Voice Fingerprint — Preserving the user's voice while scrubbing skill

Voice Fingerprint — Preserving the user's voice while scrubbing

The humanizer is destructive by design. Every pass deletes or substitutes tokens. That's fine for AI tells. It's a bug for the user's actual voice.

This file lists the signals to preserve, even when they overlap with rules in scrub-rules.md.

Contents

• Preserve unconditionally (do NOT scrub these)
• Preserve when sample voice is provided
• Conflict resolution
• How to build a voice fingerprint from samples (sketch)
• Examples
• Don't fabricate

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Preserve unconditionally (do NOT scrub these)

These are voice signatures, not AI tells. Leave them alone in every tier including --mode all.

Pattern	Why it's voice, not AI
Lowercase sentence starts (closed our seed on a tuesday...)	Users like Serge use this as a deliberate cadence cue. Capitalizing flattens their voice.
.. as a soft pause	This is the humanizer's officially-blessed alternative to em dash. Removing it has nowhere to go.
Sentence fragments (Worth it., Every time., Not even close.)	Pass 2 ADDS fragments. Don't remove the ones already there.
Contractions (don't, it's, you're, we're)	Mandatory for natural rhythm. Scrubbing curly apostrophes is fine; expanding contractions is not.
First-person sensory detail (my hands shook, the room went quiet)	Pass 3 demands these. Never strip.
Specific numbers ($47k, 9:14am, 47 days)	Pass 3 demands these. Never strip.
Named entities (HubSpot, Tuesday morning, brand names)	Pass 3 demands these. Capitalize properly per non-negotiable rule.
Self-correction within a paragraph (actually no, correction:)	Burstiness signal. Real humans circle back.

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Preserve when sample voice is provided

If the user passes optional target_voice_samples (their last 5-10 LinkedIn posts), extract:

1. Sentence-length distribution. If they routinely write 4-6 word sentences, don't force 12+ word "minimum lengths" on Pass 2.
2. Vocabulary fingerprint. Words they use 3+ times across samples are part of their voice — even if those words appear on the strict blacklist. Flag for user review rather than auto-substituting.
3. Punctuation habits. Some users use ... instead of .., or unbroken comma chains. Match the dominant pattern.
4. Opener patterns. If they always start with a number (47 days ago, $2M ARR) or a name (Jake said), preserve that template.
5. Closer patterns. If they always close with a single fragment + period (no question), don't force a question CTA.

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Conflict resolution

When a scrub rule fires on a token that's also in the user's voice fingerprint:

Tier	Behavior
Forensic	Always scrub. Forensic rules catch model leakage; if the user's voice fingerprint contains oaicite it's because they pasted AI output.
Strict	Flag for user review. Don't auto-substitute. The user gets to decide.
Aesthetic	Skip the rule entirely. Aesthetic rules already explicitly tolerate human-writer defenses.

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How to build a voice fingerprint from samples (sketch)

from collections import Counter
import re

def build_voice_fingerprint(samples: list[str]) -> dict:
    text = "\n".join(samples)
    sentences = re.split(r'(?<=[.!?])\s+', text)

    return {
        "sentence_lengths": [len(s.split()) for s in sentences],
        "vocab_freq": Counter(re.findall(r"\b[a-z][a-z']{2,}\b", text.lower())),
        "starts_lowercase_pct": sum(1 for s in sentences if s and s[0].islower()) / max(len(sentences), 1),
        "uses_double_dot": ".." in text,
        "uses_triple_dot": "..." in text,
        "punctuation_freq": Counter(c for c in text if c in ".!?,;:"),
        "fragment_pct": sum(1 for s in sentences if len(s.split()) <= 4) / max(len(sentences), 1),
    }

The skill should call this on target_voice_samples before running Pass 1.

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Examples

Example 1 — .. as soft pause (preserve)

Input: closed our seed.. then everything broke

Wrong (scrubs the ..): closed our seed. then everything broke

Right (preserve): closed our seed.. then everything broke

The .. is on the explicit preserve list. Period substitution is for --, not ...

Example 2 — lowercase start (preserve)

Input: closed our seed on a tuesday morning at 9:14am

Wrong (capitalizes): Closed our seed on a Tuesday morning at 9:14am

Right (preserve closed, capitalize Tuesday): closed our seed on a Tuesday morning at 9:14am

The non-negotiable rule says capitalize NAMES — Tuesday is a proper noun in date context, but the sentence-initial closed stays lowercase per voice rule.

Example 3. Voice-fingerprint vocabulary collision (flag, don't substitute)

User samples contain harness 4 times across 6 posts (clearly part of their voice — they work in horse-training tech).

Strict tier scrub rule says: harness → use.

Right behavior: flag for user review. Output: [VOICE-CONFLICT: 'harness' is in your voice fingerprint (4 uses in past samples) but matches strict-tier scrub. Keep or substitute?]

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Don't fabricate

The non-negotiable rule (SKILL.md line: "Never introduce facts that weren't in the input") overrides voice-fingerprint matching. If a sample contains specific numbers, do NOT carry those numbers into a different post. Only use numbers the current input already supplies.