사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/samuraigpt/generative-media-skills --skill muapi-photo-pack-generator시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
📸 Photo Pack Generator Expert Skill (Identity-Lock Edition)
Transform a single reference photo into a collection of themed images while maintaining extremely high facial identity fidelity.
This skill prioritizes identity preservation first, then applies stylistic transformations like LinkedIn portraits, dating photos, cinematic shots, or fantasy styles.
The system uses Identity Lock Prompting instead of describing the person, preventing the model from generating a new face.
Core Principles
1️⃣ Identity Lock (MOST IMPORTANT)
The generated images must always depict the same person from the reference image.
All prompts MUST include identity lock instructions.
Required identity rules:
- Preserve the exact facial identity from the reference image
- Do not modify eye shape or spacing
- Do not modify nose structure
- Do not modify jawline or chin shape
- Do not modify cheekbones
- Do not modify face proportions
- Identity must remain identical to the reference photo
2️⃣ Vision-First Scene Analysis
The agent MUST analyze the reference image before generation.
However the analysis must NOT describe the person (age, ethnicity, hair etc).
Allowed analysis fields:
- head orientation
- facial angle
- expression
- lighting direction
- framing (portrait / half body / full body)
Example:
Head orientation: slight left tilt Expression: neutral friendly Lighting: soft frontal light Framing: head and shoulders portrait
Agent Execution Flow
Step 1 — Grounding Check
Ensure the user has provided a reference image.
Supported inputs:
- local image
- URL
- uploaded file
Step 2 — Vision Analysis
Extract scene attributes only.
DO NOT describe:
- age
- ethnicity
- beard
- hair
- body type
Identity must come directly from the image.
Step 3 — Category Selection
If the user does not specify a category suggest:
- Tinder
- OldMoney
Step 4 — Prompt Construction
Use the reference image as the identity source.
Preserve the exact facial identity from the reference image.
Identity must remain identical to the reference photo.
Do not change:
- eye shape
- eye spacing
- nose structure
- jawline
- cheekbones
- face proportions
Maintain similar head orientation as the reference.
Scene example:
Outdoor café portrait Soft natural daylight 35mm portrait lens Shallow depth of field Photorealistic skin texture
Step 5 — Negative Prompt
Always include:
different person altered face changed facial features new identity generic face beautified face plastic skin face distortion
Step 6 — Execution
Example:
bash scripts/generate-pack.sh \ --image "./my_face.jpg" \ --category "LinkedIn" \ --identity-lock true \ --num 5
Supported Categories
| Category | Best For | Aesthetic |
|---|---|---|
| Professional | Studio | |
| CEO | Founders | Office |
| Tinder | Dating | Lifestyle |
| OldMoney | Luxury | Estate |
| Cyberpunk | Fantasy | Neon |
| Fitness | Gym | Athletic |
| Travel | Social | Bali/Paris |
| 90s | Retro | Vintage |
| Holiday | Seasonal | Festive |
Guardrails
Fidelity First
Identity preservation is always more important than style.
Never Re-Describe the Person
Avoid prompts like:
"Indian man in his 20s with short hair"
This causes the model to generate a new face.
Identity must come from the reference image only.
Recommended Models
Best results with:
- nano-banana-edit
Result
This system produces:
- consistent identity
- photorealistic images
- multi-style photo packs
- professional outputs
