Applies a voice profile to transform content. Use when user asks to write in a specific voice, match a tone, apply a style, or transform content to sound like a particular voice profile.
/plugin marketplace add jmagly/ai-writing-guide/plugin install jmagly-voice-plugins-voice@jmagly/ai-writing-guideThis skill inherits all available tools. When active, it can use any tool Claude has access to.
references/voice-dimensions.mdscripts/voice_loader.pyTransform 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.
| Natural Language | Action |
|---|---|
| "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 |
Skill checks these locations (in order):
.aiwg/voices/~/.config/aiwg/voices/voice-framework/voices/templates/| Profile | Description | Best For |
|---|---|---|
technical-authority | Direct, precise, confident | Docs, architecture, engineering |
friendly-explainer | Approachable, encouraging | Tutorials, onboarding, education |
executive-brief | Concise, outcome-focused | Business cases, stakeholder comms |
casual-conversational | Relaxed, personal | Blog posts, social, newsletters |
# Load from YAML
profile = load_voice_profile("technical-authority")
Tone Calibration:
Vocabulary Transformation:
prefer/avoid guidanceStructure Adjustment:
Perspective Shift:
Ensure output includes profile's authenticity characteristics:
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
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..."
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
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
Load and validate voice profiles:
python scripts/voice_loader.py --profile technical-authority
Analyze content against voice profile:
python scripts/voice_analyzer.py --content input.md --profile technical-authority
Works with:
/voice-apply command for explicit invocation/voice-create command for generating new profilesWhen reporting voice application:
Voice Applied: technical-authority
Transformations:
- Formality: 0.4 → 0.7 (increased)
- Confidence: 0.5 → 0.9 (increased)
- Vocabulary: 12 replacements
- Structure: Added 2 examples, removed 1 rhetorical question
Authenticity Check:
✓ Acknowledges tradeoffs
✓ Uses specific numbers
✓ References constraints
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