Test-Driven Development (TDD)

Write failing tests first, implement minimal code to pass, refactor. No exceptions.

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

The Iron Law

NO PRODUCTION CODE WITHOUT A FAILING TEST FIRST

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

Violating the letter of the rules is violating the spirit of the rules. No exceptions.

When to Use

Always:

• New features
• Bug fixes
• Refactoring
• Behavior changes

Exceptions (ask first):

• Throwaway prototypes
• Generated code
• Configuration files

Thinking “skip TDD just this once”? Stop. That’s rationalization.

Red-Green-Refactor

TDD follows a strict three-phase cycle:

1. RED: Write Failing Test

   Write one minimal test showing what should happen.

   Good test:

   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.

   Bad test:

   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)
2. 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.

3. GREEN: Minimal Code

   Write simplest code to pass the test.

   Good implementation:

   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.

   Bad implementation:

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

   Don’t add features, refactor other code, or “improve” beyond the test.

4. 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.

5. REFACTOR: Clean Up

   After green only:

   • Remove duplication
   • Improve names
   • Extract helpers

   Keep tests green. Don’t add behavior.

6. Repeat

   Next failing test for next feature.

Visual Workflow

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.

Good Tests

Quality	Good	Bad
Minimal	One thing. “and” in name? Split it.	test('validates email and domain and whitespace')
Clear	Name describes behavior	test('test1')
Shows intent	Demonstrates desired API	Obscures what code should do

Example: Bug Fix

Bug: Empty email accepted

1. RED

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

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

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

   $ npm test
   PASS
   
5. REFACTOR

   Extract validation for multiple fields if needed.

Red Flags - STOP and Start Over

If you:

• Wrote code before test
• Wrote test after implementation
• Test passed immediately
• Can’t explain why test failed
• Added tests “later”
• Think “just this once”
• Think “I already manually tested it”
• Think “Tests after achieve the same purpose”
• Think “It’s about spirit not ritual”
• Think “Keep as reference” or “adapt existing code”
• Think “Already spent X hours, deleting is wasteful”
• Think “TDD is dogmatic, I’m being pragmatic”
• Think “This is different because…”

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

Common Rationalizations

Excuse	Reality
”Too simple to test”	Simple code breaks. Test takes 30 seconds.
”I’ll test after”	Tests passing immediately prove nothing.
”Tests after achieve same goals”	Tests-after = “what does this do?” Tests-first = “what should this do?"
"Already manually tested”	Ad-hoc ≠ systematic. No record, can’t re-run.
”Deleting X hours is wasteful”	Sunk cost fallacy. Keeping unverified code is technical debt.
”Keep as reference, write tests first”	You’ll adapt it. That’s testing after. Delete means delete.
”Need to explore first”	Fine. Throw away exploration, start with TDD.
”Test hard = design unclear”	Listen to test. Hard to test = hard to use.
”TDD will slow me down”	TDD faster than debugging. Pragmatic = test-first.

When Stuck

Problem	Solution
Don’t know how to test	Write wished-for API. Write assertion first. Ask your human partner.
Test too complicated	Design too complicated. Simplify interface.
Must mock everything	Code too coupled. Use dependency injection.
Test setup huge	Extract helpers. Still complex? Simplify design.

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.

Related Skills

• Systematic Debugging: Write failing test to reproduce bug (Phase 4, Step 1)
• Executing Plans: Follow plan’s TDD steps for each task
• Subagent-Driven Development: Subagents use TDD for implementation

TDD is not about testing. It’s about design. Tests written first guide you toward simple, decoupled, testable code. Tests written after just verify whatever you already built.