zhao123xiao

这是一个可以让agent直接调用gpt-image2进行生图的一个skills。

11
0
85% credibility
Found May 27, 2026 at 11 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This project is a skill that helps an AI assistant create and edit images. You can describe what you want in plain language and get generated images, or you can edit existing photos by painting masks over the areas you want to change. The tool includes a simple drawing interface to highlight exactly which parts of an image should be modified, supports pasting images from your clipboard, and can output high-quality 4K images. Everything is organized with clear summaries so you can track what was created and how.

How It Works

1
💭 Imagine what you want

You describe the image you want to create in plain language, like 'a sunset over mountains with purple clouds'.

2
🎨 Watch your image appear

The AI understands your description and generates beautiful images matching what you asked for.

3
📷 Start with any image

You can also provide an existing photo or illustration to work from, or paste one directly from your clipboard.

4
🖌️ Paint what to change

You use a simple drawing tool to highlight exactly which areas of your image should be edited.

5
Choose your editing style
🤖
Let the AI decide

Choose automatic masks for the center, edges, or full image area

✏️
Draw your own

Use brush, rectangle, or circle tools to paint exactly where changes should go

6
🔄 Describe your changes

Tell the AI what you want to change in those painted areas, like 'make the sky brighter' or 'add flowers'.

🖼️ Get your edited image

The AI applies your changes only to the areas you selected, keeping everything else exactly as it was.

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AI-Generated Review

What is gpt-image2-skill?

This is a Codex skill that lets AI agents generate and edit images using Dreamfield's gpt-image-2 API. Written in Python, it wraps the API with a CLI that handles text-to-image prompts, image-to-image transformations, and mask-based inpainting. The tool auto-processes inputs (resizing, format conversion), supports clipboard capture, and generates detailed summaries of every request. It also includes an interactive mask painter for precise edit region selection.

Why is it gaining traction?

The hook here is mask-based editing without leaving the agent workflow. Developers can paint masks visually, use preset shapes (rectangle, circle, center, border), or leverage alpha channel detection. The self-test command validates the environment offline, and the retry logic handles flaky API calls gracefully. Everything gets logged to JSON summaries for debugging.

Who should use this?

AI agent developers building image generation into their workflows will find this most useful. It's particularly valuable for Codex users who need mask-based inpainting capabilities. Teams exploring Dreamfield's API without committing to a full integration will also benefit from the CLI-first approach and comprehensive error reporting.

Verdict

This is a functional, well-documented tool for its specific use case, though the credibility score of 0.8500000238418579% suggests caution. With only 11 stars and limited community validation, it's still early-stage. The code is clean and the feature set is complete, but teams should evaluate whether the Dreamfield dependency aligns with their long-term roadmap before adopting this into production pipelines.

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