voice-analysis▌
jwynia/agent-skills · updated Apr 26, 2026
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Extract and document a writer's distinctive voice patterns for consistent reproduction. Creates a "voice guide" that enables authentic writing that sounds like the source, not a generic approximation.
Voice & Tone Analysis
Purpose
Extract and document a writer's distinctive voice patterns for consistent reproduction. Creates a "voice guide" that enables authentic writing that sounds like the source, not a generic approximation.
Core Principle
Capture spirit, not just mechanics. The goal is writing that makes the source say "yes, that's me" not "I guess that's accurate."
Phase 1: Sample Collection
Gather 5-10 Examples from Each Category
Peak Voice - Writing they identify as "most them"
Off-Voice - Writing that doesn't represent them well
Different Contexts:
- Technical/instructional content
- Persuasive/argumentative pieces
- Narrative/storytelling
- Casual communication (emails, messages)
- Formal communication
- Emotional/vulnerable content
Self-Report Prompts
Rewrite Exercise: Ask: "Rewrite this neutral paragraph in your voice:"
"The new policy will be implemented next month. It includes several changes to current procedures. Employees should review documentation and submit questions by the deadline."
Rule Breaking: "What writing 'rules' do you consistently ignore? Why?"
Pet Peeves: "What writing choices immediately signal something wasn't written by you?"
Evolution: "How has your writing changed in 5 years? What stayed constant?"
Phase 2: Linguistic Analysis
Sentence Level
| Pattern | What to Track |
|---|---|
| Average length | Words per sentence |
| Range | Shortest to longest |
| Fragments | Usage frequency, contexts |
| Run-ons | Tendency, intentionality |
| Opening patterns | How sentences typically start |
| Closing patterns | How sentences typically end |
Paragraph Architecture
| Element | What to Track |
|---|---|
| Average length | Sentences per paragraph |
| Topic sentences | Beginning, middle, end, absent |
| Transitions | Explicit words, implicit flow, abrupt |
| Information order | Build-up, front-load, circular |
Punctuation Signature
| Mark | Track Usage Pattern |
|---|---|
| Em dash | Interruption, emphasis, list, asides |
| Parentheses | Frequency, content type |
| Semicolon | Presence, absence, alternative |
| Ellipsis | Trailing, pause, omission |
| Exclamation | Frequency, contexts |
| Rhetorical questions | Frequency, function |
Phase 3: Lexical Fingerprinting
Word Choice Matrix
| Category | Preferred | Avoided | Signature Examples |
|---|---|---|---|
| Technical terms | |||
| Colloquialisms | |||
| Intensifiers | very, extremely, quite... | ||
| Hedging | perhaps, might, seems... | ||
| Abstract/concrete |
Register Analysis
- Consistent register (formal/informal throughout)
- Deliberate register mixing (formal content, casual asides)
- Context-dependent shifting (formal for X, casual for Y)
Recurring Constructions
List phrases/patterns appearing 3+ times:
Phase 4: Conceptual DNA
Metaphor Mapping
| Source Domain | Target Domain | Example | Frequency |
|---|---|---|---|
| (war, journey, building...) | (ideas, processes...) |
Reference Pool
- Cultural touchstones: (movies, books, memes, history...)
- Time period: (contemporary, 90s, classic...)
- Accessibility level: (mainstream, niche, insider)
- Domains drawn from: (sports, cooking, science...)
Reasoning Patterns
Rate 1-5 for prevalence:
- Analogical reasoning (like X, therefore Y)
- First principles (from basics up)
- Empirical evidence (data, studies)
- Personal anecdote (I experienced...)
- Hypotheticals (imagine if...)
- Socratic questioning (but what if...?)
Phase 5: Emotional Texture
Enthusiasm Spectrum
| Low | Medium | High |
|---|---|---|
| (understated) | (balanced) | (expressive) |
Criticism Styles
| Style | When Used | Markers |
|---|---|---|
| Direct | "This is wrong because..." | |
| Diplomatic | "One consideration might be..." | |
| Humorous | "Well, that's one way to..." | |
| Analytical | "The issue breaks down to..." |
Vulnerability Patterns
- Admission phrases: "I'll admit...", "honestly..."
- Uncertainty markers: "I think...", "not sure but..."
- Personal revelation style: Direct? Buried in humor? Rare?
Phase 6: Reader Dynamics
Positioning
The writer positions as:
- Expert/teacher (I know, let me explain)
- Peer/collaborator (we're figuring this out together)
- Student/learner (I'm working through this)
- Challenger/provocateur (conventional wisdom is wrong)
- Guide/facilitator (here's how to navigate)
Assumed Context
- Shared knowledge level: Assumes expertise? Explains basics?
- Cultural assumptions: In-group references? Universal?
- Relationship warmth: Distant professional? Familiar?
