--- name: voice-analyzer version: 1.0.0 description: "Analyze representative writing samples into a portable personal voice profile and style guide. Use when establishing voice-matched editing for a new project or refreshing an outdated profile. Not for a target journal's editorial style; use $journal-voice." user-invocable: true allowed-tools: - Read - Write - Edit - Glob - Grep - AskUserQuestion --- # Voice Analyzer: Create a Voice Profile from Writing Samples 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:** Published papers, proposals, emails you're proud of, blog posts, referee responses, teaching materials **Avoid:** Heavily edited collaborative pieces, boilerplate text, anything that felt forced --- ## 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 ### Minimum Requirements - **Minimum:** 3 samples, 500+ words each - **Ideal:** 5-7 samples, 1000+ words each - **Advanced:** 10+ samples including different formats (email, long-form, paper sections) More samples = more accurate pattern detection, but diminishing returns after 10. ### Academic Sample Sources If you're building an academic voice profile: - **Paper drafts** — introduction and discussion sections show the most voice - **Referee responses** — often reveal how you argue and handle criticism - **Proposals and abstracts** — show how you frame contributions - **Teaching materials** — lecture notes, assignment descriptions - **Emails to collaborators** — longer substantive emails, not one-liners - **Blog posts or public writing** — if you have any **Avoid for academic profiles:** - Methods sections (too formulaic to show voice) - Literature review sections (mostly paraphrasing others) - Co-authored sections where your voice was diluted --- ## Analysis Framework When analyzing samples, examine these six dimensions: ### 1. Sentence Patterns - 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 ### 2. Vocabulary Fingerprint - Formality level (casual/conversational vs. professional/technical) - Jargon usage (field-specific terms, insider language) - Characteristic phrases you repeat - Filler words ("actually", "basically", "honestly") - Intensifiers you favor ("really", "quite", "particularly") - Academic-specific: hedging vocabulary, contribution framing ### 3. Rhythm and Flow - 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 ### 4. Tone Markers - Humor style (dry, self-deprecating, none) - Level of directness - How you handle uncertainty (hedge vs. commit) - Personal disclosure level - Relationship with reader (peer, teacher, mentor, collaborator) ### 5. Structural Habits - 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, parentheticals) ### 6. Opinion Expression - How strongly you state opinions - How you qualify claims - Use of "I" vs. "we" vs. "you" vs. passive - How you handle disagreement or controversy - Confidence level in assertions --- ## Output Format Generate a VOICE.md file with this structure: ```markdown # 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] ## Academic Mode Notes [If academic samples were analyzed] - Paper voice vs. email voice differences - Hedging conventions to preserve - Contribution framing patterns - How formality shifts by audience (journal vs. collaborator vs. student) ## 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. ``` --- ## Analysis Process ### Step 1: 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 2: 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 3: 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 4: Forbidden List Generation Based on the contrast analysis, identify phrases and patterns that would destroy this voice. These become the "never use" list. ### Step 5: Guide Assembly Compile findings into the VOICE.md format. Include specific examples from the samples to illustrate each pattern. ### Step 6: Validation Prompts Generate 3 test prompts tailored to this person's typical writing contexts. These will be used to verify the guide works. --- ## Where to Save VOICE.md - **Default:** `.context/voice/voice.md` (follows the `.context/` pattern) - **Project-specific:** `/.context/voice/voice.md` (for project-specific voice) - **Multiple profiles:** `.context/voice/[context]-voice.md` (academic, casual, teaching) Add a pointer in the project's CLAUDE.md so it auto-loads: ```markdown ## Voice Profile See [`.context/voice/voice.md`](.context/voice/voice.md) ``` --- ## Integration - `voice-editor` uses VOICE.md to guide rewrites --- ## 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. --- ## 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.