voice-analyzer

name	voice-analyzer
description	Analyze writing samples to create a portable voice profile and style guide. Use when setting up voice-matched AI writing, onboarding to a new project, or refreshing an outdated style guide.
use_when	User wants to create a voice profile, analyze writing samples for style, set up voice-matched AI writing, or create a VOICE.md style guide.
user-invocable	true

Extract voice patterns from writing samples and generate a comprehensive, portable style guide (VOICE.md).

The output becomes infrastructure -- a reference document used every time you work with AI to maintain your authentic voice instead of producing generic content.

<quick_start> Provide 3-5 writing samples where your voice feels strongest (500-2000 words each). The skill will:

1. Analyze patterns across all samples
2. Identify your distinctive voice markers
3. Generate a VOICE.md style guide
4. Create a forbidden phrases list specific to your anti-patterns
5. Provide testing prompts to validate the guide

Ideal samples: Newsletter issues, blog posts, emails you're proud of, social media threads that felt "like you"

Avoid: Heavily edited corporate content, collaborative pieces, anything that felt forced </quick_start>

<sample_gathering_guidance> <what_makes_good_samples> Include samples that:

• You wrote when feeling confident and natural
• Received feedback like "this sounds just like you"
• You'd be happy to write again
• Show your voice across different contexts (casual, professional, explanatory)
• Are at least 500 words (longer is better for pattern detection)

Avoid samples that:

• Were heavily edited by others
• Feel generic or corporate even to you
• Were written under heavy constraints
• Don't represent how you want to sound going forward </what_makes_good_samples>

<minimum_requirements>

• Minimum: 3 samples, 500+ words each
• Ideal: 5-7 samples, 1000+ words each
• Advanced: 10+ samples including different formats (email, long-form, social)

More samples = more accurate pattern detection, but diminishing returns after 10. </minimum_requirements>

<alternative_sources> If you don't have strong writing samples:

Voice memo transcription: Record yourself explaining something you know well. Transcribe it. Your speaking patterns often reveal writing voice better than forced writing.

Email archaeology: Search sent mail for messages where you were being genuinely helpful, not performing professionalism.

Chat/Slack messages: Longer explanatory messages often show natural voice patterns.

Old social media: Before you started "performing" for algorithms. </alternative_sources> </sample_gathering_guidance>

<analysis_framework> When analyzing samples, examine these dimensions:

**Sentence Structure:** - Average sentence length (short/punchy vs. long/flowing) - Length variation (uniform vs. high variance) - Sentence starters (do you vary, or repeat patterns?) - Use of fragments for emphasis - Complex vs. simple sentence construction **Word Choice:** - Formality level (casual/conversational vs. professional/technical) - Jargon usage (industry terms, insider language) - Characteristic phrases you repeat - Curse words or mild profanity patterns - Filler words ("actually," "basically," "honestly") - Intensifiers you favor ("really," "absolutely," "quite") **Paragraph Patterns:** - Typical paragraph length - How you transition between ideas - Use of one-sentence paragraphs for emphasis - Section structure and pacing - How you open and close pieces **Voice Personality:** - Humor style (dry, self-deprecating, none) - Level of directness - How you handle uncertainty (hedge vs. commit) - Personal disclosure level - Relationship with reader (peer, teacher, friend) **Organization:** - How you use lists vs. prose - Header/subheader patterns - Use of examples and analogies - How you introduce and conclude topics - Formatting preferences (bold, italics, em-dashes) **Stance and Authority:** - How strongly you state opinions - How you qualify claims - Use of "I" vs. "we" vs. "you" - How you handle disagreement or controversy - Confidence level in assertions

<output_format> Generate a VOICE.md file with this structure:

# Voice Profile: [Name]
Generated: [Date]
Based on: [X] writing samples ([total word count] words)

## Voice Summary
[2-3 sentence description of overall voice character]

## Core Voice Characteristics

### Sentence Patterns
- Average length: [X] words
- Variation: [Low/Medium/High]
- Notable patterns: [specific observations]

### Vocabulary Fingerprint
- Formality: [Casual/Conversational/Professional/Formal]
- Characteristic phrases: [list]
- Words to use freely: [list]

