A Claude Code skill that checks your writing against your own voice, not generic AI-pattern rules.
The humanizer by Siqi Chen catches generic AI tells. This does something different: it calibrates to a specific author's voice using their published work as a corpus, then flags drift from that voice alongside the standard AI pattern check.
For drafts:
- Voice drift flags (with rewrites in your register)
- Specificity audit (every unanchored claim, with required substitution)
- AI pattern check (weighted below voice drift)
- Comment stacking detection (attribution lists that aren't building toward a point)
For incoming comments:
- Authenticity score (0–3): specific citation + personal experience + real question
- Synthetic praise detection
- Response length recommendation
For your own replies:
- Three-step engagement check: locate what's new → extend it → redirect
- Voice drift flags
- Tic detection
mkdir -p ~/.claude/skills
git clone https://github.com/dannwaneri/voice-humanizer.git ~/.claude/skills/voice-humanizerThen replace CORPUS.md with your own writing. See SETUP.md for full instructions.
Generic humanizers check for patterns to avoid. This one checks for patterns to match — your specific cadences, the kinds of specificity you reach for, what good writing in your voice actually sounds like vs what Claude-flavored-you sounds like.
The corpus is private (.gitignore). The skill and structure are public.
Here's voice-humanizer catching drift that a generic humanizer would miss.
Before (draft):
The fingerprint tracks rhythm patterns, paragraph opening style, specificity signals, what you reach for when you need a concrete detail, and — just as important — what you don't do.
Flag:
Voice drift — list of five items where your corpus shows you compress to two. Em dash doing emotional emphasis work your corpus handles structurally.
After:
The fingerprint tracks what you reach for and — just as important — what you don't. Rhythm, specificity, the patterns absent from your corpus that signal drift.
No AI pattern was triggered. A generic humanizer would have passed this. Voice-humanizer caught it because the corpus knew this author compresses lists. That's the difference.
Built for Claude Code. Claude desktop users see SETUP.md for manual usage. Inspired by blader/humanizer.