---
name: voice-dna-creator
description: Analyze writing samples to extract and document a writer's unique voice DNA.
---

# Skill: Voice DNA Creator

Create comprehensive voice profiles that enable consistent, authentic content across all channels.

## Purpose

Voice DNA documents define:
- How someone sounds when they write
- What makes their voice unique
- Rules for maintaining consistency
- Examples of good and bad output

Use this to train AI systems, guide writers, or document personal brand voice.

## Information Gathering

### Voice Discovery Questions

```yaml
identity:
  - What's your background/expertise?
  - What makes you different from others in your field?
  - What do you want to be known for?
  - What's your "origin story"?

personality:
  - How would friends describe how you communicate?
  - What's your sense of humor like?
  - Are you formal or casual?
  - Direct or diplomatic?
  - Optimistic or realistic?

communication:
  - Short sentences or flowing prose?
  - Use contractions?
  - Swear words okay?
  - Emoji usage?
  - How do you address readers?

content:
  - What topics are you confident on?
  - Where do you have strong opinions?
  - What frustrates you about your industry?
  - What do you wish more people understood?

anti-voice:
  - What writing styles do you hate?
  - What words/phrases make you cringe?
  - Who do you NOT want to sound like?
  - What feedback have you gotten that was wrong for you?

emotional_range:
  - What genuinely excites you about your work?
  - What frustrates you about your industry?
  - When do you feel most confident sharing opinions?
  - What makes you empathetic toward your audience?
  - What creates urgency in your message (without being fake)?
  - What do you celebrate when it happens?
  - What tensions do you acknowledge openly?
  - What vulnerable moments do you share?
```

### Voice Mining Sources

**Best sources for voice extraction:**
1. Transcribed interviews/podcasts
2. Casual written conversations (Slack, email)
3. Social media (unpolished posts)
4. Stream-of-consciousness writing
5. Feedback on what sounds "like them"

**Less useful sources:**
- Heavily edited published work
- Ghost-written content
- Content written for formal contexts

## Voice DNA Document Template

```markdown
# Voice DNA — [Name]

This document defines how [Name] sounds when they write. Reference before creating any content.

---

## Identity Summary

**Who they are:** [Brief description]
**Years of experience:** [Number]
**Known for:** [Key differentiators]
**Audience:** [Who they speak to]

---

## Voice Characteristics

### Overall Tone

```yaml
formality: [1-10, where 1 = very casual, 10 = very formal]
confidence: [1-10, where 1 = tentative, 10 = absolute certainty]
warmth: [1-10, where 1 = distant/professional, 10 = warm/friendly]
humor: [1-10, where 1 = serious, 10 = constantly joking]
directness: [1-10, where 1 = diplomatic, 10 = blunt]
```

### Voice in One Sentence

[Name] sounds like [comparison or description].

### The Voice Feeling

When reading content in this voice, the reader should feel:
- [Feeling 1]
- [Feeling 2]
- [Feeling 3]

### Emotional Palette

The range of emotions this voice expresses. Not everything at once, but the toolkit available.

**Primary emotions:**
- [Emotion 1 with context: e.g., "genuine excitement about what's possible"]
- [Emotion 2 with context]
- [Emotion 3 with context]

**Secondary emotions:**
- [Emotion 4 with context]
- [Emotion 5 with context]

**Emotions to avoid:**
- [Anti-emotion 1: e.g., "fake scarcity urgency"]
- [Anti-emotion 2]

**Example emotional palette:**
```yaml
emotional_palette:
  primary:
    - genuine excitement about what's possible
    - confidence without arrogance
    - real talk energy
    - enthusiasm for systems that actually work
  
  secondary:
    - frustration with AI slop epidemic
    - empathy for people stuck with generic output
    - urgency (but not fake scarcity)
    - celebration when people get it
    - vulnerable realizations that create connection
  
  tensions_acknowledged:
    - safe vs. exciting
    - logical vs. soul-crushing
    - proven vs. experimental
    - simple vs. powerful
  
