test-driven-development

What this skill does

# 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

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

## The Iron Law

```
NO 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

```
┌─────────────┐
│     RED     │  Write failing test
│ Write test  │  describing desired behavior
└──────┬──────┘
       │
       ▼
┌─────────────┐
│ Verify RED  │  Run test - MUST fail
│ Watch fail  │  for expected reason
└──────┬──────┘
       │
       ▼
┌─────────────┐
│    GREEN    │  Write minimal code
│ Make it pass│  to make test pass
└──────┬──────┘
       │
       ▼
┌─────────────┐
│Verify GREEN │  Run test - MUST pass
│ Watch pass  │  all tests stay green
└──────┬──────┘
       │
       ▼
┌─────────────┐
│  REFACTOR   │  Clean up code while
│  Clean up   │  keeping tests green
└──────┬──────┘
       │
       ▼  Repeat for next behavior
```

### RED - Write Failing Test

Write one minimal test showing what should happen.

<Good>
```
test "retries failed operations 3 times":
    attempts = 0
    def operation():
        attempts += 1
        if attempts < 3: raise Error("fail")
        return "success"

    result = retry_operation(operation)

    assert result == "success"
    assert attempts == 3
```
Clear name, tests real behavior, one thing
</Good>

<Bad>
```
test "retry works":
    mock = create_mock()
        .fails_twice()
        .then_returns("success")
    retry_operation(mock)
    assert mock.call_count == 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.**

Run the project's test command targeting the specific test file.

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>
```
def retry_operation(fn, max_retries=3):
    for i in range(max_retries):
        try:
            return fn()
        except Error:
            if i == max_retries - 1: raise
    raise Error("unreachable")
```
Just enough to pass
</Good>

<Bad>
```
def retry_operation(fn, options=None):
    # options: max_retries, backoff_strategy, on_retry_callback
    # Configurable backoff: linear, exponential
    # YAGNI - all of this
```
Over-engineered
</Bad>

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

### Verify GREEN - Watch It Pass

**MANDATORY.**

Run the project's test command.

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

| 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 |

## 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

| 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. |
| "Manual test faster" | Manual doesn't prove edge cases. You'll re-test every change. |
| "Existing code has no tests" | You're improving it. Add tests for existing code. |

## 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**
```
test "rejects empty email":
    result = submit_form(email="")
    assert result.error == "Email required"
```

**Verify RED**
```
$ <test-command>
FAIL: expected "Email required", got None
```

**GREEN**
```
def submit_form(data):
    if not data.email or not data.email.strip():
        return Result(error="Email required")
    # ...
```

**Verify GREEN**
```
$ <test-command>
PASS
```

**REFACTOR**
Extract validation for multiple fields if needed.

## Verification Checklist

Before marking work complete:

- [ ] Every new function/method has a test
- [ ] Wa