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Photo Pack Generator

该 Skill 先分析参考图的朝向、表情、光线和构图,再用身份锁定提示词调用脚本生成 LinkedIn、Tinder、OldMoney 等风格照片包;强调不描述人物外貌,以避免生成新面孔。

anil-matcha
anil-matcha
热度 84.59
最近更新 2026-05-17 14:24:03
分类:创作依赖:代码执行 / 读写文件 / 第三方 API / 内部调用大模型应用场景:图像生成 / 社交媒体

安装技能

复制下面的话术发给你的 Agent,它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill: npx secure-skills-cli add muapi-photo-pack-skill
Metadata
slug
muapi-photo-pack-skill
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.
acceptLicenseTerms
true

📸 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