muapi-photo-pack-generator

Q: How do I install muapi-photo-pack-generator?

Run npx skills add https://github.com/samuraigpt/generative-media-skills --skill muapi-photo-pack-generator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/muapi-photo-pack-generator/ (personal) or .claude/skills/muapi-photo-pack-generator/ (project).

by samuraigptMedia & Creative

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

Installs: 967
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Trending rank: —
Security: Not audited

Install

Works with every agent the skills CLI supports.

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

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads muapi-photo-pack-generator automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

SKILL.md

The instructions your agent reads when the skill is triggered.

📸 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

FAQ

What does the muapi-photo-pack-generator skill do?

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

How do I install muapi-photo-pack-generator?

Run npx skills add https://github.com/samuraigpt/generative-media-skills --skill muapi-photo-pack-generator in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/muapi-photo-pack-generator/ (personal) or .claude/skills/muapi-photo-pack-generator/ (project).

Which AI agents can use muapi-photo-pack-generator?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is muapi-photo-pack-generator safe to install?

No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.

Who maintains muapi-photo-pack-generator?

It is published by samuraigpt in samuraigpt/generative-media-skills. It has 967 recorded installs.