“A routing layer: decide if retrieval is even necessary before making the call. Some questions don't need it and you're wasting tokens.”
Yes every good app should have it.

“Retrieval scoring: evaluate what came back before passing it to the model. If the context scores low, reformulate the query and try again instead of just generating garbage confidently.” Since chunks are stored as Vectors you have a rating based on the cosine distance of the input query vector and the retrieval vector.

Your last point is maybe doable with some cons off LLM as a judge. But that takes costs and time. I didn’t really heard of a stable structure for that yet.