Muapi Photo Pack Generator Agent Skill
Generate a pack of professional or aesthetic photos from a single reference image while preserving the exact identity of the person.
Install
one command, takes just this skill from the repositorynpx skills add https://github.com/SamurAIGPT/Generative-Media-Skills --skill muapi-photo-pack-generatorThe instruction itself
17 sections, as written by the author📸 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 |
|---|---|---|
| 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
Other skills for the same job
different authors, same section of the catalogue
Create beautiful visual art in .png and .pdf documents using design philosophy. You should use this skill when the user asks to create a poster, piece of art, design, or other static piece. Create original visual designs, never copying existing artists' work to avoid copyright violations.
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code, generative art, algorithmic art, flow fields, or particle systems. Create original algorithmic art rather than copying existing artists' work to avoid copyright violations.
Improves the quality of images, especially screenshots, by enhancing resolution, sharpness, and clarity. Perfect for preparing images for presentations, documentation, or social media posts.
Downloads videos from YouTube and other platforms for offline viewing, editing, or archival. Handles various formats and quality options.
Lightweight WSI tile extraction and preprocessing. Use for basic slide processing tissue detection, tile extraction, stain normalization for H&E images. Best for simple pipelines, dataset preparation, quick tile-based analysis. For advanced spatial proteomics, multiplexed imaging, or deep learning pipelines use pathml.
Microscopy data management platform. Access images via Python, retrieve datasets, analyze pixels, manage ROIs/annotations, batch processing, for high-content screening and microscopy workflows.
Python library for working with DICOM (Digital Imaging and Communications in Medicine) files. Use this skill when reading, writing, or modifying medical imaging data in DICOM format, extracting pixel data from medical images (CT, MRI, X-ray, ultrasound), anonymizing DICOM files, working with DICOM metadata and tags, converting DICOM images to other formats, handling compressed DICOM data, or processing medical imaging datasets. Applies to tasks involving medical image analysis, PACS systems, radiology workflows, and healthcare imaging applications.
This skill should be used when working with pre-trained transformer models for natural language processing, computer vision, audio, or multimodal tasks. Use for text generation, classification, question answering, translation, summarization, image classification, object detection, speech recognition, and fine-tuning models on custom datasets.
How to use it
Take samuraigpt/muapi-photo-pack-generator from the repository into ~/.claude/skills for personal
use, or into .claude/skills inside a project.
The agent identifies a skill by the name field in its header. Two skills with the
same name cannot sit side by side — one of them will be ignored.