GPT-Image2-Skill: Connect an Image Prompt Library to Codex and Claude Code

If every image task requires manually browsing cases, copying a prompt, replacing variables, and switching to an image tool, the prompt library quickly becomes another operational burden. wuyoscar/GPT-Image2-Skill takes a different approach: it connects image cases and generation capabilities to an Agent workflow.

What It Provides

The project combines image cases, an Agent Skill, and a CLI for common operations:

• Generate an image from a text description;
• Edit an image using reference images;
• Combine multiple reference images;
• Use a mask for local repainting;
• Analyze a reference image and produce candidate prompts;
• Connect image tasks to Codex, Claude Code, and similar Agent workflows.

The goal is not to replace an image model. It is to reduce the manual switching between finding a case, writing an instruction, running the task, and asking for another edit.

An Agent Image Workflow

Describe the goal
  → Agent identifies the task type
  → find a similar case
  → generate candidate prompts
  → replace the subject and constraints
  → call the image model
  → check the result
  → continue editing or finish

You do not need to write a complete prompt at the start. Provide the task, subject, scene, and constraints. The Agent can propose directions before you confirm one.

Why Prompt Extraction Helps

When you already have a reference image you like, a vision model can help break down:

• Subject and background;
• Composition and camera;
• Light, materials, and color;
• Style and post-processing;
• Text area and layout;
• Instructions that can be edited next.

The result is not an exact recovery of the original prompt. Treat it as a structured description of how to approach the image, then adapt it to your own subject and model.

Boundaries When Connecting an Agent

Before installing the Skill, check:

• Whether the Agent already has the same capability;
• Whether the installation is project-scoped or user-scoped;
• Which dependencies and environment variables the CLI needs;
• Whether images and prompts will be sent to an external model service;
• Whether output files or directories can contain sensitive material.

Do not overwrite an existing Skill, change global configuration, or create an API-key file just because a README contains an install command. Keep credentials in a controlled environment. Never put them in prompts, logs, or Git repositories.

When It Is Worth Using

It fits workflows that:

• Produce images repeatedly for a known task;
• Frequently edit reference images;
• Need a consistent series of related visuals;
• Want an Agent to participate in prompt search and revision;
• Spend too much time copying content between tools.

For an occasional single image, the model's own interface may be simpler. The Skill pays off in repeated tasks and workflow integration.

Summary

GPT-Image2-Skill is an Agent operation layer above an image model. It connects case retrieval, prompt rewriting, image generation, and editing into one flow. Installation steps, model support, and CLI parameters change with the repository, so use the current project README as the source of truth.