Validation check: Flagging raw ChatGPT/Claude inputs at signup to force better clones?

Hey hackers,

I’m building Postessia, a platform designed to deeply clone a user's personal writing style.
But I’m running into a bizarre, modern "garbage in, garbage out" problem.

During onboarding, users frequently paste a raw, unedited text sample straight out of ChatGPT or Claude and say, "This is my writing style.

"The issue?

If you train a style-cloning engine on a generic LLM sample, the outputs just sound like a second-generation copy of generic AI fluff. It kills the product value.

To fix this, I’m planning to add an AI Structural Baseline Check right inside the sample paste box.Before the app processes the sample, the backend will scan for:Low Burstiness: Sentences with a static, machine-like 15-word rhythm.Low Perplexity: Hyper-predictable, mathematically uniform word choices.

AI Framework Flags: The "throat-clearing" intros ("In today's digital age...") and the standard AI buzzword toolkit (tapestry, delve, crucial, testament).

If it triggers the flags, a subtle UI alert will pop up:“We detected standard GPT/Claude structures here.

Postessia is going to actively override this baseline to inject human sentence variance and token diversity into your variations.”Instead of letting them get mediocre results, I want to show them that Postessia actually understands what a real human footprint looks like.

We haven't coded this yet, so I want to ask you:

If an onboarding flow flagged your pasted text as "AI-structured," would you find it highly valuable, or would you feel called out/annoyed?
Does this feature make the cloning tool feel more premium, or is it an unnecessary friction point at signup?
Would love to get your raw feedback before I start building this out over the weekend!