Great idea! We had a similar idea back in 2015 with SKLL[1]. We are still actively maintaining it and it’s definitely been helpful to many folks, including many outside our organization, over the years! Wishing you the best!
Some scientists just want to build cool things and not have to worry about publishing. Some of my colleagues over the years have moved to Apple and startups for this reason.
As someone who did contribute to NLTK quite a bit, it was quite useful back in the day especially when I had to teach NLP/CL to linguistics (non-CS) graduate students. I agree with Radim that NLTK has a purpose - and it's not to implement the latest and the greatest NLP algorithms. I'm glad NLTK exists and although it is not what I use today, I'm pretty sure whatever I do use today (CoreNLP, gensim, etc.) will all be superseded by the next best thing a decade from now.
[1] https://github.com/EducationalTestingService/skll