Interactive Patterns
- Questions per 1000 words: ___
- Direct address frequency ("you"): ___
- Imperative usage (commands): ___
- Inclusive language ("we/us"): ___
Phase 7: Voice Guide Synthesis
Core Voice Statement
In 2-3 sentences, capture the essence:
The Rules That Matter Most
Always:
Never:
Usually, unless:
Sentence Construction Guide
- Preferred length:
- Variety pattern:
- Opening moves:
- Power positions: (where key info lands)
Word Selection Principles
- Go-to words for [concept]:
- Banned words/phrases:
- Register rules:
Structural Signatures
- Paragraph rhythm:
- Transition style:
- Information architecture:
Emotional Register
- Default tone:
- Excitement expression:
- Criticism approach:
- Vulnerability threshold:
The Litmus Test
A piece captures this voice when: 1. 2. 3.
Red Flags
Definitely NOT this voice when: 1. 2. 3.
Phase 8: Validation
Before finalizing the voice guide:
- Can identify the author in a blind test?
- Guided writing feels authentic, not performative?
- Patterns are descriptive, not prescriptive?
- Captures spirit, not just mechanics?
- Source would say "yes, that's me"?
Quick Reference Template
In Every Piece
The Heart of the Voice
[Single paragraph essence]
Emergency Voice Recovery
When writing has gone generic, add: 1. 2. 3.
Usage Notes
For AI Writing
Once the voice guide is complete, include relevant sections in the prompt to guide generation toward authentic voice reproduction.
For Self-Analysis
Writers can use this framework to understand their own voice, identify what makes their writing distinctive, and consciously apply those patterns.
For Editing
Use the voice guide as a checklist when editing to ensure consistency and authenticity.
Anti-Patterns
1. Mechanics Over Spirit
Pattern: Cataloging every linguistic feature without understanding what makes the voice feel distinctive. Why it fails: A perfect inventory of word frequencies and sentence lengths can produce writing that's technically accurate but feels like a parody. Voice is gestalt, not components. Fix: Start from "what makes this voice feel like this?" Work backward to mechanics. The inventory serves understanding; understanding doesn't emerge from inventory alone.
2. Single-Context Capture
Pattern: Analyzing voice from one type of writing, then applying it to all contexts. Why it fails: Writers shift voice across contexts. Technical writing voice differs from casual email voice. Capturing one context and forcing it everywhere creates uncanny artifacts. Fix: Sample across contexts. Map how voice shifts. Include context-switching rules in the voice guide. Understand which elements are constant vs. context-dependent.
3. Frequency as Rule
Pattern: If they use em-dashes 8% of the time, the voice guide prescribes 8% em-dash usage. Why it fails: Frequency is a statistical average, not a style rule. Forced frequency creates awkward placement. Natural writers don't count punctuation. Fix: Understand when they use em-dashes, not how often. "Uses em-dashes for dramatic interjections, rarely for lists" is actionable. "8% em-dashes" is not.
4. Imitation Artifacts
Pattern: Voice-guided writing that feels like someone doing an impression—technically accurate but overperformed. Why it fails: Distinctive features become tics when isolated. Real voice balances distinctive and neutral. Guides that catalog only distinctive features produce caricature. Fix: Include neutral baseline alongside distinctive features. Most sentences should sound natural, with distinctive features emerging at appropriate moments, not constantly.
5. Frozen Voice
Pattern: Treating the voice guide as permanent, not updating as the writer evolves. Why it fails: Writers change. A voice guide from 2020 may not fit 2025 writing. Using outdated guides produces writing that feels like an old version of the person. Fix: Note the capture date. Plan periodic updates. Include the writer's own reflections on how their voice has evolved. Treat the guide as living documentation.
Integration
Inbound (feeds into this skill)
| Skill | What it provides |
|---|---|
| (writing samples) | Raw material for analysis |
| prose-style | Sentence-level craft framework for analysis |
Outbound (this skill enables)
| Skill | What this provides |
|---|---|
| prose-style | Voice-specific sentence construction guidance |
| dialogue | Voice patterns for character speech |
| (AI generation) | Voice guides for consistent AI-assisted writing |
Complementary
| Skill | Relationship |
|---|---|
| prose-style | Voice-analysis captures what; prose-style provides how. Use voice-analysis first to understand the target, then prose-style to achieve it |
| dialogue | Voice-analysis for authorial voice; dialogue skill for character voices within fiction |
How to use voice-analysis on Cursor
AI-first code editor with Composer
Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add voice-analysis
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches voice-analysis from GitHub repository jwynia/agent-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate voice-analysis. Access the skill through slash commands (e.g., /voice-analysis) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
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Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★30 reviews- ★★★★★Amelia Mensah· Dec 24, 2024
Useful defaults in voice-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
- ★★★★★Aanya Haddad· Dec 12, 2024
voice-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Chaitanya Patil· Dec 4, 2024
I recommend voice-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Piyush G· Nov 23, 2024
Solid pick for teams standardizing on skills: voice-analysis is focused, and the summary matches what you get after install.
- ★★★★★Aditi Perez· Nov 15, 2024
We added voice-analysis from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Aditi Menon· Nov 3, 2024
Keeps context tight: voice-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Aditi Iyer· Oct 22, 2024
I recommend voice-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Shikha Mishra· Oct 14, 2024
voice-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Harper Garcia· Oct 6, 2024
voice-analysis reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Soo Liu· Sep 13, 2024
voice-analysis is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
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