Scalar

The product

Scalar renders interactive API references from OpenAPI and Swagger documents, with a built-in API testing tool and generated code examples for many languages. It also offers an offline-first API client that syncs with server frameworks through a watch mode. Teams can publish API references on Scalar’s managed hosting for free, and paid tiers add written docs, team collaboration, and custom domains.

The developer problem

An API reference is only as accurate as the OpenAPI document behind it, and that document usually comes out of a server framework rather than a text editor. If a framework integration drops a parameter or an auth scheme, the reference, the test tool, and every generated code example repeat the mistake. The watch mode keeps the client in sync with the server framework, but each framework describes its routes in its own way, so each integration needs its own care. For an ASP.NET team, the question is whether the reference matches what the controllers actually accept.

My focus

• ASP.NET integration. I’d work on a C# framework integration for ASP.NET and test it against real controllers, confirming that parameters, auth schemes, and response types reach the rendered reference intact.
• API reference themes. I’d work on themes in TypeScript and Vue that keep endpoints, schemas, and the test tool readable on a phone as well as a wide monitor.
• Generated code examples. I’d run each generated code example as a real request, so the snippet a reader copies matches what the API accepts.
• SDK and API docs pages. I’d write a getting-started page for each framework integration, tested by running the watch mode against a sample server before it goes live.

Why it fits my experience

• At Mitutoyo I worked primarily in C# on the .NET Framework, and I built an ASP.NET MVC dashboard so plant managers could see line status in a browser without a client install, which had been the single most common support complaint.
• At Meta I developed developer-facing content for more than 40 REST APIs on Wit.ai, Meta’s natural language processing platform, including intent and entity modeling, training data design, and the API workflows developers use to build conversational features.
• At Meta I also partner with SDK engineers through the release cycle, reviewing API changes early enough that breaking changes ship with migration guidance instead of a support thread.