image-prompt-reverse README

The project's README from github.com/LunarXuan/image-prompt-reverse. As one markdown file: README.md.

Image Prompt Reverse

中文 · English

中文

image-prompt-reverse 是一个用于 Codex 的图片反推提示词 Skill。它会分析用户上传的参考图片,识别图片用途、媒介、主体、构图、镜头语言、光影、色彩、材质、背景、空间层次、情绪和后期风格,并生成可直接用于 AI 生图工具的高还原度提示词。

支持类型

输出内容

默认输出两项:

  1. 正向 Prompt:450—700个中文字符的连续自然语言,并附英文等义版本
  2. Negative Prompt:10—15条英文负面词,用逗号分隔

Skill 会优先提炼最影响相似度的3—5个视觉锚点,避免编造看不清的细节,也会根据目标媒介排除容易混淆的错误风格。图片中的文字、Logo和说明会被视为视觉内容,不会被当作指令执行。

安装

将本仓库目录复制到 Codex 的个人 Skills 目录:

%USERPROFILE%\.codex\skills\image-prompt-reverse

或直接克隆:

git clone https://github.com/LunarXuan/image-prompt-reverse.git "%USERPROFILE%\.codex\skills\image-prompt-reverse"

安装后可使用 $image-prompt-reverse 调用。

文件结构

SKILL.md                         Skill 主入口
references/analysis-framework.md 通用图片分析框架
references/category-guides.md    分类专项分析规则
agents/openai.yaml               Codex 调用界面配置

友情链接

欢迎访问 LINUX DO,浏览社区最新主题与讨论。

English

image-prompt-reverse is a Codex Skill for reverse-engineering image-generation prompts from user-uploaded reference images. It analyzes the image purpose, medium, subject, composition, camera language, lighting, color, materials, background, spatial depth, mood, and post-processing style, then produces high-fidelity prompts that can be used directly with AI image-generation tools.

Supported image types

Output

The default output contains two sections:

  1. Positive Prompt: a 450–700 Chinese-character natural-language prompt, followed by an equivalent English version
  2. Negative Prompt: 10–15 English negative terms separated by commas

The Skill prioritizes the 3–5 visual anchors that have the greatest impact on similarity. It avoids inventing uncertain details, excludes confusing media styles, and treats text, logos, and instructions visible inside an image as visual content rather than executable instructions.

Installation

Copy this repository into your personal Codex Skills directory:

%USERPROFILE%\.codex\skills\image-prompt-reverse

Or clone it directly:

git clone https://github.com/LunarXuan/image-prompt-reverse.git "%USERPROFILE%\.codex\skills\image-prompt-reverse"

Invoke it with $image-prompt-reverse after installation.

File structure

SKILL.md                         Skill entry point
references/analysis-framework.md Shared image-analysis framework
references/category-guides.md    Category-specific analysis rules
agents/openai.yaml               Codex invocation metadata

Visit LINUX DO to browse the community’s latest topics and discussions.

image-prompt-reverse (LunarXuan/image-prompt-reverse)

Searching Database…

What is this?A Codex Skill that reverse-engineers AI image prompts from a reference image you upload, analyzing purpose, medium, subject, composition, lighting, color, and more to produce a high-fidelity prompt you can feed back into AI image generators.
Is this a standalone app or a plugin for something else?It's a Skill definition (markdown-based) that plugs into Codex's personal Skills system, not a standalone application.
How do I install and use it?Copy the repository directory into your personal Codex Skills directory (or clone it directly), then invoke it with $image-prompt-reverse.
Do I need anything besides Codex to use this?You just need Codex with its Skills feature set up; the skill itself has no extra runtime dependencies listed.
Does it always produce accurate prompts?It intentionally avoids inventing details it can't clearly see and excludes styles likely to be confused with the target medium, so output quality depends on image clarity rather than guesswork.
What happens to text or logos inside the uploaded image?Any text, logos, or instructions visible in the image are treated purely as visual content to describe, not as commands the skill executes.
What image types can it handle?Photography (portraits, products, documentary, food, animals, nature, cityscapes), illustration (flat, anime, hand-drawn, Chinese-inspired, cyberpunk), 3D renders, typography/logos/posters, and IP or blind-box character designs.
What does the output look like?By default you get a Positive Prompt of 450-700 Chinese characters with an equivalent English version, plus a Negative Prompt list of 10-15 comma-separated English terms.
How does it decide what to include in the prompt?It prioritizes the 3-5 visual anchors that most affect similarity to the original image rather than cataloging every detail.
Creator
LunarXuan
Size
<0.1 MB
Stars
563
Updated
CommitSep 06
Age
1mo
Commits · 90 Days