Token导航 LogoToken导航TokenDH.com
前端设计需要联网github未标认证来源可访问许可证需确认审计提醒

muapi-photo-pack-generatormuapi 照片包生成器

Agent Skill

用于辅助图像生成、图片编辑、视觉素材处理或图像模型工作流。它适合让 Agent 根据文本生成图片、处理背景、整理视觉提示词或调用相关图像工具。使用时需要确认输入图片、版权来源、输出格式和模型限制;涉及人物、品牌、商品或公开展示素材时,应额外核对授权、真实性和内容合规边界。

总安装

4,425

周安装

179

GitHub Stars

3,081

下载量

1,389
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:muapi-photo-pack-generator(muapi 照片包生成器)
来源仓库:https://github.com/samuraigpt/generative-media-skills
仓库路径:skills/muapi-photo-pack-generator
安装命令:
npx skills add https://github.com/samuraigpt/generative-media-skills --skill muapi-photo-pack-generator
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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

简介

用于辅助图像生成、图片编辑或视觉素材处理,支持文本生成图片和提示词整理。

  • 适用于图像模型工作流、背景处理或视觉内容创作等前端设计场景。
  • 通过 npx skills add 命令从 samuraigpt/generative-media-skills 仓库安装。
  • 使用时需确认输入图片、版权来源、输出格式及模型限制;涉及人物或品牌时应核对授权。
  • muapi-photo-pack-generator 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

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
  • 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

CategoryBest ForAesthetic
LinkedInProfessionalStudio
CEOFoundersOffice
TinderDatingLifestyle
OldMoneyLuxuryEstate
CyberpunkFantasyNeon
FitnessGymAthletic
TravelSocialBali/Paris
90sRetroVintage
HolidaySeasonalFestive

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.96%
按下载量换算527

Claude

29.65%
按下载量换算412

Cursor

18.94%
按下载量换算263

Gemini CLI

9.78%
按下载量换算136

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills