Prompt matters. Obviously if you want another model opinion you must generate from the scratch using the same prompt and then you can try to synthesize, but working with an existing response can work if desired. I use explicit instructions to find issues with assigned severities and then these are going through the panel of judges, only issues passing certain threshold are fixed in the original response.

I'll share a revelation which vastly improved my results: tell judges to evaluate truth and usefulness/should-be-fixed axis separately. Because inevitably with a prompt that is forcing to find issues you will end up with nitpicks. Plus truth axis allows to better evaluate the issue-finder models for your use case.

That's some part of what happens when I generate explanations like this one: https://hanzirama.com/character/%E6%9D%A5#explain - at this point the site is a small side product of my LLMs-evaluation machinery.

Bonus content for patient readers: if you need top quality you will likely need to pin provider(s) on OR, :exacto is not enough to get good repeatable results especially for open-weights models.