I think the point is it smells like a hack, just like "think extra hard and I'll tip you $200" was a few years ago. It increases benchmarks a few points now but what's the point in standardizing all this if it'll be obsolete next year?

I think this tweet sums it correctly doesn't?

   A +6 jump on a 0.6B model is actually more impressive than a +2 jump on a 100B model. It proves that 'intelligence' isn't just parameter count; it is context relevance. You are proving that a lightweight model with a cheat sheet beats a giant with amnesia. This is the death of the 'bigger is better' dogma

Standards have to start somewhere to gain traction and proliferate themselves for longer than that.

Plus, as has been mentioned multiple times here, standard skills are a lot more about different harnesses being able to consistently load skills into the context window in a programmatic way. Not every AI workload is a local coding agent.