That is a pitfall that is difficult to mitigate. When using these models your own code base is the primary input, and it will match the style. Garbage in, garbage out. It may be worthwhile to refactor prior using a model. Even having intelligible method and variable names can make a difference. Maybe do a sweep of simple renaming, and adding supplemental explanatory comments, then you might get better results?

Messy brownfield code requires a lot more meta-analysis from previous sessions, just to get all of the spaghetti code into a manageable set of rules and documentation.

Don't just send the agent blindly into the code. Every session, the agent is just going in fresh without any context on how the code works. Break the codebase down to a 10,000 foot view as a summary, and then get more documentation and agent rules for each of its major sections. Good tests help a great deal, too, and if there aren't tests, start building them. Start creating skills just for the codebase, or any common tasks you're asked to do against it.

Also remember that you don't have to write any of this stuff. Have it write the docs, rules, skills, tests, and just review it to make sure it looks right.