aplaceforallmystuff/claude-voice-analyzer/voice-analyzer

<objective> 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. </objective>

<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:

<dimension name="sentence_patterns"> 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

</dimension>

<dimension name="vocabulary_fingerprint"> 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")

</dimension>

<dimension name="rhythm_and_flow"> 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

</dimension>

<dimension name="tone_markers"> 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)

</dimension>

<dimension name="structural_habits"> 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)

</dimension>

<dimension name="opinion_expression"> 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

</dimension> </analysis_framework>

<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
 
### Quarterly Refresh
-Gather new strong samples
-Re-run analysis
-Compare to this guide
-Update patterns that have changed
 
## Testing Prompts
 
Use these to validate the guide works:
 
**Test 1 - Short form:**
"Using my voice profile, write a 3-sentence response to [common scenario in your field]"
 
**Test 2 - Long form:**
"Using my voice profile, write the opening 2 paragraphs for a piece about [topic you know well]"
 
**Test 3 - Edge case:**
"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> <step number="1" name="Initial Read"> Read all samples without analyzing. Get a feel for the overall voice impression. Note your gut reaction: what makes this writing distinctive? </step>

<step number="2" name="Pattern Extraction"> 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). </step>

<step number="3" name="Contrast Analysis"> Compare to generic AI output patterns. What does this writer do that AI typically doesn't? What AI patterns are absent from these samples? </step>

<step number="4" name="Forbidden List Generation"> Based on the contrast analysis, identify phrases and patterns that would destroy this voice. These become the "never use" list. </step>

<step number="5" name="Guide Assembly"> Compile findings into the VOICE.md format. Include specific examples from the samples to illustrate each pattern. </step>

<step number="6" name="Validation Prompts"> Generate 3 test prompts tailored to this person's typical writing contexts. These will be used to verify the guide works. </step> </analysis_process>

<examples> <example name="conversational_expert"> 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"

</example>

<example name="technical_authority"> 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

</example> </examples>

<integration_notes> Where to save VOICE.md:

• Project-specific: ./.claude/VOICE.md (for this project only)
• User-wide: ~/.claude/voice/VOICE.md (for all projects)
• Multiple profiles: ~/.claude/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>