Agent skill

Voice Apply

by jmagly in jmagly/aiwg

Apply a voice profile to transform content. An agent skill from jmagly/aiwg.

MITAuto-check passedWriting & Content

Install Voice Apply

skills CLI
$ npx skills add jmagly/aiwg --skill voice-apply -a claude-code

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

GitHub CLI
$ gh skill install jmagly/aiwg voice-apply --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/jmagly/aiwg.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agentic/code/plugins/voice/skills/voice-apply .claude/skills/voice-apply && 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-apply
GitHub stars
220
Token cost
~2.3k tokens
SKILL.md length
787 words
Files
3 (incl. scripts, references)
Skills in repo
12
Repo updated
First seen
Licence
MIT

At a glance

Apply a voice profile to transform content. An agent skill from jmagly/aiwg.

  • Works in 4 steps: Load Voice Profile → Analyze Source Content (if transforming) → Apply Voice Characteristics → …
  • The user asks to write in a specific voice
  • SKILL.md covers Local writing and…, Reviewed voice application, Brief and fidelity contract and Purpose, plus 11 more sections
  • Runs Python scripts from its folder; calls python

What it does

Voice Apply is an agent skill from jmagly/aiwg. Apply a voice profile to transform content. Use when the user asks to write in a specific voice, match a tone, or sound like a particular voice profile.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files, including scripts and reference files (for example `references/voice-dimensions.md` and `scripts/voice_loader.py`).

It sits in Writing & Content, covering Brand voice and tone. The repository describes itself as: Cognitive architecture for AI-augmented software development. Specialized agents, structured workflows, and multi-platform deployment. Claude Code · Codex · Copilot · Cursor ·… The licence is MIT.

When your agent uses it

  • The user asks to write in a specific voice
  • Sound like a particular voice profile

Example prompts

  • “/voice-apply”

Requirements

  • Python 3

Workflow steps

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

  1. Load Voice Profile
  2. Analyze Source Content (if transforming)
  3. Apply Voice Characteristics
  4. Verify Authenticity Markers

What it can do on your machine

Read from SKILL.md and the folder at commit dda238f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    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 Apply loads about 2.3k tokens when it runs, and up to ~2.8k if it reads all its reference files. Until then it costs about 41 tokens; SKILL.md has 787 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~41
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.8k

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); the scripts in this folder are not scanned.

SKILL.md

The full file from jmagly/aiwg at commit dda238f, republished under its MIT licence (© jmagly). 787 words, ~2,301 tokens.

Download SKILL.mdSave it as .claude/skills/voice-apply/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
voice-apply
description
Apply a voice profile to transform content. Use when the user asks to write in a specific voice, match a tone, or sound like a particular voice profile.
namespace
aiwg
version
1.0.0
platforms
all
triggers
help write better content, help me make this writing clearer and consistent, choose voice writing validation or marketing flow, apply voice profile

Voice Apply Skill

Local writing and participating consumer recipes

Use author-controlled writing workflows for the actual aiwg writing plan and aiwg writing proofread commands, channel APIs, bounded revision, explicit learning, scoped MCP resources and separate receipts. Planning creates a structured artifact; proofreading applies exact listed author-authorized corrections without a model or voice rewrite. A selected mode is not an applied transformation. Unsupported consumers use explicit instruction exports; never claim every provider response is intercepted. Keep original text and unresolved review decisions recoverable. Publication controls remain with the user's existing workflow.

Reviewed voice application

For model-driven voice transformation, use the packaged criticism/correction flow and output impact guide. The selected development lane uses one Astra draw and at most one correction with the primary session as reviewer. Neutral analytical packets are required; private author provenance stays outside generator and corrector context. Preserve the original unless a hash-bound review accepts both fidelity and cadence. This does not change deterministic proofread-only behavior or qualify all channels.

Brief and fidelity contract

For author-controlled writing, prepare a structured writing brief before generating prose. Record reader task, supported propositions, limitations, intended action and approved author notes. Missing first-person experiences or design rationale are editorial gaps; do not invent them. Keep evidence strength independent of voice. Proofread-only applies selected authorized correction IDs to the original source; other operations expose explicit permissions and lineage for downstream execution.

Run fidelity checks after every final structure/presentation pass. Uncertain paraphrases require review. Preserve the original on configured fallback and report attempted versus retained changes outside product prose. Automated literal guards are not semantic proof.

