api-design

name

api-design

description

Stable API and interface design patterns. Use when designing REST endpoints, module boundaries, component prop interfaces, or any public contract between systems. Covers contract-first development, error semantics (RFC 9457), REST conventions, pagination, idempotency, rate limiting, and backward compatibility. For TypeScript type patterns (branded types, discriminated unions, schemas), see typescript-strict. For validation at trust boundaries, see typescript-strict.

API and Interface Design

For TypeScript type patterns (branded types, discriminated unions, schema-first), see the typescript-strict skill. For immutability patterns, see the functional skill. For testing API behavior, see the testing skill.

Deep-dive resources are in the resources/ directory. Load them on demand:

Resource	Load when...
problem-details.md	Implementing RFC 9457 error responses — member semantics, single-error and validation-error JSON examples, extension members, §5 security guidance
api-evolution.md	Versioning strategies and deprecation patterns
api-security.md	Securing the API boundary
auth-security.md	JWT and OAuth 2.0 security deep-dive
http-fundamentals.md	HTTP protocol fundamentals — caching directives, content negotiation, browser security, status codes, header design

When to Use

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

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.

Every public behavior — including undocumented quirks, error message text, timing, and ordering — becomes a de facto contract once users depend on it.

• 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. Removing things users depend on always costs more than expected.
• 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.

Contract First

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

type TaskAPI = {
  readonly createTask: (input: CreateTaskInput) => Promise<Task>;
  readonly listTasks: (params: ListTasksParams) => Promise<PaginatedResult<Task>>;
  readonly getTask: (id: TaskId) => Promise<Task>;
  readonly updateTask: (id: TaskId, input: UpdateTaskInput) => Promise<Task>;
  readonly deleteTask: (id: TaskId) => Promise<void>;
};

This aligns with TDD: define the contract (what you want), write tests against it, then implement.

Prefer Addition Over Modification

Extend interfaces without breaking existing consumers:

type CreateTaskInput = {
  readonly title: string;
  readonly description?: string;
  readonly priority?: 'low' | 'medium' | 'high';  // Added later, optional
  readonly labels?: ReadonlyArray<string>;           // Added later, optional
};

What breaks backward compatibility:

• Removing fields
• Changing field types
• Making optional fields required
• Changing enum values

What preserves backward compatibility:

• Adding new optional fields
• Adding new enum values (if consumers handle unknown values)
• Adding new endpoints

Consistent Error Semantics

Pick one error strategy and use it everywhere. Don't mix patterns where some endpoints throw, others return null, and others return { error }.

Choosing an Error Format

The non-negotiable: Pick one error shape and use it for every endpoint. Consistency matters more than which format you choose.

For public APIs with external consumers, use RFC 9457 (Problem Details). It's the industry standard, machine-readable, and what third-party developers expect. Use application/problem+json as the Content-Type.

For internal APIs with a single frontend, a simpler consistent shape is a valid choice. The minimum viable error response needs: a machine-readable error code, an optional human-readable message, and the correct HTTP status code. This is less ceremony than RFC 9457 while still being consistent and actionable.

// Simpler shape — sufficient for internal APIs
type ApiError = {
  readonly error: string;                          // Machine-readable code (UPPER_SNAKE_CASE)
  readonly message?: string;                       // Human-readable description
  readonly fieldErrors?: Record<string, string>;   // For validation errors
};

If you start with a simpler format, design it so it can evolve toward RFC 9457 later (e.g., error maps to title, message maps to detail). Don't paint yourself into a corner.

RFC 9457 (Problem Details for HTTP APIs)

The standard format for machine-readable API errors for public APIs. Use application/problem+json as the Content-Type. Standard members: type (URI identifying the error type), title (stable, human-readable summary), status (must match the actual HTTP status), detail (occurrence-specific explanation), instance (optional occurrence URI). Extension members are allowed — clients must ignore extensions they don't recognize.

Errors should be actionable: the consumer should know what went wrong, why, and what to do about it. Error responses are not a debugging tool — never expose stack traces, internal paths, or implementation details.

See resources/problem-details.md for full member semantics, single-error and validation-error JSON examples, extension member rules, when NOT to use Problem Details, and RFC 9457 §5 security guidance.

