Being schemaless is deliberate design decision as it eliminates the need for managing and building schema files. By not requiring schema, messages are always readable to arbitrary consumers.
If you want schema, it must be done by the application through runtime type checking. All messages contain type information. Though I do see the value of adding pydantic-like schema checking in the future.
EDIT: Regarding message size, Lite³ does demand a message size penalty for being schemaless and fully indexed at the same time. Though if you are using it in an RPC / streaming setting, this can be negated through brotli/zstd/dict compression.
The thing about schemaless is that it's great for usability and I like it with JSON but as with JSON when we develop applications in reality at the end of the day you always have some kind of schema, whether it's written down or not. Like you alluded with pydantic, the application is going to rely on the data being in some sort of shape, even if it's very defensively written and practically everything is optional, you still end up relying something. That would be the informal schema so in my mind if I have a schema anyway no matter what... then maybe this should be supported in the serialization format/library to give me the benefit of size reductions.
I very often use the best of both worlds. Have schema for messages, but some messages have additional "info" field, which is typically json for other data not defined elsewhere or not added to every message.
The library contains iterator functions that can be used to recursively traverse a message from the root and discover the entire structure. Then every value can be checked for defined constraints appropriately while at the same time validating the traversal paths. Also a schema description format is needed, perhaps something like JSONSchema can be used.
Doing this by definition requires processing an entire message which can be a little slow, so it is best done in C and exposed through CPython bindings / CFFI.
If you want schema, it must be done by the application through runtime type checking. All messages contain type information. Though I do see the value of adding pydantic-like schema checking in the future.
EDIT: Regarding message size, Lite³ does demand a message size penalty for being schemaless and fully indexed at the same time. Though if you are using it in an RPC / streaming setting, this can be negated through brotli/zstd/dict compression.