This paper wasn't for SKILLS per se, but for LLMs, and suggests that LLMs can't follow too many constraints at one time very well https://arxiv.org/abs/2608.12426 . Other papers suggest that LLMs show more information sparsity in the results with negative constraints.

Good one; reading this briefly took me back to the days of “Needle in a Haystack” being super challenging for LLMs. Maybe there needs to be a benchmark of “Rule in a Haystack” (similar to information one, testing not only independent rules also the ones that need hops) to clarify model performance regarding this. Thank you for the resource.