test uses.

The fix:

// ✅ GOOD: Mirror real API completeness
const mockResponse = {
  status: 'success',
  data: { userId: '123', name: 'Alice' },
  metadata: { requestId: 'req-789', timestamp: 1234567890 }
  // All fields real API returns
};

Gate Function

BEFORE creating mock responses:
  Check: "What fields does the real API response contain?"

  Actions:
    1. Examine actual API response from docs/examples
    2. Include ALL fields system might consume downstream
    3. Verify mock matches real response schema completely

  Critical:
    If you're creating a mock, you must understand the ENTIRE structure
    Partial mocks fail silently when code depends on omitted fields

  If uncertain: Include all documented fields

Anti-Pattern 5: Integration Tests as Afterthought

The violation:

✅ Implementation complete
❌ No tests written
"Ready for testing"

Why this is wrong:

• Testing is part of implementation, not optional follow-up
• TDD would have caught this
• Can't claim complete without tests

The fix:

TDD cycle:
1. Write failing test
2. Implement to pass
3. Refactor
4. THEN claim complete

When Mocks Become Too Complex

Warning signs:

• Mock setup longer than test logic
• Mocking everything to make test pass
• Mocks missing methods real components have
• Test breaks when mock changes

your human partner's question: "Do we need to be using a mock here?"

Consider: Integration tests with real components often simpler than complex mocks

TDD Prevents These Anti-Patterns

Why TDD helps: 1. Write test first → Forces you to think about what you're actually testing 2. Watch it fail → Confirms test tests real behavior, not mocks 3. Minimal implementation → No test-only methods creep in 4. Real dependencies → You see what the test actually needs before mocking

If you're testing mock behavior, you violated TDD - you added mocks without watching test fail against real code first.

Quick Reference

Red Flags

• Assertion checks for *-mock test IDs
• Methods only called in test files
• Mock setup is >50% of test
• Test fails when you remove mock
• Can't explain why mock is needed
• Mocking "just to be safe"

The Bottom Line

Mocks are tools to isolate, not things to test.

If TDD reveals you're testing mock behavior, you've gone wrong.

Fix: Test real behavior or question why you're mocking at all.