I've read the OMeta paper, the object models paper, and most of the VPRI papers. I'm generally sympathetic to their point of view -- I hate bloated software.

But what has been built with these tools? If OMeta was really better, wouldn't we be using it to parse languages by now? They already have a successor Ohm, which is interesting, but I also think it falls short.

I'm searching desperately for a meta-language to describe my language, so I would use it if it were better.

I think they generally do the first 90%... but skip out on the remaining 90% (sic) you need to make something more generally useful and usable.

I think this is the case with all software. None of it is 100% or even 95%. This is why I've given up on learning anything language specific. If you understand the concepts then you'll be able to re-create the pieces you need in your language of choice because most of the time the other 5% or 10% is context dependent.

Yes I think you're expressing the same sentiment as Knuth, who I quoted in my blog here:

http://www.oilshell.org/blog/2016/12/27.html

I tend to agree and most of my shell is either written from scratch, or copying and adapting small piees of code that are known to work. I take ownership of them rather than using them as libraries.

That is even the case for the Python interpreter, which is the current subject of the blog.

I'm not quite sure, but I think OMeta falls even shorter than the typical piece of software. I'm not saying it's not worthwhile -- it seems like a good piece of research software and probably appropriate for their goals. But to say it generalizes is a different claim.