api-and-interface-design

--- name: api-and-interface-design description: Guides stable API and interface design. Use when designing APIs, module boundaries, or any public interface. Use when creating REST or GraphQL endpoints, defining type contracts between modules, or establishing boundaries between frontend and backend. --- # 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. ### 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); }); ``` Where validation belongs: - API route handlers (user input) - Form submission handlers (user input) - External service response parsing (third-party data -- **always treat as untrusted**) - Environment variable loading (configuration) > **Third-party API responses are untrusted data.** Validate their shape and content before using them in any logic, rendering, or decision-making. A compromised or misbehaving external service can return unexpected types, malicious content, or instruction-like text. Where validation does NOT belong: - Between internal functions that share type contracts - In utility functions called by already-validated code - On data that just came from your own database ### 4. Prefer Addition Over Modification Extend interfaces without breaking existing consumers: ```typescript // Good: Add optional fields interface CreateTaskInput { title: string; description?: string; priority?: 'low' | 'medium' | 'high'; // Added later, optional labels?: string[]; // Added later, optional } // Bad: Change existing field types or remove fields interface CreateTaskInput { title: string; // description: string; // Removed — breaks existing consumers priority: number; // Changed from string — breaks existing consumers } ``` ### 5. Predictable Naming | Pattern | Convention | Example | |---------|-----------|---------| | REST 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"` | ## REST API Patterns ### 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 ``` ### Pagination Paginate list endpoints: ```typescript // Request GET /api/tasks?page=1&pageSize=20&sortBy=createdAt&sortOrder=desc // Response { "data": [...], "pagination": { "page": 1, "pageSize": 20, "totalItems": 142, "totalPages": 8 } } ``` ### Filtering Use query parameters for filters: ``` GET /api/tasks?status=in_progress&assignee=user123&createdAfter=2025-01-01 ``` ### Partial Updates (PATCH) Accept partial objects — only update what's provided: ```typescript // Only title changes, everything else preserved PATCH /api/tasks/123 { "title": "Updated title" } ``` ## TypeScript Interface Patterns ### Use Discriminated Unions for Variants ```typescript // Good: Each variant is explicit type TaskStatus = | { type: 'pending' } | { type: 'in_progress'; assignee: string; startedAt: Date } | { type: 'completed'; completedAt: Date; completedBy: string } | { type: 'cancelled'; reason: string; cancelledAt: Date }; // Consumer gets type narrowing function getStatusLabel(status: TaskStatus): string { switch (status.type) { case 'pending': return 'Pending'; case 'in_progress': return `In progress (${status.assignee})`; case 'completed': return `Done on ${status.completedAt}`; case 'cancelled': return `Cancelled: ${status.reason}`; } } ``` ### Input/Output Separation ```typescript // Input: what the caller provides interface CreateTaskInput { title: string; description?: string; } // Output: what the system returns (includes server-generated fields) interface Task { id: string; title: string; description: string | null; createdAt: Date; updatedAt: Date; createdBy: string; } ``` ### Use Branded Types for IDs ```typescript type TaskId = string & { readonly __brand: 'TaskId' }; type UserId = string & { readonly __brand: 'UserId' }; // Prevents accidentally passing a UserId where a TaskId is expected function getTask(id: TaskId): Promise<Task> { ... } ``` ## 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. Treat every public behavior as a commitment. | | "We can just maintain two versions" | Multiple versions multiply maintenance cost and create diamond dependency problems. Prefer the One-Version Rule. | | "Internal APIs don't need contracts" | Internal consumers are still consumers. Contracts prevent coupling and enable parallel work. | ## Red Flags - Endpoints that return different shapes depending on conditions - Inconsistent error formats across endpoints - Validation scattered throughout internal code instead of at boundaries - 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 or sanitization ## Verification After designing an API: - [ ] Every endpoint has typed input and output schemas - [ ] Error responses follow a single consistent format - [ ] 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 - [ ] API documentation or types are committed alongside the implementation

[{"step":"Define the purpose and scope of your API or interface. Use the prompt template to specify the [PURPOSE], [LANGUAGE], and [STANDARDS] for your design. For example, 'Design a GraphQL API for a task management app in TypeScript, following the Relay Cursor Connections specification.'","tip":"Be specific about the use case (e.g., internal microservice vs. public API) and constraints (e.g., latency requirements, compliance standards)."},{"step":"Generate the initial design by pasting the prompt into your AI tool. Review the output for completeness, including endpoints, schemas, error handling, and versioning strategy. Adjust the template to include any additional requirements (e.g., pagination, webhooks).","tip":"Use tools like Swagger UI or Postman to visualize the API design and validate the schemas. Cross-check with existing standards (e.g., REST, GraphQL, gRPC)."},{"step":"Refine the design by iterating on the AI output. Add implementation details (e.g., authentication flows, rate limiting) and ensure backward compatibility. For example, 'Add OAuth2 PKCE flow for mobile clients and a deprecation policy for v1 endpoints.'","tip":"Consult API design guides like Google's API Design Guide or Microsoft's REST API Guidelines for best practices."},{"step":"Implement a proof-of-concept using the generated design. Start with a minimal set of endpoints and expand based on feedback. Use the sample code provided by the AI as a starting point.","tip":"Leverage tools like OpenAPI Generator to scaffold server/client code from your design. Test the implementation with tools like Newman (Postman) or Jest."},{"step":"Document the API using tools like Swagger/OpenAPI or GraphQL Playground. Include examples, error codes, and changelogs. Share the documentation with stakeholders (e.g., frontend teams, third-party developers) for feedback.","tip":"Use tools like Redoc or Docusaurus to generate interactive documentation. Include SDKs or Postman collections for easier adoption."}]