---

name: test-driven-development description: Use when implementing any feature or bugfix, before writing implementation code

Test-Driven Development (TDD)

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.

When to Use

Always:

• New features
• Bug fixes
• Refactoring
• Behavior changes

Exceptions (ask your human partner):

• Throwaway prototypes
• Generated code
• Configuration files

Design alignment:

• Tests should verify behavior specified in the design doc
• If design doc or wireframe exists, test against THAT, not your interpretation
• Test names should map to design requirements

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

The Iron Law

CopyNO PRODUCTION CODE WITHOUT A FAILING TEST FIRST

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

Copydigraph 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.

const result = await retryOperation(operation);

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

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

<Bad>
```typescript
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

Requirements:

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

Verify RED - Watch It Fail

MANDATORY. Never skip.

Copynpm run test:ci -- 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.

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

Verify GREEN - Watch It Pass

MANDATORY.

Copynpm run test:ci -- 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.

Example: Bug Fix

Bug: Empty email accepted

RED

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

Verify RED

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

GREEN

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

Verify GREEN

Copy$ npm run test:ci
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, avoid these common pitfalls.

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

The Iron Laws

Copy1. 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

Bad:

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

Good:

Copytest('renders sidebar', () => {
  render(<Page />);  // Don't mock sidebar
  expect(screen.getByRole('navigation')).toBeInTheDocument();
});

Gate: Before asserting on any mock element, ask: "Am I testing real component behavior or just mock existence?"

Anti-Pattern 2: Test-Only Methods in Production

Bad:

Copyclass Session {
  async destroy() {  // Only used in tests!
    await this._workspaceManager?.destroyWorkspace(this.id);
  }
}

Good:

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

Gate: Before adding any method to production class, ask: "Is this only used by tests?" If yes, put it in test utilities.

Anti-Pattern 3: Mocking Without Understanding

Bad:

Copy// Mock breaks test logic - prevents config write that test depends on
vi.mock('ToolCatalog', () => ({
  discoverAndCacheTools: vi.fn().mockResolvedValue(undefined)
}));

Gate: Before mocking, understand what side effects the real method has and whether the test depends on them.

Anti-Pattern 4: Incomplete Mocks

Bad:

Copyconst mockResponse = {
  status: 'success',
  data: { userId: '123', name: 'Alice' }
  // Missing: metadata that downstream code uses
};

Good: Mirror real API completeness - include ALL fields the real API returns.

Anti-Pattern 5: Integration Tests as Afterthought

Testing is part of implementation, not optional follow-up. TDD cycle: test → implement → refactor → complete.

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"

Final Rule

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

No exceptions without your human partner's permission.