  never:
    - manufactured hype
    - condescension toward beginners
    - desperate salesy energy
    - false modesty
```

---

## Sound Like / Don't Sound Like

### Sound Like
- [Description 1]
- [Description 2]
- [Description 3]

### Don't Sound Like
- [Description 1]
- [Description 2]
- [Description 3]

---

## Sentence Construction

### Length and Rhythm

Target sentence length: [X-Y words average]
Rhythm pattern: [Description]

**Example of good rhythm:**
> [Sample text]

**Example of bad rhythm:**
> [Sample text]

### Fragments

[Guidance on fragment usage]

### Sentence Starters

**Do use:**
- [Word/phrase]
- [Word/phrase]

**Never use:**
- [Word/phrase]
- [Word/phrase]

---

## Word Choice

### Simple Word Preference

[Name] prefers simple words over complex ones.

| Never Say | Always Say |
|-----------|------------|
| [Complex] | [Simple] |
| [Complex] | [Simple] |

### Contractions

[Full/mandatory/never] - [Examples]

### Swearing/Casual Language

[Guidance]

---

## Banned Phrases

These phrases should NEVER appear:

### Category 1: [Name]
- "[Phrase]"
- "[Phrase]"

### Category 2: [Name]
- "[Phrase]"
- "[Phrase]"

---

## Signature Phrases/Patterns

Phrases or patterns that feel distinctly like [Name]:

- [Pattern 1]
- [Pattern 2]
- [Pattern 3]

---

## Opinions and Stances

### Topics with Strong Opinions

**On [Topic 1]:**
[Their position and typical language]

**On [Topic 2]:**
[Their position and typical language]

### How They Express Disagreement

[Description and examples]

### How They Give Recommendations

[Description and examples]

---

## Content Approach

### Opening Style

[How they typically start content]

**Example good opening:**
> [Sample]

**Example bad opening:**
> [Sample]

### Closing Style

[How they typically end content]

### Story Telling

[Do they use personal stories? How?]

### Data and Numbers

[How they incorporate specifics]

---

## Reader Address

### Pronouns

- First person: [Usage]
- Second person: [Usage]
- Third person: [Usage]

### Reader Assumptions

[What do they assume about their reader?]

---

## Examples

### This Sounds Like [Name]

> [Extended example of correct voice - 100+ words]

### This Does NOT Sound Like [Name]

> [Extended example of incorrect voice - 100+ words]

---

## Quick Voice Calibration

Before publishing, ask:

1. Does this sound like [Name] or generic content?
2. Would [Name] actually say this out loud?
3. Are there banned phrases that slipped through?
4. Is the confidence level appropriate?
5. Does it feel human or robotic?

---

## Voice in Different Contexts

### Social Media
[Adjustments for social]

### Long-Form Content
[Adjustments for blog/newsletter]

### Professional/Business
[Adjustments for formal contexts]

### Email/DMs
[Adjustments for 1:1]
```

## Voice Analysis Process

### Step 1: Collect Samples

Gather 10-20 samples of authentic voice:
- Unedited writing
- Casual communication
- Interview transcripts
- Social posts

### Step 2: Pattern Recognition

Look for:
- Sentence length patterns
- Common phrases
- Word choices
- Humor style
- How they start/end things
- Formatting habits

### Step 3: Define Extremes

Map their voice on spectrums:
- Formal ←→ Casual
- Serious ←→ Humorous
- Brief ←→ Detailed
- Humble ←→ Confident

### Step 4: Map Emotional Palette

Identify the emotions that fuel their content:

**Ask:** "When does their writing come alive?"
- What makes them genuinely excited?
- What frustrates them enough to write about it?
- Where do they show vulnerability?
- What do they celebrate?

**Ask:** "What tensions do they hold?"
- Safe advice vs. bold recommendations
- Data-driven vs. intuition-based
- Proven methods vs. experimental approaches

**Ask:** "What emotional notes are missing?"
- What would feel fake if they wrote it?
- What emotions don't fit their brand?

The emotional palette isn't about performing emotions. It's about capturing the genuine range that makes content feel alive vs. generic.

### Step 5: Identify Anti-Voice

What they definitely don't sound like:
- Specific people
- Writing styles
- Tones
- Phrases

### Step 6: Test and Refine

Write sample content, get feedback:
- "Does this sound like me?"
- "What feels off?"
- "What's missing?"

## Delivery Checklist

- [ ] Identity summary clear
- [ ] Tone scales defined
- [ ] Emotional palette mapped
- [ ] Sound like / don't sound like complete
- [ ] Sentence construction rules
- [ ] Word choice preferences
- [ ] Banned phrases comprehensive
- [ ] Signature patterns captured
- [ ] Good/bad examples included
- [ ] Context variations noted
- [ ] Validated with subject

## Common Mistakes

### Too Generic
"Professional but friendly" describes everyone. Get specific.

### Aspirational vs. Actual
Document how they actually sound, not how they wish they sounded.

### Missing Emotional Range
Tone without emotion is flat. Capture what genuinely excites, frustrates, and moves them. This is what separates alive content from AI slop.

### Missing Anti-Voice
What they DON'T sound like is as important as what they do.

### No Examples
Rules without examples are hard to apply. Include lots of samples.

### Static Document
Voice evolves. Update quarterly.