Purpose

Transform content to match a specified voice profile. This skill loads voice profiles and applies their characteristics (tone, vocabulary, structure, perspective) to new or existing content.

Evidence constraints are recorded in the natural voice ownership ADR and versioned ledger. Treat phrase highlights as contextual editorial suggestions, never authorship probabilities. Preserve supplied facts, uncertainty and author intent; an assertive tone does not strengthen evidence. Author notes were already part of the cited post-editing study. Neither topic-matched examples nor a fixed example count is established as a universally best choice. The ledger is an evidence contract, not a claim that the planned natural voice pipeline has been qualified.

When This Skill Applies

  • User asks to "write in X voice" or "use Y tone"
  • User wants to "make this sound more [casual/formal/technical/etc.]"
  • User provides content and asks to transform its style
  • User references a voice profile by name
  • User wants content to match a specific audience or context

Trigger Phrases

Natural LanguageAction
"Write this in technical voice"Apply technical-authority profile
"Make it more casual"Apply casual-conversational or calibrate toward casual
"This needs to sound executive"Apply executive-brief profile
"Explain like I'm a beginner"Apply friendly-explainer profile
"Use the [profile-name] voice"Load and apply named profile
"Transform this to match [example]"Analyze example, apply derived voice
Show full SKILL.md (311 more words)Show less

Voice Profile Locations

Skill checks these locations (in order):

  1. Project: .aiwg/voices/
  2. User: ~/.config/aiwg/voices/
  3. Built-in: voice-framework/voices/templates/

Built-in Voice Profiles

ProfileDescriptionBest For
technical-authorityDirect, precise, confidentDocs, architecture, engineering
friendly-explainerApproachable, encouragingTutorials, onboarding, education
executive-briefConcise, outcome-focusedBusiness cases, stakeholder comms
casual-conversationalRelaxed, personalBlog posts, social, newsletters

Application Process

1. Load Voice Profile
python
# Load from YAML
profile = load_voice_profile("technical-authority")
2. Analyze Source Content (if transforming)
  • Current tone characteristics
  • Vocabulary patterns
  • Structure patterns
  • Gap analysis vs target voice
3. Apply Voice Characteristics

Tone Calibration:

  • Adjust formality level (word choice, contractions)
  • Preserve evidence strength and all required hedging; adjust expression only
  • Set warmth (clinical vs personable)
  • Tune energy (measured vs enthusiastic)

Vocabulary Transformation:

  • Replace words per prefer/avoid guidance
  • Introduce domain terminology naturally
  • Use characteristic phrasing only where natural and supported; never insert signatures mechanically

Structure Adjustment:

  • Modify sentence length distribution
  • Adjust paragraph breaks
  • Reorganize supported material within edit permissions; do not invent examples or analogies that add claims

Perspective Shift:

  • Adjust narrative person (I, we, you, they)
  • Preserve supported opinions and attribution; do not invent a viewpoint
  • Set reader relationship tone
4. Verify Authenticity Markers

Check these properties only when supported by the source; never invent them to satisfy a profile:

  • Acknowledges uncertainty (if specified)
  • Shows tradeoffs (if specified)
  • Uses specific numbers (if specified)
  • References constraints (if specified)

Usage Examples

Apply Named Voice
User: "Write release notes in technical-authority voice"

Process:
1. Load technical-authority.yaml
2. Generate release notes with:
   - Precise technical terminology
   - Specific version numbers
   - Direct, confident statements
   - Tradeoff acknowledgments where relevant
Transform Existing Content
User: "Make this documentation more friendly for beginners"

Input: "The API endpoint accepts a JSON payload containing the requisite parameters..."

Process:
1. Load friendly-explainer.yaml
2. Analyze: formal, technical, passive
3. Transform to: casual, accessible, active

Output: "To use this endpoint, send it some JSON with the info it needs..."
Calibrate Voice
User: "This is too formal, dial it back 30%"

Process:
1. Identify current formality (~0.8)
2. Calculate target (0.8 - 0.3 = 0.5)
3. Adjust vocabulary and structure for medium formality

Voice Blending

Combine multiple profiles:

User: "Write this with 70% technical-authority and 30% friendly-explainer"

