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Agent skill

Voice Analyzer

by flonat in flonat/flonat-research

Analyze representative writing samples into a portable personal voice profile and style guide.

MITAuto-check passedWriting & Content

Install Voice Analyzer

skills CLI
$ npx skills add flonat/flonat-research --skill voice-analyzer -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install flonat/flonat-research voice-analyzer --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/flonat/flonat-research.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/voice-analyzer .claude/skills/voice-analyzer && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
voice-analyzer
GitHub stars
146
Token cost
~2.3k tokens
SKILL.md length
860 words
Files
1
Skills in repo
83
Repo updated
First seen
Licence
MIT

At a glance

Analyze representative writing samples into a portable personal voice profile and style guide.

  • Works in 12 steps: Sentence Patterns → Vocabulary Fingerprint → Rhythm and Flow → …
  • Establishing voice-matched editing for a new project
  • SKILL.md covers Quick Start, Sample Gathering Guidance, Analysis Framework and Output Format, plus 5 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Voice Analyzer is an agent skill from flonat/flonat-research. 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 Use when establishing voice-matched editing for a new project or refreshing an outdated profile.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.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Writing & Content, covering Brand voice and tone. The repository describes itself as: Shareable Claude Code + Codex infrastructure for PhD researchers — skills, agents, hooks, and rules for academic workflows. The licence is MIT.

When your agent uses it

  • Establishing voice-matched editing for a new project
  • Refreshing an outdated profile

Example prompts

  • “/voice-analyzer”

Requirements

  • Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, AskUserQuestion

Workflow steps

12 steps, taken from the step headings in SKILL.md.

  1. Sentence Patterns
  2. Vocabulary Fingerprint
  3. Rhythm and Flow
  4. Tone Markers
  5. Structural Habits
  6. Opinion Expression
  7. Initial Read
  8. Pattern Extraction
  9. Contrast Analysis
  10. Forbidden List Generation
  11. Guide Assembly
  12. Validation Prompts

What it can do on your machine

Read from SKILL.md and the folder at commit da27600. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Read
    • Write
    • Edit
    • Glob
    • Grep
    • AskUserQuestion

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md (its code samples are markdown).

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Voice Analyzer loads about 2.3k tokens when it runs. Until then it costs about 68 tokens; SKILL.md has 860 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~68
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from flonat/flonat-research at commit da27600, republished under its MIT licence (© flonat). 860 words, ~2,299 tokens.

Download SKILL.mdSave it as .claude/skills/voice-analyzer/SKILL.md (or your agent's skills folder).
name
voice-analyzer
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.
allowed-tools
Read, Write, Edit, Glob, Grep, AskUserQuestion
version
1.0.0
user-invocable
true

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
Show full SKILL.md (343 more words)Show less

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: <project>/.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.

© flonat, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in skills/voice-analyzer of flonat/flonat-research.

Open the folder on GitHubat commit da27600

Compare with similar skills

Voice Analyzer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Voice Analyzer compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Voice Analyzer this skillflonat/flonat-research146—~2.3kAutomated safety check: PassMIT
Avoid AI Writingconorbronsdon/avoid-ai-writing4.9k3 repos~8.1kAutomated safety check: PassMIT
BrandOhh-889/skyroc79513 repos~733Automated safety check: PassMIT
Khazix WeChat Article WriterKKKKhazix/khazix-skills21k1 repos~2.9kAutomated safety check: PassMIT
Writing Guidelinesvercel-labs/agent-skills32k7 repos~309Automated safety check: PassNone
Unslop AI Writing Cleanuptheclaymethod/unslop516—~1.7kAutomated safety check: PassMIT

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Categories

Questions about Voice Analyzer

What does Voice Analyzer do?

Analyze representative writing samples into a portable personal voice profile and style guide. Voice Analyzer is an agent skill from flonat/flonat-research. Analyze representative writing samples into a portable personal voice profile and style guide.

When should I use Voice Analyzer?

Voice Analyzer fits situations like: establishing voice-matched editing for a new project; refreshing an outdated profile.

How do I install Voice Analyzer in Claude Code?

Run `npx skills add flonat/flonat-research --skill voice-analyzer -a claude-code`. Or copy the skill folder (skills/voice-analyzer in flonat/flonat-research) into .claude/skills/voice-analyzer in your project. Claude Code loads it when a task matches its description.

How do I install Voice Analyzer in Codex?

Run `npx skills add flonat/flonat-research --skill voice-analyzer -a codex`. Or copy the skill folder (skills/voice-analyzer in flonat/flonat-research) into .agents/skills/voice-analyzer in your project. Codex loads it when a task matches its description.

Can I use Voice Analyzer in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add flonat/flonat-research --skill voice-analyzer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/voice-analyzer, .gemini/skills/voice-analyzer, .github/skills/voice-analyzer and .opencode/skills/voice-analyzer in your project.

What does Voice Analyzer need to run?

SKILL.md names no scripts, command-line tools or credentials: Voice Analyzer is instructions for the agent only. Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, AskUserQuestion.

Does Voice Analyzer access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Voice Analyzer safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Voice Analyzer use?

Voice Analyzer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Voice Analyzer use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Voice Analyzer?

Skills that share tags, products or a category with Voice Analyzer: Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), Brand (Ohh-889/skyroc, 795 stars), Khazix WeChat Article Writer (KKKKhazix/khazix-skills, 21k stars) and Writing Guidelines (vercel-labs/agent-skills, 32k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Voice Analyzer?

flonat (a GitHub user) maintains it in flonat/flonat-research, which has 146 GitHub stars. The repository holds 83 skills in this directory. The repository was last updated on September 29, 2026.

Source: flonat/flonat-research on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.