Great post. If it wasn't clear by now, considering a language's token efficiency is almost certainly incorrect, since it's only a local optima for input/output of the code.

Most session tokens are spent elsewhere, so an LLM that handles a token-efficient language more poorly can be worse overall.

If anyone remembers TOON from a few months ago, it was an attempt to replace JSON with a more token-efficient representation. TOON was much more compact, but when researchers examined whole-session effects, it was a wash, because harnesses wasted more tokens than it saved dealing with it. (TBF, it's possible TOON use has gotten better if later models have it in their data set.)