# SkillPatch skill: tdd

This skill guides an agent through Test-Driven Development (TDD) using the red → green loop. It defines what makes a good test, where tests should be placed (seams), common anti-patterns to avoid, and strict rules for the TDD cycle. It is designed to be consulted actively during every TDD cycle to produce high-quality, behavior-focused tests.

You (the agent) were given this URL and asked to use this skill. This is a **public** skill — no SkillPatch account, API key, or prior setup is required. Two ways to use it:

**1. Use it right now** — the skill's complete file tree (SKILL.md + all reference files) is inlined below; read `SKILL.md` first, then follow it, consulting the other files as it directs.

**2. Install the exact package onto disk** (recommended if you can run a shell — this reproduces the skill byte-for-byte, including any binary assets that can't be inlined):

```bash
mkdir -p .claude/skills/tdd
curl -sSL https://skillpatch.dev/install_skill/tdd | tar -xz -C .claude/skills/
```

(`.claude/skills/` is Claude Code's convention; use whatever directory your agent loads skills from.)


---

## Skill files (3)

- `SKILL.md`
- `mocking.md`
- `tests.md`


### `SKILL.md`

```markdown
---
name: tdd
description: Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
---

# Test-Driven Development

TDD is the red → green loop. This skill is the reference that makes that loop produce tests worth keeping: what a good test is, where tests go, the anti-patterns, and the rules of the loop. Every section applies on every cycle — consult them before and during the loop, not after.

When exploring the codebase, read `CONTEXT.md` (if it exists) so test names and interface vocabulary match the project's domain language, and respect ADRs in the area you're touching.

## What a good test is

Tests verify behavior through public interfaces, not implementation details. Code can change entirely; tests shouldn't. A good test reads like a specification — "user can checkout with valid cart" tells you exactly what capability exists — and survives refactors because it doesn't care about internal structure.

See [tests.md](tests.md) for examples and [mocking.md](mocking.md) for mocking guidelines.

## Seams — where tests go

A **seam** is the public boundary you test at: the interface where you observe behavior without reaching inside. Tests live at seams, never against internals.

**Test only at pre-agreed seams.** Before writing any test, write down the seams under test and confirm them with the user. No test is written at an unconfirmed seam. You can't test everything — agreeing the seams up front is how testing effort lands on the critical paths and complex logic instead of every edge case.

Ask: "What's the public interface, and which seams should we test?"

## Anti-patterns

- **Implementation-coupled** — mocks internal collaborators, tests private methods, or verifies through a side channel (querying the database instead of using the interface). The tell: the test breaks when you refactor but behavior hasn't changed.
- **Tautological** — the assertion recomputes the expected value the way the code does (`expect(add(a, b)).toBe(a + b)`, a snapshot derived by hand the same way, a constant asserted equal to itself), so it passes by construction and can never disagree with the code. Expected values must come from an independent source of truth — a known-good literal, a worked example, the spec.
- **Horizontal slicing** — writing all tests first, then all implementation. Bulk tests verify _imagined_ behavior: you test the _shape_ of things rather than user-facing behavior, the tests go insensitive to real changes, and you commit to test structure before understanding the implementation. Work in **vertical slices** instead — one test → one implementation → repeat, each test a **tracer bullet** that responds to what the last cycle taught you.

## Rules of the loop

- **Red before green.** Write the failing test first, then only enough code to pass it. Don't anticipate future tests or add speculative features.
- **One slice at a time.** One seam, one test, one minimal implementation per cycle.
- **Refactoring is not part of the loop.** It belongs to the review stage (see the `code-review` skill), not the red → green implementation cycle.

```


### `mocking.md`

````markdown
# When to Mock

Mock at **system boundaries** only:

- External APIs (payment, email, etc.)
- Databases (sometimes - prefer test DB)
- Time/randomness
- File system (sometimes)

Don't mock:

- Your own classes/modules
- Internal collaborators
- Anything you control

## Designing for Mockability

At system boundaries, design interfaces that are easy to mock:

**1. Use dependency injection**

Pass external dependencies in rather than creating them internally:

```typescript
// Easy to mock
function processPayment(order, paymentClient) {
  return paymentClient.charge(order.total);
}

// Hard to mock
function processPayment(order) {
  const client = new StripeClient(process.env.STRIPE_KEY);
  return client.charge(order.total);
}
```

**2. Prefer SDK-style interfaces over generic fetchers**

Create specific functions for each external operation instead of one generic function with conditional logic:

```typescript
// GOOD: Each function is independently mockable
const api = {
  getUser: (id) => fetch(`/users/${id}`),
  getOrders: (userId) => fetch(`/users/${userId}/orders`),
  createOrder: (data) => fetch('/orders', { method: 'POST', body: data }),
};

// BAD: Mocking requires conditional logic inside the mock
const api = {
  fetch: (endpoint, options) => fetch(endpoint, options),
};
```

The SDK approach means:
- Each mock returns one specific shape
- No conditional logic in test setup
- Easier to see which endpoints a test exercises
- Type safety per endpoint

````


### `tests.md`

````markdown
# Good and Bad Tests

## Good Tests

**Integration-style**: Test through real interfaces, not mocks of internal parts.

```typescript
// GOOD: Tests observable behavior
test("user can checkout with valid cart", async () => {
  const cart = createCart();
  cart.add(product);
  const result = await checkout(cart, paymentMethod);
  expect(result.status).toBe("confirmed");
});
```

Characteristics:

- Tests behavior users/callers care about
- Uses public API only
- Survives internal refactors
- Describes WHAT, not HOW
- One logical assertion per test

## Bad Tests

**Implementation-detail tests**: Coupled to internal structure.

```typescript
// BAD: Tests implementation details
test("checkout calls paymentService.process", async () => {
  const mockPayment = jest.mock(paymentService);
  await checkout(cart, payment);
  expect(mockPayment.process).toHaveBeenCalledWith(cart.total);
});
```

Red flags:

- Mocking internal collaborators
- Testing private methods
- Asserting on call counts/order
- Test breaks when refactoring without behavior change
- Test name describes HOW not WHAT
- Verifying through external means instead of interface

```typescript
// BAD: Bypasses interface to verify
test("createUser saves to database", async () => {
  await createUser({ name: "Alice" });
  const row = await db.query("SELECT * FROM users WHERE name = ?", ["Alice"]);
  expect(row).toBeDefined();
});

// GOOD: Verifies through interface
test("createUser makes user retrievable", async () => {
  const user = await createUser({ name: "Alice" });
  const retrieved = await getUser(user.id);
  expect(retrieved.name).toBe("Alice");
});
```

**Tautological tests**: Expected value restates the implementation, so the test passes by construction.

```typescript
// BAD: Expected value is recomputed the way the code computes it
test("calculateTotal sums line items", () => {
  const items = [{ price: 10 }, { price: 5 }];
  const expected = items.reduce((sum, i) => sum + i.price, 0);
  expect(calculateTotal(items)).toBe(expected);
});

// GOOD: Expected value is an independent, known literal
test("calculateTotal sums line items", () => {
  expect(calculateTotal([{ price: 10 }, { price: 5 }])).toBe(15);
});
```

````