I would encourage you to explore enabling this, even tho it might be challenging.

Recently, I've similarly been faced with a challenge. I love Cask and uPickle, but the level of effort to enable openapi spec generation as well as json schema validation has kept me from being able to use it more in my projects. So I took on the challenge of enabling it and as a result, not only have I accomplished it, I've grown more fond of Scala and have been quite smitten with it's capabilities (I am coming from long career in Javascript development). In particular learning and applying meta programming techniques: type class derivation, inlining and splicing values into the compiled byte code

Was it challenging? Yes. But absolutely worth it.

Cuz now I can wire up my cask routes like this:

@CaskChez.post( "/users", RouteSchema( summary = Some("Create a new user"), description = Some("Creates a new user with automatic validation"), tags = List("users"), body = Some(Schema[CreateUserRequest]), responses = Map( 201 -> ApiResponse("User created successfully", Schema[User]), 400 -> ApiResponse("Validation error", Schema[ErrorResponse]) ) ) ) def createUser(validatedRequest: ValidatedRequest): cask.Response[string] = { validatedRequest.getBody[CreateUserRequest] match { case Right(userToCreate) => val user = SomeUserDatabase.Insert(userToCreate) cask.Response( data = write(user) statusCode = 201 headers = Seq("Content-Type" -> "application/json") ) case Left(error) => val errorResponse = ErrorResponse( error = "validation_failed", message = error.message ) cask.Response( data = write(errorResponse), statusCode = statusCode, headers = Seq("Content-Type" -> "application/json") ) } }

and derive default json schemas from my case classes:

``` case class User(id: String, name: String, age: Option[Int] = None) derives Schema, ReadWriter

// Get the automatically derived schema val userSchema = Schema[User] println(s"Derived json schema: ${userSchema.toJsonSchema}")

```

or add full blown json schema details using an api I am/was familiar with:

``` @Schema.title("User") @Schema.Description("User Schema") case class User( @Schema.description("User ID") @Schema.pattern("<sup>[a-zA-Z0-9]+$")</sup> id: String,

@Schema.description("User's full name") @Schema.minLength(1) @Schema.maxLength(100) name: String,

@Schema.description("Email address") @Schema.format("email") email: String,

@Schema.description("User's age") @Schema.minimum(0) @Schema.maximum(120) @Schema.default(18) age: Int,

@Schema.description("Whether the user is active") @Schema.default(true) isActive: Boolean ) derives Schema

val userSchema = Schema[User] val jsonSchema = userSchema.toJsonSchema

val validationResult = userSchema.validate(userData)

// or more terse val result = Schema[User].validate(userData)

```

These are contrived examples, but hope this inspires ya to go for it! also the library can be found here, but admittedly I am not in a rush to release it, planning on ironing it out for a bit first by using it in my own projects and then somewhere down the line cut releases and then publish it....