muapi-photo-pack-generator

Name: muapi-photo-pack-generator
Author: samuraigpt

Generate a pack of professional or aesthetic photos from a single reference image while preserving the exact identity of the person.

INSTALLATION

npx skills add https://github.com/samuraigpt/generative-media-skills --skill muapi-photo-pack-generator

Run in your project or agent environment. Adjust flags if your CLI version differs.

SKILL.md

📸 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

uploaded file

Step 2 — Vision Analysis

Extract scene attributes only.

DO NOT describe:

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

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