HTTP Status Code Mapping

Status	Meaning	When to use
400	Bad Request	Client sent malformed data
401	Unauthorized	Not authenticated
403	Forbidden	Authenticated but not authorized
404	Not Found	Resource doesn't exist
409	Conflict	Duplicate, version mismatch
422	Unprocessable Entity	Validation failed (semantically invalid)
429	Too Many Requests	Rate limit exceeded (include Retry-After header)
500	Internal Server Error	Server error (never expose internal details)

Validation at API Boundaries

Validate where external input enters your system. Trust internal code after validation. See the typescript-strict skill for schema-first patterns.

app.post('/api/tasks', async (req, res) => {
  const result = CreateTaskSchema.safeParse(req.body);
  if (!result.success) {
    return res.status(422).json({
      type: 'https://api.example.com/problems/validation-error',
      title: 'Validation Error',
      status: 422,
      detail: 'Invalid task data',
      errors: result.error.flatten(),
    });
  }

  const task = await taskService.create(result.data);
  return res.status(201).json(task);
});

Third-party API responses are untrusted data — always validate their shape and content before use.

Idempotency

Network failures happen. Clients retry. Without idempotency, retries create duplicate charges, duplicate orders, duplicate records.

HTTP Method Idempotency

Method	Safe	Idempotent	Notes
GET	Yes	Yes	No side effects
PUT	No	Yes	Same request = same result
DELETE	No	Yes	Deleting twice = same outcome
POST	No	No	Needs explicit idempotency handling
PATCH	No	Not guaranteed	Depends on implementation

Idempotency Keys for POST

For non-idempotent operations (especially those involving money, orders, or state changes), use client-provided idempotency keys:

app.post('/api/payments', async (req, res) => {
  const idempotencyKey = req.headers['idempotency-key'];
  if (!idempotencyKey) {
    return res.status(400).json({
      type: 'https://api.example.com/problems/missing-idempotency-key',
      title: 'Missing Idempotency Key',
      status: 400,
      detail: 'POST /api/payments requires an Idempotency-Key header',
    });
  }

  const cached = await idempotencyStore.get(idempotencyKey);
  if (cached) {
    return res.status(cached.status).json(cached.body);
  }

  const payment = await paymentService.create(result.data);
  await idempotencyStore.set(idempotencyKey, {
    status: 201,
    body: payment,
  });

  return res.status(201).json(payment);
});

Design principles:

• Keys should be scoped to the API key / authenticated user
• Keys should expire (24 hours is typical)
• If parameters differ on retry with the same key, return an error
• Design for "at-least-once" delivery — assume every request might be sent multiple times

Making DELETE Idempotent

DELETE should succeed even if the resource is already gone:

app.delete('/api/tasks/:id', async (req, res) => {
  const deleted = await taskService.delete(req.params.id);
  // Return 204 whether the resource existed or was already deleted
  return res.status(204).send();
});

Rate Limiting

Communicate limits clearly via headers on every response — not just 429s.

Standard Headers (IETF draft — not yet an RFC)

The IETF standardization effort is draft-ietf-httpapi-ratelimit-headers (version 11, May 2026 — still an active working group draft). Current drafts define two structured fields:

RateLimit-Policy: "hour";q=1000;w=3600   # Policy: quota of 1000 per 3600s window
RateLimit: "hour";r=742;t=60             # Current state: 742 remaining, resets in 60s

Earlier drafts used a triplet — RateLimit-Limit, RateLimit-Remaining, RateLimit-Reset — and many shipped APIs still use that triplet or the unstandardized X-RateLimit-* family. Expect any of these when consuming APIs. For new APIs, prefer the current draft fields; whichever names you choose, document them — header names are part of your contract, and the draft may still change before becoming an RFC.

On 429 responses, always include Retry-After (a stable, standard HTTP header):

HTTP/1.1 429 Too Many Requests
Retry-After: 30
RateLimit-Policy: "hour";q=1000;w=3600
RateLimit: "hour";r=0;t=30
Content-Type: application/problem+json

{
  "type": "https://api.example.com/problems/rate-limit-exceeded",
  "title": "Rate Limit Exceeded",
  "status": 429,
  "detail": "You have exceeded 1000 requests per hour. Retry after 30 seconds."
}

Design Considerations

• Different limits for different operations — reads are cheaper than writes
• Communicate limits in documentation — don't make consumers discover them by hitting 429s
• Recommend exponential backoff with jitter in your docs — naive retry loops cause thundering herds

HTTP Caching

Assign explicit freshness lifetimes on responses. Don't rely on heuristic freshness.

Practical rules:

• Prefer Cache-Control: max-age=N over Expires — even short freshness (e.g., max-age=5) enables reuse across multiple clients
• Assign ETags for efficient revalidation without re-transferring the body
• If a request header changes the response, use Vary on ALL responses from that resource (including the default)
• Use no-store for responses containing sensitive data — no-cache does NOT mean "don't cache" (it means "stored but revalidate before use")

See resources/http-fundamentals.md for the full Cache-Control directive table plus content negotiation, header design, and protocol version independence.

