Aiwg voice-create
Generate custom voice profiles from natural language descriptions by mapping tone, formality, and domain to voice dimensions
install
source · Clone the upstream repo
git clone https://github.com/jmagly/aiwg
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/jmagly/aiwg "$T" && mkdir -p ~/.claude/skills && cp -r "$T/agentic/code/addons/voice-framework/skills/voice-create" ~/.claude/skills/jmagly-aiwg-voice-create-fee943 && rm -rf "$T"
manifest:
agentic/code/addons/voice-framework/skills/voice-create/SKILL.mdsource content
voice-create
Generate custom voice profiles from natural language descriptions.
Triggers
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
- "make me sound like [reference]" → reference-based voice creation
- "voice fingerprint" → voice profile extraction from text
Behavior
When triggered, this skill:
-
Parses the description to identify:
- Target audience (developers, executives, general public)
- Tone characteristics (formal/casual, confident/tentative, warm/clinical)
- Domain context (technical, marketing, academic, conversational)
- Any specific constraints or preferences mentioned
-
Maps description to voice dimensions:
- Formality (0-1): casual ↔ formal
- Confidence (0-1): hedging ↔ assertive
- Warmth (0-1): clinical ↔ friendly
- Energy (0-1): calm ↔ enthusiastic
- Complexity (0-1): simple ↔ sophisticated
-
Generates vocabulary guidance:
- Preferred terms based on domain
- Terms to avoid based on tone
- Signature phrases that match the voice
-
Creates structure patterns:
- Sentence length preferences
- Paragraph structure
- Use of lists, examples, analogies
-
Outputs valid YAML conforming to voice-profile.schema.json
Usage Examples
Technical Documentation Voice
User: "Create a voice for API documentation - precise, no-nonsense, assumes developer knowledge" Output: technical-api-docs.yaml - formality: 0.6 - confidence: 0.9 - warmth: 0.2 - energy: 0.3 - complexity: 0.8 - vocabulary: technical terms, code references, precise metrics
Friendly Tutorial Voice
User: "Make me a voice for beginner tutorials - encouraging, patient, uses lots of analogies" Output: beginner-tutorial.yaml - formality: 0.2 - confidence: 0.7 - warmth: 0.9 - energy: 0.7 - complexity: 0.3 - vocabulary: everyday language, encouraging phrases, analogies
Executive Summary Voice
User: "Generate a voice profile for board presentations - authoritative but accessible" Output: board-presentation.yaml - formality: 0.8 - confidence: 0.9 - warmth: 0.4 - energy: 0.5 - complexity: 0.6 - vocabulary: business metrics, strategic language, clear conclusions
Output Location
Generated profiles are saved to:
(project-specific, default).aiwg/voices/{name}.yaml
(user-wide, with --global flag)~/.config/aiwg/voices/{name}.yaml
Voice Generation Process
Step 1: Dimension Calibration
Parse natural language for dimension indicators:
| Description Keywords | Dimension | Value Range |
|---|---|---|
| casual, relaxed, conversational | formality | 0.1-0.3 |
| professional, business | formality | 0.5-0.7 |
| formal, academic, official | formality | 0.8-1.0 |
| tentative, careful, hedging | confidence | 0.2-0.4 |
| balanced, measured | confidence | 0.5-0.7 |
| assertive, authoritative, direct | confidence | 0.8-1.0 |
| clinical, detached, objective | warmth | 0.1-0.3 |
| neutral, professional | warmth | 0.4-0.6 |
| friendly, warm, personable | warmth | 0.7-0.9 |
| calm, measured, understated | energy | 0.1-0.3 |
| balanced, engaged | energy | 0.4-0.6 |
| enthusiastic, dynamic, energetic | energy | 0.7-0.9 |
| simple, accessible, plain | complexity | 0.1-0.3 |
| clear, moderate | complexity | 0.4-0.6 |
| sophisticated, detailed, nuanced | complexity | 0.7-0.9 |
Step 2: Domain Detection
Identify domain from context:
- Technical: API, code, system, architecture, implementation
- Marketing: brand, campaign, audience, engagement, conversion
- Academic: research, methodology, analysis, findings, literature
- Executive: strategy, ROI, stakeholder, decision, outcome
- Support: help, issue, solution, troubleshoot, resolve
Step 3: Vocabulary Generation
Based on domain and tone, generate:
- 5-10 preferred terms
- 3-5 terms to avoid
- 2-4 signature phrases
Step 4: Structure Selection
Map tone to structure patterns:
- High formality → longer sentences, structured paragraphs
- Low formality → shorter sentences, varied structure
- High confidence → direct statements, conclusions first
- High warmth → questions, inclusive language ("we", "let's")
Integration
Works with other voice-framework skills:
- Created voices can be applied via
voice-apply - Created voices can be inputs to
voice-blend
can create base profiles thatvoice-analyze
refinesvoice-create
References
- Schema:
../../../schemas/voice-profile.schema.json - Dimensions guide:
../voice-apply/references/voice-dimensions.md - Built-in templates:
../../voices/templates/