The point is that, with a sufficiently complex setup (with skills, MCPs, prompts, etc.) the difference in AI models will impact the quality of work. You might not care now, but you might care when you have 2 million lines of code and zero idea whats going on.

The point is vendor lock-in. The vibe coding community has reinvented vendor lock-in and is bound to repeat every mistake associated with it.

Can you give an example of a skill or prompt that would work in Claude and not in the others?

Pretty much every single detailed prompt made after trial, error, and refinement is tailored to a specific LLM. They will all perform worse used with other LLMs than a similar prompt tailored for the second LLM would perform, and at times quite poorly.

How well would it work to ask the working LLM to rewrite the prompt to get the best results? Do the models understand enough about themselves to do that?

Claude has a /product-self-knowledge skill, and I am sure the others have something similar. So yes, it is possible if you work with care, as necessary with all things LLM related. There are hundreds if not thousands of skills on github that were created just this way.

That's kind of pointless, then, because what happens when Anthropic releases their next-gen model?

It's not like you aim to do it, you are just in a feedback loop improving results for the tool you are using. It is inherent in any prompt developed through iteration.