api-and-interface-design

Files (7)

• SKILL.md
• asdr-014-http-https.md · references/
• asdr-018-apis.md · references/
• asdr-023-idempotency.md · references/
• asdr-129-stripe-s-payments-apis-the-first-10-years.md · references/
• htn-http-routing.md · references/
• htn-rest-api-design.md · references/

SKILL.md (first lines)

# API and Interface Design

## Overview

Design stable, well-documented interfaces that are hard to misuse. Good interfaces make the right thing easy and the wrong thing hard. This applies to REST APIs, GraphQL schemas, module boundaries, component props, and any surface where one piece of code talks to another.

## When to Use

- Designing new API endpoints
- Defining module boundaries or contracts between teams
- Creating component prop interfaces
- Establishing database schema that informs API shape
- Changing existing public interfaces

## Core Principles

### Hyrum's Law

> With a sufficient number of users of an API, all observable behaviors of your system will be depended on by somebody, regardless of what you promise in the contract.

This means: every public behavior — including undocumented quirks, error message text, timing, and ordering — becomes a de facto contract once users depend on it. Design implications:

- **Be intentional about what you expose.** Every observable behavior is a potential commitment.
- **Don't leak implementation details.** If users can observe it, they will depend on it.
- **Plan for deprecation at design time.** See `deprecation-and-migration` for how to safely remove things users depend on.
- **Tests are not enough.** Even with perfect contract tests, Hyrum's Law means "safe" changes can break real users who depend on undocumented behavior.

### The One-Version Rule

Avoid forcing consumers to choose between multiple versions of the same dependency or API. Diamond dependency problems arise when different consumers need different versions of the same thing. Design for a world where only one version exists at a time — extend rather than fork.

### Decouple the API Surface from the Storage Schema

The wire contract and the database schema are two different things that change at two different rates.
If the API just serializes your tables, every storage refactor (splitting a column, normalizing,
reshaping for a new index) becomes a *breaking API change*, and conversely every API need distorts the
schema. Design the resource representation for the **consumer**, then map it to storage explicitly
through a serializer / DTO layer, so either side can evolve behind that seam. This is why `Task` (the
output type below) is defined separately from any table row — and why "establishing a database schema
that informs API shape" (in *When to Use*) means *informs*, never *dictates*: Hyrum's Law makes an
accidentally-exposed column as permanent as a deliberately-promised field.

> Per the Google API Design Guide (resource-oriented design; cloud.google.com/apis/design). Stack-agnostic —
> the DTO/serializer seam applies equally to REST, GraphQL, and RPC.

### 1. Contract First

Define the interface before implementing it. The contract is the spec — implementation follows.

```typescript
// Define the contract first
interface TaskAPI {
  // Creates a task and returns the created task with server-generated fields
  createTask(input: CreateTaskInput): Promise<Task>;

  // Returns paginated tasks matching filters
  listTasks(params: ListTasksParams): Promise<PaginatedResult<Task>>;

  // Returns a single task or throws NotFoundError
  getTask(id: string): Promise<Task>;

  // Partial update — only provided fields change
  updateTask(id: string, input: UpdateTaskInput): Promise<Task>;

  // Idempotent delete — succeeds even if already deleted
  deleteTask(id: string): Promise<void>;
}
```

### 2. Consistent Error Semantics

Pick one error strategy and use it everywhere:

```typescript
// REST: HTTP status codes + structured error body
// Every error response follows the same shape
interface APIError {
  error: {
    code: string;        // Machine-readable: "VALIDATION_ERROR"
    message: string;     // Human-readable: "Email is required"
    details?: unknown;   // Additional context when helpful
  };
}

// Status code mapping
// 400 → Client sent invalid data
// 401 → Not authenticated
// 403 → Authenticated but not authorized
// 404 → Resource not found
// 409 → Conflict (duplicate, version mismatch)
// 422 → Validation failed (semantically invalid)
// 500 → Server error (never expose internal details)
```

**Don't mix patterns.** If some endpoints throw, others return null, and others return `{ error }` — the consumer can't predict behavior.

### 3. Validate at Boundaries

Trust internal code. Validate at system edges where external input enters:

```typescript
// Validate at the API boundary
app.post('/api/tasks', async (req, res) => {
  const result = CreateTaskSchema.safeParse(req.body);
  if (!result.success) {
    return res.status(422).json({
      error: {
        code: 'VALIDATION_ERROR',
        message: 'Invalid task data',
        details: result.error.flatten(),
      },
    });
  }

  // After validation, internal code trusts the types
  const task = await taskService.create(result.data);
  return res.status(201).json(task);
});
```

From ajyadav013/claude-kit, MIT.

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