Talking to the person who gave it to you, in my experience.

In my own testing, Pangram is excellent at detecting the default output styles of LLMs.

If you tell the LLM to change its output style, so it’s not full of “load-bearing spaced em dashes that aren’t X, they aren’t Y. they’re Z.” constructions (which humans are pretty good at detecting on their own), the false negative rate soars.

The question you're asking has nothing to do with who has the burden of proof when it comes to claims about Pangram, but I'll answer it anyway.

Today, the best way is probably Pangram. Tomorrow, it might not be, especially if they try to push their recall up.

You might have to make peace with the fact that there may not always be a tool that does what you want.