voice-extractor

Voice Extractor

AI-generated content all sounds the same. The fix isn't better prompts — it's teaching the AI how you actually communicate.

This skill extracts your communication DNA from writing samples and produces a Voice Guide: documented, tested, and ready to use.

Mode

Detect from context or ask: "Quick voice snapshot, full Voice Guide, or full guide with examples?"

Default: standard — use quick if they just need a fast reference. Use deep if they're onboarding a ghostwriter or building a content team.

Context Loading Gates

Before extracting, collect:

• Writing samples — minimum 3 samples OR 500 total words (see priority list below)
• Purpose of voice guide — AI training? Ghostwriter onboarding? Team alignment?
• Confidence zones — Any topics where they want to sound more/less authoritative?
• Known anti-patterns — Any words or phrases they already know they want to avoid?

Sample priority (most → least authentic):

1. Casual Slack or email (raw, unedited voice)
2. Podcast or call transcript
3. LinkedIn posts or articles
4. Website copy (often edited, less authentic)

Minimum sample gate: If samples total under 500 words, stop:

"These samples are too short to extract reliable patterns. Please add 2-3 more — emails, Slack messages, or transcripts work best. The messier and more casual, the better."

Do not attempt full extraction from under 500 words. Offer quick mode instead.

Phase 1: Sample Quality Assessment

Before extracting, reason through:

1. Sample authenticity: Are these samples from edited/polished contexts (website, press) or raw contexts (Slack, email)? More polish = less authentic voice.
2. Sample variety: Do the samples cover different contexts (professional, casual, educational)? Single-context samples produce single-dimension voice guides.
3. Exclusion check: Identify and flag patterns that are NOT the authentic voice:
   • Platform formatting tics (LinkedIn line breaks, Twitter brevity forcing)
   • Typos and autocorrect errors
   • Phrases borrowed from others (quotes, retweets)
   • Unusually formal writing (legal docs, press releases)
4. Sample size adequacy: Is there enough material for full mode, or should I use quick mode?

Output a sample assessment:

"I have [X samples / Y words] to work with. Quality: [high/medium — why]. I'll use [full/quick] mode. Excluding: [any patterns and why]."

Phase 2: Core Energy Extraction

Identify the fundamental communication mode:

Role:

• Teacher (breaks things down systematically)
• Challenger (pushes back on assumptions)
• Cheerleader (builds confidence and momentum)
• Straight-shooter (cuts through BS efficiently)

Default energy:

• Calm authority ("Here's what works.")
• High enthusiasm ("This is exciting — let me show you.")
• Understated confidence ("I've seen this a hundred times.")

Recurring themes: What topics appear unprompted across samples? These are the things they actually care about.

Phase 3: Phrase Extraction (Systematic)

Scan all samples and extract:

Transition phrases (how they shift topics):

• Quote exact examples from samples
• Pattern: "Here's the thing...", "What I've learned...", "Let me put it differently..."

Emphasis phrases (how they land a point):

• Quote exact examples
• Pattern: "The reality is...", "This is the part people miss...", "Here's the actual problem..."

Closers (how they wrap up):

• Quote exact examples
• Pattern: "That's the move.", "Start there.", "You've got this."

Phase 4: Confidence Zone Mapping

Map their stated expertise areas to each zone. This calibration is what makes the voice feel real vs. one-dimensional.

Phase 5: Anti-Pattern Documentation

Extract what they'd NEVER say:

• Words that would feel wrong in their voice
• Phrases that make them cringe
• Tones they naturally avoid
• Industry jargon they hate

Source these from sample evidence where possible: "You never used [word] across [X samples] — it doesn't fit your voice."

Phase 6: Validation Test (REQUIRED)

After extracting the full profile, generate 2 test sentences on the same topic:

Version A (using the extracted voice profile):

"[Sample sentence in their voice]"

Version B (wrong voice — contrasting example):

"[Same content, different voice — shows what to avoid]"

Ask the user: "Does Version A actually sound like you when you're not overthinking it? What feels off?"

This validation catches extraction errors before the guide is put into production.

Quick Mode (--quick)

When samples are thin (300–500 words) or time is short:

1. Read 3 samples fast
2. Pull 10 signature phrases
3. Note 3 things they'd never say
4. Write 1 sentence describing their energy

Output: Minimum viable voice guide.

Difference from full mode:

• Quick: ~10 phrases, 3 anti-patterns, 1-sentence energy descriptor
• Full: Complete profile with confidence calibration, validated test sentences, and source-cited examples

Phase 7: Self-Critique Pass (REQUIRED)

After generating the Voice Guide:

• Are the extracted phrases actually from the samples, or am I inferring them?
• Does the anti-pattern list include specific words/phrases, or just vague categories?
• Do the validation test sentences demonstrate a real difference between in-voice and out-of-voice?
• Is the confidence zone mapping specific to named topics, or just generic?
• Would a ghostwriter be able to use this guide without asking follow-up questions?

Flag any issues: "The anti-pattern section only has 2 entries — not enough for a usable guide. I need more samples or direct input from the user."

Output Structure

## Voice Guide: [Name] — [Date

Skill by Brian Wagner | AI Marketing Architect | brianrwagner.com