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I would recommend exploring OpenRPC for those who have not yet seen it. It brings protocol-buffer-like definitions (components), RPC definitions and centralised error definitions.
Notably missing both Go and Rust
> Skir is a universal language for representing data types, constants, and RPC interfaces. Define your schema once in a .skir file and generate idiomatic, type-safe code in TypeScript, Python, Java, C++, and more.

Maybe I'm missing some additional features but that's exactly what https://buf.build/plugins/typescript does for Protobuf already, with the advantage that you can just keep Protobuf and all the battle hardened tooling that comes with it.

https://capnproto.org/ has been my goto since forever. Made by the protobuf inventor
I've been dabbling with the newer Cap'n Web, whose nicely descriptive README's first line says:

> Cap'n Web is a spiritual sibling to Cap'n Proto (and is created by the same author), but designed to play nice in the web stack.

It's just JSON, which has up and down sides. But things like promise pipelining are such a huge upside versus everything else: you can refer to results (and maybe send them around?) and kick off new work based on those results, before you even get the result back.

This is far far far superior to everything else, totally different ball-game.

I've been a little rebuffed by wasm when I try, keep getting too close to some gravitational event horizon & get sucked in & give up, but for more data-throughput oriented systems, I'm still hoping wrpc ends up being a fantastic pick. https://github.com/bytecodealliance/wrpc . Also Apache Arrow Flight, which I know less about, has mad traction in serious data-throughput systems, which being adjacent to amazingly popular Apache Arrow makes sense. https://arrow.apache.org/docs/format/Flight.html

Obligatory dense field numbers seems like a massive downside, the problems of which would become evident after a busy repo has been open for a few days.
I spent some time in the actual compiler source. There's real work here, genuinely good ideas.

The best thing Skir does is strict generated constructors. You add a field, every construction site lights up. Protobuf's "silently default everything" model has caused mass production incidents at real companies. This is a legitimately better default.

Dense JSON is interesting but the docs gloss over the tradeoff: your serialized data is [3, 4, "P"]. If you ever lose your schema, or a human needs to read a payload in a log, you're staring at unlabeled arrays. Protobuf binary has the same problem but nobody markets binary as "easy to inspect with standard tools." The "serialize now, deserialize in 100 years" claim has a real asterisk. Compatibility checking requires you to opt into stable record IDs and maintain snapshots. If you skip that (and the docs' own examples often do), the CLI literally warns you: "breaking changes cannot be detected." So it's less "built-in safety" and more "safety available if you follow the discipline." Which is... also what Protobuf offers.

The Rust-style enum unification is genuinely cleaner than Protobuf's enum/oneof split. No notes there, that's just better language design.

Minor thing that bothered me disproportionately: the constant syntax in the docs (x = 600) doesn't match what the parser actually accepts (x: 600).

The weirdest thing that bugged the heck out of me was the tagline, "like protos but better", that's doing the project no favors.

I think this would land better if it were positioned as "Protobuf, but fresh" rather than "Protobuf, but better." The interesting conversation is which opinions are right, not whether one tool is universally superior.

Quite frankly, I don't use protobuf because it seems like an unapproachable monolith, and I'm not at FAANG anymore, just a solo dev. No one's gonna complain if I don't. But I do love the idea of something simpler thats easy to wrap my mind around.

That's why "but fresh" hits nice to me, and I have a feeling it might be more appealing than you'd think - ex. it's hard to believe a 2 month old project is strictly better than whatever mess and history protobufs gone through with tons of engineers paid to use and work on it. It is easy to believe it covers 99% of what Protobuf does already, and any crazy edge cases that pop up (they always do, eventually :), will be easy to understand and fix.

If I may suggest, Swift support will be more than appreciated, to consider it for a viable protocol for connecting backend with mobile applications.
That “compact JSON” format reminds me if the special protobufs JSON format that Google uses in their APIs that has very little public documentation. Does anyone happen to know why Google uses that, and to OP, were you inspired by that format?
I don't know but if I had to guess.

