voice-create

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Generate custom voice profiles from natural language descriptions by mapping tone, formality, and domain to voice dimensions

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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:

.aiwg/voices/{name}.yaml (project-specific, default)
~/.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/