An API can be easy to implement and difficult to live with. The difference often appears months later, when a second client arrives, a workflow changes or a failure needs to be diagnosed. A useful design goal is to make those changes understandable to someone who did not write the original service.
Start with one complete interaction
Before listing endpoints, describe a single user task. Consider a service that creates support requests: what information must the caller provide, what does acceptance mean, and how will the caller discover what happened next? Write a sample request and response before choosing the internal classes.
For example, a creation response might return a stable request identifier and its current state. Avoid promising that work is complete when it has only been queued. If processing is asynchronous, document how the caller can check progress and what a terminal failure looks like.
Separate the contract from storage
Database rows are convenient response objects until the schema needs to change. Define an explicit external representation instead. It can omit internal flags, use names that make sense to consumers and keep relationships stable even when tables are reorganised.
This does introduce mapping code. The trade-off is worthwhile at boundaries that have independent consumers; a tiny internal tool may need much less ceremony. The point is to choose the boundary deliberately, rather than expose every persistence detail by accident.
Make failure part of the design
A client needs to distinguish invalid input from a temporary service failure. HTTP defines the semantics of methods and status codes; use that shared vocabulary consistently. For machine-readable error responses, RFC 9457 provides a standard Problem Details format. Keep client-facing explanations separate from stack traces and implementation details. See HTTP Semantics and Problem Details for HTTP APIs.
For the support-request example, document missing required fields, an unavailable dependency and an unauthorised caller. Give each case an example. Discuss retry behaviour explicitly: a timed-out creation request may already have succeeded, so blindly repeating it can create duplicate work. A deduplication strategy needs defined scope, retention and behaviour when a repeated key carries different input.
Review changes from the consumer’s side
Before releasing a change, ask what an existing consumer will observe. Renaming a field is obviously disruptive, but changing a default, ordering rule or error condition can also affect behaviour. Even an added field can break a client that rejects unknown properties.
Keep a small set of consumer-facing checks: a valid request, invalid input, missing permission and one realistic failure path. Test the promise made at the boundary rather than every implementation detail. Include examples in documentation so that someone can understand the contract without reading the service code.
Choose one endpoint and write its successful response, three failure responses and retry behaviour. Any ambiguity you find there is cheaper to resolve before another team depends on it.