That doesn't strike me as sophisticated, it strikes me as obvious to anyone with a little proficiency in computational thinking and a few days of experience with tool-using LLMs.

The goal is to design a probability distribution to solve your task by taking a complicated probability distribution and conditioning it, and the more detail you put into thinking about ("how to condition for this?" / "when to condition for that?") the better the output you'll see.

(what seems to be meant by "context" is a sequence of these conditioning steps :) )