What you say is true, yet, I observe that people undertake that herculean effort with some frequency.
Whether that's a good idea, and why that is, those would be entirely separate conversations. But it's just an observable fact that languages pick up native implementations of core functionality over time, subject to certain performance restrictions (e.g., I'm sure that if it wouldn't be unusably slow, Python would have a native-Python image library... it's just Python doesn't really have that option).
The effort I'm familiar with is the many attempts to make a decent linear algebra library in haskell. There are a number of libraries with huge work put in, but none has reached blas/lapack parity. Nothing's remotely comparable to numpy in ease of use yet. It picks up more libraries as time goes on, and the existing ones mature, but it's so slow that I'm skeptical they'll ever match numpy's usefulness a decade ago.
I think it's really easy to focus on the big hitters and forget they are the exceptions. Yes, matching lapack, any GUI toolkit, a browser engine, and a handful of other things is a big challenge that takes its own community to overcome, not something any language community can do with an incidental fraction of the community's available firepower.
But those are the exceptions, and often you don't need a best-of-breed solution and may prefer the language-native one.
Again, I'm not theorizing about what could be here; I'm looking out in the world, where I see that most libraries tend to emerge out into a native version if the underlying language can possibly meet the basic requirements for performance and such. This is something that needs to be explained, not explained away.
Also... I love me some Haskell, and on a per capita basis the community is great, but if Rust's community isn't already several times larger and growing faster, I'd be stunned, just to pick one example. Haskell has some very interesting cases of best-of-breed libraries, but it doesn't exhibit the library profusion you get from sheer personpower. (Of course, it doesn't really have the problems you get when your libraries are generated by sheer personpower either.)
Whether that's a good idea, and why that is, those would be entirely separate conversations. But it's just an observable fact that languages pick up native implementations of core functionality over time, subject to certain performance restrictions (e.g., I'm sure that if it wouldn't be unusably slow, Python would have a native-Python image library... it's just Python doesn't really have that option).