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- jmagly/aiwg
- 최근 소스 활동
- 2026년 4월 30일 21:57
- 감지된 SKILL.md 언어
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- 스타
- 178
- 포크
- 26
설치 방법
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
소스 파일 검토
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
메뉴
기본적으로 소스를 먼저 확인하는 Prompt가 선택됩니다. 직접 명령으로 전환하거나 로컬 사본을 다운로드할 수도 있습니다.
설치 여부를 결정하기 전에 SKILL.md와 SkillsMP에 표시된 보조 파일을 읽어 보세요.
SOC 직업 분류 기준
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
직접 명령은 검토 Prompt를 거치지 않습니다. 실행하기 전에 소스를 확인하세요.
npx skills add https://github.com/jmagly/aiwg --skill voice-blend명령은 한 줄로 유지됩니다. 복사하기 전에 가로로 스크롤해 전체 내용을 확인하세요.
로컬 사본을 원하시나요? SkillsMP에서 현재 제공할 수 있는 파일을 다운로드하세요.
SKILL.md 표시 중
WCAG accessibility analysis for color palettes including contrast ratios, compliance checking, and remediation suggestions. Use when user needs to verify colors meet accessibility standards.
Generate, analyze, compare, export, and suggest color palettes using color theory. Use when user asks about colors, palettes, color schemes, or needs help choosing colors for a project.
Research current color trends from Pantone, architecture, film, and design. Use when user asks about trending colors, popular palettes, or wants research-backed color inspiration.
| namespace | aiwg |
| name | voice-blend |
| platforms | ["all"] |
| description | Combine multiple voice profiles with weighted mixing to create hybrid voices |
Combine multiple voice profiles with weighted mixing to create hybrid voices.
Alternate expressions and non-obvious activations (primary phrases are matched automatically from the skill description):
When triggered, this skill:
Loads source voice profiles from:
voices/templates/).aiwg/voices/)~/.config/aiwg/voices/)Parses blend specification:
Interpolates dimensions:
Generates hybrid profile with clear lineage tracking
User: "Blend technical-authority and friendly-explainer"
Result: 50/50 blend
- formality: 0.45 (avg of 0.7 and 0.2)
- confidence: 0.8 (avg of 0.9 and 0.7)
- warmth: 0.55 (avg of 0.3 and 0.8)
- vocabulary: merged from both
User: "80% executive-brief, 20% casual-conversational"
Result: Weighted blend
- formality: 0.7 (0.8*0.85 + 0.2*0.15)
- confidence: 0.86 (0.8*0.9 + 0.2*0.6)
- Dominant structure from executive-brief
User: "Combine technical-authority, friendly-explainer, and executive-brief"
Result: Equal thirds (33.3% each)
- All dimensions averaged across three profiles
- Vocabulary merged from all three
For each tone dimension:
blended_value = Σ(weight_i × value_i) / Σ(weight_i)
Structure settings use the dominant voice (highest weight):
name: technical-friendly-blend
version: 1.0.0
description: Blended voice profile
blend_sources:
- name: technical-authority
weight: 0.7
- name: friendly-explainer
weight: 0.3
tone:
formality: 0.55 # interpolated
confidence: 0.84 # interpolated
warmth: 0.45 # interpolated
energy: 0.49 # interpolated
complexity: 0.65 # interpolated
vocabulary:
prefer:
- precise technical terminology # from technical
- concrete examples # from friendly
avoid:
- marketing superlatives # common to both
signature_phrases:
- "The system handles..."
Blended profiles are saved to:
.aiwg/voices/{name}.yaml (default)--output flag~/.config/aiwg/voices/ with --global flagvoice-create or built-in templatesvoice-applyvoice-analyze → voice-blend → voice-apply# Equal blend of two voices
python voice_blender.py --voices "technical-authority,friendly-explainer"
# Weighted blend
python voice_blender.py --voices "technical-authority:0.7,friendly-explainer:0.3"
# Custom output name
python voice_blender.py --voices "..." --name my-hybrid-voice
# Output to specific directory
python voice_blender.py --voices "..." --output .aiwg/voices/
# JSON output for inspection
python voice_blender.py --voices "..." --json
../voice-apply/scripts/voice_loader.py../../../schemas/voice-profile.schema.json../../voices/templates/