Generate custom voice profiles from natural language descriptions by mapping tone, formality, and domain to voice dimensions
Scanned 9/3/2026
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---
namespace: aiwg
name: voice-create
platforms: [all]
description: Generate custom voice profiles from natural language descriptions by mapping tone, formality, and domain to voice dimensions
---
# 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:
1. **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
2. **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
3. **Generates vocabulary guidance**:
- Preferred terms based on domain
- Terms to avoid based on tone
- Signature phrases that match the voice
4. **Creates structure patterns**:
- Sentence length preferences
- Paragraph structure
- Use of lists, examples, analogies
5. **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:
1. `.aiwg/voices/{name}.yaml` (project-specific, default)
2. `~/.config/aiwg/voices/{name}.yaml` (user-wide, with --global flag)
## 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`
- `voice-analyze` can create base profiles that `voice-create` refines
## References
- Schema: `../../../schemas/voice-profile.schema.json`
- Dimensions guide: `../voice-apply/references/voice-dimensions.md`
- Built-in templates: `../../voices/templates/`
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