When models start to forage around in the weeds, it's a good idea to restart the session and add more information to the prompt for what it should ignore or assume. For example in ML projects, Claude gets very worried that datasets aren't available or are perhaps responsible. Usually if you tell it outright where you suspect the bug to be (or straight up tell it, even if you're unsure) it will focus on that. Or, make it give you a list of concerns and ask you which are valid.

I've found that having local clones of large library repos (or telling it to look in the environment for packages) is far more effective than relying on built-in knowledge or lousy web search. It can also use ast-grep on those. For some reason the agent frameworks are still terrible about looking up references in a sane way (where in an IDE you would simply go to declaration).