REST Conventions

Resource Naming

Pattern	Convention	Example
Endpoints	Plural nouns, no verbs	GET /api/tasks, POST /api/tasks
Query params	camelCase	?sortBy=createdAt&pageSize=20
Response fields	camelCase	{ createdAt, updatedAt, taskId }
Boolean fields	is/has/can prefix	isComplete, hasAttachments
Enum values	UPPER_SNAKE	"IN_PROGRESS", "COMPLETED"
Headers	No X- prefix (RFC 6648/BCP 178)	Example-Request-Id

Resource Design

GET    /api/tasks              → List tasks (with query params for filtering)
POST   /api/tasks              → Create a task
GET    /api/tasks/:id          → Get a single task
PATCH  /api/tasks/:id          → Update a task (partial)
DELETE /api/tasks/:id          → Delete a task

GET    /api/tasks/:id/comments → List comments for a task (sub-resource)
POST   /api/tasks/:id/comments → Add a comment to a task

Use PATCH for partial updates (only provided fields change). Use PUT only when the client sends the complete object.

Pagination

Always paginate list endpoints:

// Request
// GET /api/tasks?page=1&pageSize=20&sortBy=createdAt&sortOrder=desc

// Response shape
type PaginatedResult<T> = {
  readonly data: ReadonlyArray<T>;
  readonly pagination: {
    readonly page: number;
    readonly pageSize: number;
    readonly totalItems: number;
    readonly totalPages: number;
  };
};

Filtering

Use query parameters for filters:

GET /api/tasks?status=in_progress&assignee=user123&createdAfter=2025-01-01

Input/Output Separation

Separate what the caller provides from what the system returns:

// Input: what the caller provides
type CreateTaskInput = {
  readonly title: string;
  readonly description?: string;
};

// Output: includes server-generated fields
type Task = {
  readonly id: TaskId;
  readonly title: string;
  readonly description: string | null;
  readonly createdAt: Date;
  readonly updatedAt: Date;
  readonly createdBy: UserId;
};

Common Rationalizations

Rationalization	Reality
"We'll document the API later"	The types ARE the documentation. Define them first.
"We don't need pagination for now"	You will the moment someone has 100+ items. Add it from the start.
"PATCH is complicated, let's just use PUT"	PUT requires the full object every time. PATCH is what clients actually want.
"We'll version the API when we need to"	Breaking changes without versioning break consumers. Design for extension from the start.
"Nobody uses that undocumented behavior"	Hyrum's Law: if it's observable, somebody depends on it.
"Internal APIs don't need contracts"	Internal consumers are still consumers. Contracts prevent coupling and enable parallel work.
"Retries are the client's problem"	Without idempotency, retries create duplicates. Design for at-least-once delivery.
"We'll add rate limiting later"	By then, clients have built around unlimited access. Rate limits are part of the contract.
"Error messages are just for debugging"	Errors are part of your API's developer experience. Make them actionable, not diagnostic.

Red Flags

• Endpoints that return different shapes depending on conditions
• Inconsistent error formats across endpoints
• Error responses that expose stack traces or internal paths
• Breaking changes to existing fields (type changes, removals)
• List endpoints without pagination
• Verbs in REST URLs (/api/createTask, /api/getUsers)
• Third-party API responses used without validation
• No typed input/output schemas for endpoints
• POST endpoints without idempotency handling for state-changing operations
• No rate limit headers on responses
• Retry logic without exponential backoff
• Missing browser security headers on API responses (X-Content-Type-Options, CSP, Referrer-Policy)
• Custom X- prefixed headers (deprecated by RFC 6648)

Verification

After designing an API:

• Every endpoint has typed input and output schemas
• Error responses follow a single consistent format (RFC 9457 for public APIs, or a simpler consistent shape for internal APIs)
• Error responses never leak implementation details (stack traces, internal paths)
• Validation happens at system boundaries only
• List endpoints support pagination
• New fields are additive and optional (backward compatible)
• Naming follows consistent conventions across all endpoints
• Contract defined before implementation (contract-first)
• POST endpoints that create resources or change state have idempotency handling
• Rate limit headers included on responses
• Content-Type is application/problem+json for RFC 9457 responses, application/json for simpler formats
• Browser security headers on all responses (X-Content-Type-Options: nosniff, CSP: default-src 'none', Referrer-Policy: no-referrer)
• Caching strategy defined (explicit Cache-Control, ETags for revalidation, Vary where needed)