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    About

    Use when implementing any feature or bugfix, before writing implementation code

    SKILL.md

    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

    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.

    ```typescript 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>
    ```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.

    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.

    ```typescript async function retryOperation(fn: () => Promise): Promise { 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 ```typescript async function retryOperation( fn: () => Promise, options?: { maxRetries?: number; backoff?: 'linear' | 'exponential'; onRetry?: (attempt: number) => void; } ): Promise { // YAGNI } ``` Over-engineered

    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

    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', 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

    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.

    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.

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