It is indeed not something clarified by the code snippets; In normal feedforward layers, it is common to choose the "hidden_dim = 4 x emb_dim", while in GLU feedforward layer, the convention is to use "hidden_dim = 2/3 * regular_ffn_hidden_dim" (to keep the overall number of parameters roughly the same). In the case of gpt-oss, they chose to go a bit more extreme and set "hidden_dim = emb_dim", thus reducing the overall number of parameters!
It wouldn't be difficult at all if the optimal running technique was known before hand; I think the goal of many of these RL exercises is to either i) find a better solution than what we may have imagined or ii) confirm that our knowledge was indeed the best possible solution!
I don't have any ideas on how to make it more "human-like", but for some words it would have been nice to have their definitions (maybe in a tooltip over the words).