Process:
1. Load both profiles
2. Weighted merge:
   - tone.formality: 0.7 * 0.7 + 0.3 * 0.3 = 0.58
   - tone.warmth: 0.7 * 0.3 + 0.3 * 0.8 = 0.45
   - etc.
3. Apply merged profile

Script Reference

voice_loader.py

Load and validate voice profiles:

bash
python scripts/voice_loader.py --profile technical-authority
voice_analyzer.py

Analyze content against voice profile:

bash
python scripts/voice_analyzer.py --content input.md --profile technical-authority

Integration

Works with:

  • /voice-apply command for explicit invocation
  • /voice-create command for generating new profiles
  • SDLC templates (apply appropriate voice per artifact type)
  • Marketing templates (brand voice consistency)

Output Format

When reporting voice application:

Voice Applied: technical-authority

Transformations:
- Formality: 0.4 → 0.7 (increased)
- Evidence strength: unchanged; original qualifications retained
- Vocabulary: 12 replacements
- Structure: reordered supported clauses within approved edit scope

Authenticity Check:
✓ Acknowledges tradeoffs
✓ Uses specific numbers
✓ References constraints

References

  • @$AIWG_ROOT/agentic/code/addons/voice-framework/README.md — Voice framework addon overview and profile documentation
  • @$AIWG_ROOT/agentic/code/addons/voice-framework/voices/templates/ — Built-in voice profile templates
  • @$AIWG_ROOT/agentic/code/addons/writing-quality/README.md — Writing quality addon for authenticity enforcement
  • @$AIWG_ROOT/docs/cli-reference.md — CLI reference for voice commands
  • @$AIWG_ROOT/agentic/code/addons/aiwg-utils/rules/instruction-comprehension.md — Parsing voice and style directives accurately

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

Files

SKILL.md and 2 other files (scripts, references) in agentic/code/plugins/voice/skills/voice-apply of jmagly/aiwg.

  • SKILL.md
  • references/voice-dimensions.md
  • scripts/voice_loader.py

Open the folder on GitHubat commit dda238f

Compare with similar skills

Voice Apply 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 Apply compared with similar skills
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Voice Apply this skilljmagly/aiwg220—~2.3kAutomated safety check: PassMIT
Avoid AI Writingconorbronsdon/avoid-ai-writing4.9k3 repos~8.1kAutomated safety check: PassMIT
Khazix WeChat Article WriterKKKKhazix/khazix-skills21k2 repos~2.9kAutomated safety check: PassMIT
BrandOhh-889/skyroc79513 repos~733Automated safety check: PassMIT
Writing Guidelinesvercel-labs/agent-skills32k7 repos~309Automated safety check: PassNone
Unslop AI Writing Cleanuptheclaymethod/unslop512—~1.7kAutomated safety check: PassMIT

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Questions about Voice Apply

What does Voice Apply do?

Apply a voice profile to transform content. An agent skill from jmagly/aiwg. Voice Apply is an agent skill from jmagly/aiwg. Apply a voice profile to transform content.

When should I use Voice Apply?

Voice Apply fits situations like: the user asks to write in a specific voice; sound like a particular voice profile.

How do I install Voice Apply in Claude Code?

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

How do I install Voice Apply in Codex?

Run `npx skills add jmagly/aiwg --skill voice-apply -a codex`. Or copy the skill folder (agentic/code/plugins/voice/skills/voice-apply in jmagly/aiwg) into .agents/skills/voice-apply in your project. Codex loads it when a task matches its description.

Can I use Voice Apply 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 jmagly/aiwg --skill voice-apply -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-apply, .gemini/skills/voice-apply, .github/skills/voice-apply and .opencode/skills/voice-apply in your project.

What does Voice Apply need to run?

Going by SKILL.md and its folder, Voice Apply needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Voice Apply 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 Apply 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. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Voice Apply use?

Voice Apply 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 Apply 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. Its references folder adds about 497 tokens, read only when the agent opens those files.

What are the alternatives to Voice Apply?

Skills that share tags, products or a category with Voice Apply: Avoid AI Writing (conorbronsdon/avoid-ai-writing, 4.9k stars), Khazix WeChat Article Writer (KKKKhazix/khazix-skills, 21k stars), Brand (Ohh-889/skyroc, 795 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 Apply?

jmagly (a GitHub user) maintains it in jmagly/aiwg, which has 220 GitHub stars. The repository holds 12 skills in this directory. The repository was last updated on October 5, 2026.

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