create-voice
SolidCreate voice profiles from writing samples.
Install
Quality Score: 93/100
Skill Content
Details
- Author
- notque
- Repository
- notque/vexjoy-agent
- Created
- 2 months ago
- Last Updated
- today
- Language
- Python
- License
- MIT
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voice-reference
Stores a static voice profile and 2-3 past writing samples so long-form-writing, case-study, column-editorial, thought-leadership, interview-storytelling, and ai-slop-reviewer can measure tone consistency and detect drift. Provides NNGroup 4-dimension voice calibration plus brand-voice axes. Use when user asks about voice profile, tone calibration, brand voice, voice reference, writing sample anchor, 보이스 프로필, 톤 캘리브레이션, 문체 기준, 브랜드 보이스, or 글 샘플 앵커.
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Unified voice content generation pipeline with mandatory validation and joy-check. 13-phase pipeline: LOAD, GROUND, STATS-CHECKPOINT, GENERATE, HOOK-GATE, VALIDATE, REFINE, VARIETY-GATE, JOY-CHECK, ANTI-AI, CLOSE-GATE, OUTPUT, CLEANUP. Use when writing articles, blog posts, or any content that uses a voice profile. Use for "write article", "blog post", "write in voice", "generate content", "draft article", "write about".
voice-extractor
Extract and document someone's authentic writing voice from samples. Use when someone needs a "voice guide," wants to capture their writing DNA, or needs to train AI to write in their style. Also useful for ghostwriting, brand voice documentation, or onboarding writers.
voice-matching
Write extended prose (>~150 words) that reads as the researcher's own writing, not as AI-generated text. Use when producing grant sections, cover letters, addenda, rebuttals, manuscript drafts, lab-website updates, or any output that will be read by a program officer, journal reviewer, or hiring committee as the researcher's first-person work. The voice index (agent/voice_index.py) provides retrievable exemplars of the researcher's published prose ranked by topic similarity; this skill describes how to use them and what patterns to actively avoid.
vocal-direction
Create detailed vocal specifications including style, register, techniques, emotional delivery, and influence references for AI music generation