There's a mountain of grpc-centric python code at $dayjob and it's been miserable to live with. Maybe it's less awful in c/c++, or at least confers some decent performance there. In python it's hot garbage.
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The only way to know is to dig through CLs? Write a test.
There's also automated tooling to compare protobuff schemas for breaking changes.
If you are building something that needs binary performance that GRPC provides, go for it, but pretending there is no extra cost over doing the obvious thing is not true.
No, it by definition does not, because JSON has no schema. Only your application contains and knows the (expected) structure of the data, but you literally cannot know what structure any random blob of JSON objects will have without a separate schema. When you read a random /docs page telling you "the structure of the resulting JSON object from this request is ...", that's just a schema but written in English instead of code. This has big downstream ramifications.
For example, many APIs make the mistake of parsing JSON and only returning some opaque "Object" type, which you then have to map onto your own domain objects, meaning you actually parse every JSON object twice: once into the opaque structure, and once into your actual application type. This has major efficiency ramifications when you are actually dealing with a lot of JSON. The only way to do better than this is to have a schema in some form -- any form at all, even English prose -- so you can go from the JSON text representation directly into your domain type at parse-time. This is part of the reason why so many JSON libraries in every language tend to have some high level way of declaring a JSON object in the host language, typically as some kind of 'struct' or enum, so that they can automatically derive an actually efficient parsing step and skip intermediate objects. There's just no way around it. JSON doesn't have any schema, and that's part of its appeal, but in practice one always exists somewhere.
You can use protobuf in text-based form too, but from what you said, you're probably screwed anyway if your coworkers are just churning stuff and changing the values of fields and stuff randomly. They're going to change the meaning of JSON fields willy nilly too and there will be nothing to stop you from landing back in step 1.
I will say that the quality of gRPC integrations tends to vary wildly based on language though, which adds debt, you're definitely right about that.
Sure, the removal of a field can cause an application level error, but that is probably the most benign form of failure there is. What's worse is when no error occurs and the data is simply reinterpreted to fit the schema. Then your database will slowly fill up with corrupted garbage data and you'll have to restore from a backup.
What you have essentially accomplished in your response is to miss the entire point.
There are also other problems with protobuf in the sense that the savings aren't actually as big as you'd expect. E.g. there is still costly parsing, the data transmitted over the wire isn't significantly smaller unless you have data that is a poor fit for JSON.