/humanize — AI-voice audit (detect-and-flag)

Read the target file (or all paper-like files), audit for the canonical AI-voice tells in academic prose, and write a structured report. The skill does not rewrite. The author edits.

Why this skill exists

Referees and editors increasingly recognise AI-generated prose. The tells are not stylistic preferences — they're statistically conspicuous patterns the LLM training distribution produces at higher rates than human academic writers. Five reasons to audit before submission:

1. Reviewer suspicion is a tax. Even good substance pays a credibility tax if the prose reads as AI-drafted.
2. Journal policy is tightening. A growing number of venues require disclosure or prohibit AI-drafted text.
3. AI tells signal weak content. Boilerplate transitions ("Moreover", "It is important to note") almost always cover up logical gaps the author didn't think through.
4. You are not the tells. Even authors who use AI tools heavily can preserve their own voice by stripping the model's lexical fingerprint.
5. The fix is cheap once you can see it. The cost is detection, not rewriting — once the report flags the tells, removal is mechanical.

What this skill is NOT