1. Google uses protobufs everywhere, so having something that behaves equivalently is very valuable. For example in protobuf renaming fields is safe, so if they used field names in the JSON it would be protobuf incompatible.

2. It is usually more efficient because you don't send field names. (Unless the struct is very sparse it is probably smaller on the wire, serialized JS usage may be harder to evaluate since JS engines are probably more optimized for structs than heterogeneous arrays).

3. Presumably the ability to use the native JSON parsing is beneficial over a binary parser in many cases (smaller code size and probably faster until the code gets very hot and JITed).

I don't know the reason TextFormat was invented, but in practice it's way easier to work with TextFormat than JSON in the context of Protos.

Consider numeric types -

JSON: number aka 64-bit IEEE 754 floating point

Proto: signed and unsigned int 8, 16, 32, 64-bit, float, double

I can only imagine the carnage saved by not accidentally chopping of the top 10 bits (or something similar) of every int64 identifier when it happens to get processed by a perfectly normal, standards compliant JSON processor.

It's true that most int64 fields could be just fine with int54. It's also true that some fields actually use those bits in practice.

Also, the JSPB format references tag numbers rather than field names. It's not really readable. For TextProto it might be a log output, or a config file, or a test, which are all have ways of catching field name discrepancies (or it doesn't matter). For the primary transport layer to the browser, the field name isn't a forward compatible/safe way to reference the schema.

So oddly the engineers complaining about the multiple text formats are also saved from a fair number of bugs by being forced to use tools more suited to their specific situation.

JSON is slightly worse than you describe - the JSON language doesn’t restrict you to 64bit floats, but most implementations do as you describe. On the other hand, the JSON language doesn’t support NaNs or infinities, so the union of language and implementation means that in practice JSON is strictly weaker than IEEE 754.
Like this but zero copy, easy migration/versioning, Rust and WASM support.
Looks nice. But what are the use cases of this? I'm still trying to figure that out.
Impressive. Some interop with established standards such as OpenAPI or gRPC would make it an easier sell for non-greenfield projects
Did you look at other formats like Avro, Ion etc? Some feedback:

1. Dense json

Interesting idea. You can also just keep the compact binary if you just tag each payload with a schema id (see Avro). This also allows a generic reader to decode any binary format by reading the schema and then interpreting the binary payload, which is really useful. A secondary benefit is you never ever misinterpret a payload. I have seen bugs with protobufs misinterpreted since there is no connection handshake and interpretation is akin to 'cast'.

2. Compatibility checks

+100 there's not reason to allow breaking changes by default

3. Adding fields to a type: should you have to update all call sites?

I'm not so sure this is the right default. If I add a field to a core type used by 10 services, this requires rebuilding and deploying all of them.

4. enum looks great. what about backcompat when adding new enum fields? or sometimes when you need to 'upgrade' an atomic to an enum?

> For optional types, 0 is decoded as the default value of the underlying type (e.g. string? decodes 0 as "", not null).

In the "dense JSON" format, isn't representing removed/absent struct fields with `0` and not `null` backwards incompatible?

If you remove or are unaware of a `int32?` field, old consumers will suddenly think the value is present as a "default" value rather than absent

Apart from the comparison with Protobuf, how does it compare to flatbuffers, capnproto, messagepack, jsonbinpack... ?
flatbuffers and capnproto are in the game of trying to make serialization to binary format as efficient as possible. Their goal is trying to beat benchmarks: how long it takes to convert an object to bytes and vice-versa. It's cool, but I personally think that for most use cases (not all), serialization efficiency shouldn't be the primary goal: serialization time is often negligible compared to time it takes to send data over the wire, and it's less important than other features (e.g. quality of the generated API) that some of these techs might neglect. I have an example to illustrate this. With Proto3, Google decided that when encoding a `string` field in C++, it would not perform UTF-8 validation. This leads to better benchmark metrics. This has also been a horrible mistake that led to many bugs which have costed so much in eng hours, since for example the same protobuf C++ API fails at deserialization when it encounters an invalid UTF-8 string.

