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AI Prompt Reverse Engine

通过多模态图像理解把图片归入摄影、插画、3D渲染、排版/标志、风景、角色设计等7个视觉类别,提取主体、风格、光照、色彩、构图等特征并输出JSON结构化提示词,再按类别适配不同AI模型的提示词策略。材料只给出方法与规则,未给出可执行实现。

keweizhan
keweizhan
热度 30.22
最近更新 2026-05-11 17:47:30
分类:创作依赖:内部调用大模型 / 读写文件 / 代码执行应用场景:图像生成

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 prompt-reverse-skill
Metadata
name
prompt-reverse-skill
description
Convert image to structured prompts for multiple AI models
version
1.0.0
tags
["ai","multimodal","prompt","image"]

Prompt Reverse Skill

Description

Convert an image into structured prompts using a category-aware prompt generation system.

This skill performs:

  • Image understanding (multimodal analysis)
  • Structured feature extraction (JSON)
  • Visual type classification
  • Style-aware prompt generation
  • Multi-model prompt adaptation

Visual Category System

This skill uses a 7-category visual classification framework:

  1. Photography
  2. Illustration
  3. 3D Render
  4. Typography / Logo
  5. Landscape
  6. Character Design
  7. General (fallback)

Each category applies specialized prompt strategies.


Prompt Strategy by Category

Photography

  • camera lens (50mm, wide angle)
  • lighting (cinematic, HDR)
  • depth of field
  • realism emphasis

Illustration

  • drawing style (anime, digital art)
  • line quality
  • color palette

3D Render

  • rendering engine (octane, blender)
  • material (PBR)
  • lighting & shadows

Typography / Logo

  • layout design
  • font style
  • vector graphics

Landscape

  • composition (wide angle, perspective)
  • atmospheric depth
  • natural lighting

Character Design

  • face details
  • pose and expression
  • stylization

Inputs

image_path

Path to the input image.


Outputs

structured_data

{
  "subject": "...",
  "style": "...",
  "lighting": "...",
  "color": "...",
  "composition": "...",
  "details": "..."
}