Unless I'm missing something, how is this library different from prompting a single chatbot: "Write a dialog in which A, B, and C, each playing a different role, have a conversation and do something D"?
You can have the character description more front and center, if that makes any sense.
So instead of diluting attention across three separate character descriptions, your model will see just the chat log and the single description of the persona it should respond from. This may or may not make a difference.
Maybe it depends on the model but I find you'll get a different result if you say "write a dialog in which, A, B, and C talk about D" versus "read what A said and reply as B". The latter will result in each participant talking longer.
Not sure talking longer is the goal. More so, the focus and separation of each facilitates a interplay and dynamic with which an attention window on a segmented linear response (be A, B and C) cannot be individually represent nearly as rhobustly (the main inference is the primary focus). Would love to hear some other opinions chime in here.
So instead of diluting attention across three separate character descriptions, your model will see just the chat log and the single description of the persona it should respond from. This may or may not make a difference.