As per messagepack, jsonbinpack, these seem to be layers on top of JSON to make JSON more compact. They still use field names for field identity, which I think can be problematic for long-term data persistence since it prevents renaming fields. I think the Protobuf/Thrift approach of using meaningless field numbers in serialization forms is better.

This seems a Chesterton's fence fail.

protobuf solved serialization with schema evolution back/forward compatibility.

Skir seems to have great devex for the codegen part, but that's the least interesting aspect of protobufs. I don't see how the serialization this proposes fixes it without the numerical tagging equivalent.

I had my fair share of frustration with proto as well. I appreciate in Skir

GH style import. This is a big one I wish proto had in the first place. The entire idea of a proto registry feels reactive to me when, ideally, you want to pull in a versioned shared file to import that is verified by the compiler long before serve or client verifies the payload schema.

Schema validation and compatibility checks on CI. Again a big one and critical to catch issues early.

Enums done right... No further comment required.

I think with some more attention to details e.g. hammering out the gaps some other comments have identified and more language support e.g. Rust, Go, C# this can actually work out over time.

Here is an idea to contemplate as a side gig with your favorite Ai assistant: A tool to convert proto to Skir. Or at least as much as possible. As someone who had to maintain larger and complex proto files, a lot of proto specific pain points are addressed.

The only concern i have is timing. Ten years ago this would have been a smash hit. These days, we have Thrift and similar meaning the bar is definitely higher. That's not necessarily bad, but one needs to be mindful about differentiation to the existing proto alternatives.

I hope this project gains trajectory and community especially from the frustrated proto folks.

Hey, thanks a lot for the comment! I share your frustration with protobuf: although I think it's great, it carries a few design flaws which are hard to fix at this point and they create pain points which are not going away.

I completely agree with you about timing, wish I had done this 10 years ago :)

"Here is an idea to contemplate as a side gig with your favorite Ai assistant: A tool to convert proto to Skir. Or at least as much as possible. As someone who had to maintain larger and complex proto files, a lot of proto specific pain points are addressed." < I tried asking Claude: "Migrate this project from protobuf to Skir, see https://skir.build/" and it works pretty well. I created http://skir.build/llms.txt which helps with this. The pain point is data migration though, and as much as I want Skir to succeed: I cannot recommend people migrating from protobuf to Skir if they have some persisted data to migrate, the effort is probably not worth it.

Definitely interesting and seems to be a nice improvement over Protobuf. Especially for Python, Protobuf bindings for Python were made probably after taking a lot of hallucinogenic drugs.

I like constants, great addition.

Things that I'll miss:

1. Oneof fields. There are enums, but it looks like it's not possible to have ad-hoc onefos?

2. Streaming requests/responses.

3. Introspection and annotations.

4. Go bindings.

Thanks for the comment! Agree with you about the horrible Protobuf-to-Python bidding, it was a big frustration and definitely contributed to me wanting to build Skir.

1. You can create an enum with just "wrapper" fields, that's exactly like a oneof

2. Totally fair, I'm planning to work on this later this year, probably Q3 (priority is adding support to 4 more languages, and then I'll get to it)

3. So there is introspection in the 6 targeted languages, and I think I did it a bit better than protobuf because it generally has better type safety. Example in C++: https://github.com/gepheum/skir-cc-example/blob/main/string_...;

Typescript: https://skir.build/docs/typescript#reflection

I realize I haven't documented it in Python (although it is available and generally the same API as Typescript), will fix that

However, you're right that there is no support yet for annotations. Still trying to gauge whether that's needed

4. Assuming you mean Go language: working on that now, hoping to have C#, Go, Rust and Swift in the next 2-3 months.