The main point is not about generating skewed distributions, it's about "universality" - the same distribution starts popping up in seemingly unrelated settings. E.g., (large) eigenvalues of random matrices is connected to the length of the longest increasing subsequence of permutations. In a sense it's the discovery of a new kind of central limit theorem.
As someone who has studied statistics in college, there is little original or novel about these finding. Any distribution can be reversed-engineered to find its characteristic function.
