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1. Does the API start from consumer tasks?
List the important jobs consumers need to accomplish, the roles that perform them, and the permissions those jobs require. Use those scenarios to shape resources, relationships, and operations. Avoid exposing internal service boundaries or data structures when they make the public model harder to use.
Microsoft Graph’s REST API guidelines describe an API-first approach: define the user-facing contract before implementation. The guidelines summarize the usability goal this way: “The success of your ecosystem depends on APIs that are easy to discover, simple to use, fit for purpose, and consistent across your products.” Microsoft Graph REST API Guidelines
- Can a consumer map an API operation to a recognizable task?
- Are resource relationships clear without requiring knowledge of the service’s internals?
- Do the model and permissions cover realistic roles and workflows, not only the simplest case?
2. Can consumers discover and predict the API’s behavior?
Use familiar HTTP, REST, and JSON conventions where they fit, and choose names that explain what resources and operations do. Consistency matters more than any one casing or naming convention: avoid switching among synonyms, using vague generic labels, or inventing jargon consumers must memorize. Microsoft’s Azure guidance discusses these principles in its API design guidance.
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- Do similar operations follow similar naming and behavior patterns?
- Are relationships among resources explicit, and do operations behave as consumers would expect?
- Can consumers distinguish required inputs, optional inputs, and defaults?
3. Does the contract give implementers what they need?
A usable contract explains request and response shapes, required fields, authentication, permissions, operation behavior, and possible errors. Include examples that show meaningful workflows, not just isolated requests. A machine-readable description can generate documentation and SDKs; OpenAPI is one option, not the only valid format. Whatever the format, keep the published contract aligned with the service that actually runs.
Microsoft’s architecture guidance notes that an established contract can let developers work while service implementation is still underway. Microsoft Azure API design guidance
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- Can a developer understand the contract before obtaining access to a running service?
- Do documentation and examples identify required permissions and explain expected responses?
- Can consumers try realistic requests or generate reliable client support from the contract?
4. Can clients and people act on errors?
Use appropriate HTTP status codes and stable, machine-readable error codes so client software can decide what to do. Pair them with precise human-readable messages that explain what needs to change, while avoiding sensitive details. A request identifier can help service operators connect a customer report with relevant logs.
Microsoft Azure’s service design guidance states: “The errors returned by your service are a critical part of your developer experience and are part of your API contract.” It also treats changes to status codes and top-level error codes as compatibility-sensitive. Microsoft Azure API design guidance
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Rank #3
- Can a client distinguish authentication or permission failures from invalid input and temporary service problems?
- Does the response say what a user or developer can correct, without leaking implementation details?
- Can support staff use an identifier in the response to investigate a report?
5. Will collections remain usable as they grow?
Consider filtering and pagination whenever a collection or its payload could grow. Planning these features early avoids forcing consumers to retrieve unnecessarily large responses and reduces the risk of changing the contract later. Azure’s guidance warns that adding pagination after launch can be a breaking change, and recommends server-driven paging in most cases.
An opaque next-page link lets a client continue without rebuilding paging state. Where appropriate, client-driven page sizing can give consumers more control; weigh that flexibility against bounded payloads and protection for the service. Microsoft Azure API design guidance
Rank #4
- Can clients retrieve large result sets in manageable portions?
- Does the response provide a clear way to continue, such as a next-page link?
- Are filtering and page-size choices defined well enough that clients can predict their effect?
6. Can the API evolve without surprising existing clients?
Preserve existing client behavior where possible, and make breaking changes explicit. Choose a versioning strategy deliberately: Microsoft’s architecture guidance discusses versions in the URI, query string, header, or media type, each with different implications for routing, caching, links, and client clarity. It does not identify one universally best mechanism.
When evaluating a strategy, consider how consumers discover a version, how long multiple versions must be supported, whether URIs remain stable, and how routing and caches behave. Microsoft Azure API design guidance
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Best Value
- Are compatibility expectations clear to consumers?
- Can clients tell when a change requires an update?
- Does the chosen versioning approach fit the service’s routing, caching, and support needs?
7. Can consumers implement real workflows in their tools and languages?
Support SDKs across the programming languages your consumers use, while keeping the underlying API coherent for people who call it directly. Validate practical workflows, including permission failures and recoverable errors, rather than checking only that a successful request works. Microsoft’s Graph and Azure guidance offers product-specific recommendations; treat those as examples to adapt to your service rather than universal rules for every API.
Quick Recap
A practical review checklist
- Can a new consumer find and understand the contract?
- Do names, resource relationships, and behaviors remain predictable across endpoints?
- Can consumers identify authentication and permissions before implementation?
- Are errors actionable for both client software and people troubleshooting a request?
- Can clients consume large collections safely, with pagination planned from the outset?
- Are compatibility expectations and versioning choices clear?
- Can consumers implement and test realistic workflows in their preferred languages and tools?
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