test-driven-development

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.

Test-quality standard: Write tests to the same bar they'll be judged against. ${CLAUDE_PLUGIN_ROOT}/references/checklists/testing.md is the canonical test-quality checklist — pyramid, DAMP, mocking gates, what not to test, coverage. This skill is the workflow; that file is the standard (the test-quality-reviewer agent grades against it).

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.

Lint gate (if project has a linter):

After refactoring, run the project's lint command on changed files only:

# Example: ruff check <changed-files>, eslint <changed-files>, cargo clippy

Catch lint violations NOW — before the next action item adds more code on top. The specific command comes from the project's CLAUDE.md. If you don't know it yet, run it once on a file you just edited. If it passes, move on. If it fails, fix before proceeding.

Do NOT defer lint fixes to "after implementation." Lint errors compound — a single import-style choice (e.g., from __future__ import annotations) can cascade through every subsequent file if not caught immediately.

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

What NOT to Test

The canonical skip-list lives in ${CLAUDE_PLUGIN_ROOT}/references/checklists/testing.md. Rule of thumb: if a test would only fail when someone intentionally changes behavior (static markup, CSS, element counts, presentational-only components), it's preventing change, not testing it — don't write it. DO test conditional rendering, computed values, user interactions, state transitions, edge cases, and business rules.

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 function/method with logic (conditionals, computation, side effects) 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.

Coverage Requirements

Canonical criteria — test pyramid, the four pillars, coverage completeness — live in ${CLAUDE_PLUGIN_ROOT}/references/checklists/testing.md. Highlights:

Target: 80%+ Coverage of Logic Paths

• Coverage means branch/logic coverage, not line coverage of markup
• Pure presentational components (no conditionals, no computed values) do NOT need unit tests — they are validated visually
• Do not write tests solely to increase coverage numbers
• All edge cases covered
• Error scenarios tested
• Boundary conditions verified

Test Types

Type	Scope	Examples
Unit	Individual functions, utilities, pure functions	Component logic, helpers
Integration	API endpoints, database operations, service interactions	External API calls
E2E	Critical user flows, complete workflows	Browser automation, UI interactions

E2E Test Pattern (Playwright)

import { test, expect } from '@playwright/test'

test('user can search and filter markets', async ({ page }) => {
  await page.goto('/')
  await page.click('a[href="/markets"]')
  await expect(page.locator('h1')).toContainText('Markets')

  await page.fill('input[placeholder="Search"]', 'election')
  await page.waitForTimeout(600) // debounce

  const results = page.locator('[data-testid="market-card"]')
  await expect(results).toHaveCount(5, { timeout: 5000 })
})

Coverage Verification

npm run test:coverage
# Verify 80%+ coverage achieved

Coverage Thresholds (jest.config.js)

{
  "coverageThresholds": {
    "global": {
      "branches": 80,
      "functions": 80,
      "lines": 80,
      "statements": 80
    }
  }
}

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

Mocks are tools to isolate, not things to test. Before every mock, run these gates:

Don't test mock behavior

BEFORE asserting on any mock element:
  Ask: "Am I testing real behavior or mock existence?"
  IF mock existence → delete the assertion or unmock the component

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

// ✅ GOOD: If sidebar must be mocked, assert on Page's behavior
test('page passes user data to sidebar', () => {
  render(<Page user={testUser} />);
  expect(Sidebar).toHaveBeenCalledWith(
    expect.objectContaining({ user: testUser }), expect.anything()
  );
});

Don't add test-only methods to production classes

BEFORE adding any method to a production class:
  Ask: "Is this only used by tests?"
  IF yes → put it in test utilities instead

Mock at the right level

BEFORE mocking any method:
  1. "What side effects does the real method have?"
  2. "Does this test depend on any of those side effects?"
  IF yes → mock lower (the actual slow/external operation), not the method the test depends on

// ❌ BAD: Mock prevents config write that test depends on
test('detects duplicate server', async () => {
  vi.mock('ToolCatalog', () => ({
    discoverAndCacheTools: vi.fn().mockResolvedValue(undefined)
  }));
  await addServer(config);
  await addServer(config);  // Should throw - but won't!
});

// ✅ GOOD: Mock the slow part, preserve behavior test needs
test('detects duplicate server', async () => {
  vi.mock('MCPServerManager'); // Just mock slow server startup
  await addServer(config);    // Config written
  await addServer(config);    // Duplicate detected ✓
});

Preserve real semantics in mocks

BEFORE creating any mock:
  Ask: "What type does the real implementation return?"
  Value vs. stream? Sync vs. async? Array vs. cursor?
  IF mock changes the abstraction type → fix it

// ❌ BAD: Mock returns array, real implementation returns async cursor
const mockDb = {
  getUsers: vi.fn().mockResolvedValue([
    { id: '1', name: 'Alice' },
    { id: '2', name: 'Bob' },
  ])
};
// Test passes, but production breaks on 1000+ users when
// pagination and backpressure actually matter.

// ✅ GOOD: Mock preserves real cursor semantics
const mockDb = {
  getUsers: vi.fn().mockReturnValue({
    async *[Symbol.asyncIterator]() {
      yield { id: '1', name: 'Alice' };
      yield { id: '2', name: 'Bob' };
    }
  })
};

Red flags

• Assertion checks for *-mock test IDs
• Methods only called in test files
• Mock setup is >50% of test code
• mockResolvedValue() when real code returns a stream
• Mocking "just to be safe"

Final Rule

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

No exceptions without your human partner's permission.