### Rhythm and Flow
- Paragraph style: [description]
- Transition patterns: [description]
- Pacing notes: [description]

### Tone Markers
- Primary tone: [description]
- Humor style: [description]
- Reader relationship: [description]

### Structural Habits
- List vs. prose preference: [description]
- Formatting patterns: [description]

### Opinion Expression
- Directness level: [1-10]
- Qualification style: [description]
- Authority stance: [description]

## The Forbidden List

### Never Use (These kill your voice)
- [phrase 1]
- [phrase 2]
- [etc.]

### Use Sparingly (Context-dependent)
- [phrase 1] - only when [context]
- [etc.]

### Watch for Clusters (OK alone, problematic together)
- [pattern description]

## Voice Maintenance

### Monthly Check
- Read 3 recent pieces aloud
- Do they still sound like you?
 Update this guide if voice has evolved


 Gather new strong samples
 Re-run analysis
 Compare to this guide
 Update patterns that have changed



Use these to validate the guide works:


"Using my voice profile, write a 3-sentence response to [common scenario in your field]"


"Using my voice profile, write the opening 2 paragraphs for a piece about [topic you know well]"


"Using my voice profile, write about [topic outside your usual content]"

Compare outputs to your natural writing. If they feel off, update the guide.

</output_format>

<analysis_process> Read all samples without analyzing. Get a feel for the overall voice impression. Note your gut reaction: what makes this writing distinctive?

Go through each dimension in the analysis framework. Pull specific examples from the samples. Look for patterns that appear across multiple samples (not one-offs). Compare to generic AI output patterns. What does this writer do that AI typically doesn't? What AI patterns are absent from these samples? Based on the contrast analysis, identify phrases and patterns that would destroy this voice. These become the "never use" list. Compile findings into the VOICE.md format. Include specific examples from the samples to illustrate each pattern. Generate 3 test prompts tailored to this person's typical writing contexts. These will be used to verify the guide works. **Sample characteristics:** Newsletter writer, explains complex topics simply, uses humor and personal anecdotes

Key findings:

• Sentences vary wildly (5-40 words)
• Heavy use of "Here's the thing" and "The reality is"
• Self-deprecating humor about own mistakes
• One-sentence paragraphs for emphasis
• Direct address to reader ("you")
• Specific numbers and timeframes ("three hours later, no hyperbole")

Forbidden list generated:

• "It's worth noting that"
• "In today's digital landscape"
• "Leverage" as a verb
• Paired adjectives ("comprehensive and thorough")
• Any sentence starting with "Furthermore" or "Moreover"

**Sample characteristics:** Engineering blog, detailed explanations, code examples, dry humor

Key findings:

• Longer sentences with technical precision
• Code-switches between casual and technical
• Humor through understatement
• Heavy use of concrete examples
• "Actually" and "technically" as qualifiers
• Lists for technical content, prose for opinions

Forbidden list generated:

• Vague claims without specifics
• Marketing superlatives ("revolutionary," "game-changing")
• Excessive hedging ("it might be argued")
• Emoji in technical sections
• "Simply" before complex explanations

<integration_notes> Where to save VOICE.md:

• Project-specific: resources/VOICE.md (for this project only)
• User-wide: resources/voice/VOICE.md (for all projects)
• Multiple profiles: resources/voice/[context]-voice.md (professional, casual, technical)

Using with other skills:

• slop-detector will reference VOICE.md for personalized pattern detection
• voice-editor uses VOICE.md to guide rewrites
• Include path to VOICE.md in project's CLAUDE.md for automatic loading

Maintenance schedule:

• Monthly: Quick read-aloud check (15 min)
• Quarterly: Full refresh with new samples (1 hour)
• After major voice shifts: Complete re-analysis </integration_notes>

<success_criteria> The voice analysis is complete when:

• All provided samples have been analyzed
• Each dimension in the analysis framework has findings
• VOICE.md file is generated with all sections
• Forbidden list contains at least 10 specific items
• 3 validation prompts are tailored to the user's context
• User has been shown where to save the file
• Testing process has been explained

Quality check: The generated guide should allow someone unfamiliar with the writer to produce content that readers would recognize as authentic. </success_criteria>

<core_principle> You're not trying to achieve perfection on attempt one. You're building infrastructure that improves with use. The first guide will be good but not perfect -- that's normal. Each piece written with this guide makes it more precise.

Voice doesn't live in first drafts. It lives in editing choices. The guide gives AI direction; your editing gives the work your actual voice. </core_principle>