Generate a pack of professional or aesthetic photos from a single reference image while preserving the exact identity of the person.
Scanned 5/27/2026
Install via CLI
openskills install SamurAIGPT/Generative-Media-Skills---
name: muapi-photo-pack-generator
version: 0.1.0
description: Generate a pack of professional or aesthetic photos from a single reference image while preserving the exact identity of the person.
---
# 📸 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:
- LinkedIn
- 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 |
|---|---|---|
| LinkedIn | 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
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