How to Integrate GPT-Image2 Style Library with AI Coding Agents: Complete Setup Guide

AI coding agents can integrate GPT-Image2 style library by installing the npm package and invoking the skill through the skills framework, enabling automatic template matching and prompt generation for GPT-Image2 image workflows.

The GPT-Image2 style library is a specialized agent skill that provides structured visual styles, prompt templates, and scene tags for the GPT-Image2 image-generation model. According to the freestylefly/awesome-gpt-image-2 repository, this integration allows Claude Code, Codex, Cursor, and other AI agents to automatically select optimal templates and produce production-ready prompts without manual curation.

Installation Methods for AI Coding Agents

You have two primary paths to integrate this library with your agent workflow: global npm installation or the native skills helper (recommended for most agents).

Method 1: Global npm Installation

Install the package globally and populate local agent skill directories using the CLI installer at bin/install.mjs:

npm install -g gpt-image-2-style-library

# Copy skill files to ~/.claude/skills, ~/.codex/skills, ~/.agents/skills

gpt-image-2-style-library install all

The bin/install.mjs script handles cross-agent discovery by copying files into standard skill locations. After installation, agents automatically detect the skill by name.

Method 2: Skills Helper (Recommended)

For Claude Code, Codex, and Cursor, use the skills CLI for streamlined integration:

npx skills add freestylefly/awesome-gpt-image-2 \
  --skill gpt-image-2-style-library \
  --agent claude-code codex \
  --global --yes --copy

This approach leverages package.json metadata and avoids manual path configuration.

Core Architecture Components

Understanding the file structure helps you customize and debug GPT-Image2 style library integration.

Skill Manifest (SKILL.md)

The agents/skills/gpt-image-2-style-library/SKILL.md file defines the agent workflow:

1. Language detection — Respond in the user's detected language
2. Target output identification — Classify requests (product, poster, UI, infographic)
3. Template matching — Rank candidates by category → visual style tag → scene tag → example cases
4. Prompt construction — Assemble final output using structured blocks
5. Copy-ready delivery — Return executable prompt with optional explanations

Data Store (style-library.json)

The data/style-library.json catalog contains:

• Categories: UI, Infographic, Poster, Chart, Document
• Styles: 3D, Brand, Illustration, Photorealistic, Minimal
• Scenes: Tech, Commerce, History, Nature, Urban
• Templates: Anchors, covers, guidance text, common pitfalls, reference case IDs

Agents read this file at runtime to perform matching without external network calls.

Package Definition (package.json)

{
  "name": "gpt-image-2-style-library",
  "version": "1.0.0",
  "bin": {
    "gpt-image-2-style-library": "bin/install.mjs"
  },
  "files": [
    "SKILL.md",
    "bin/",
    "data/",
    "references/",
    "assets/"
  ]
}

The package.json entry point (bin/install.mjs) enables both global CLI usage and npx execution.

Runtime Integration Example

Below is a complete agent plugin configuration and invocation pattern:

Skill Plugin Definition

{
  "name": "gpt-image-2-style-library",
  "description": "Select a GPT-Image2 template and generate a prompt",
  "type": "skill",
  "entrypoint": "gpt-image-2-style-library"
}

User Invocation

/use gpt-image-2-style-library to create an infographic about renewable energy

Agent Runtime (Simplified)

// Agent loads skill by name from ~/.claude/skills/
const skill = await loadSkill('gpt-image-2-style-library');

// Execute with natural language request
const result = await skill.run({
  request: 'create an infographic about renewable energy'
});

// Output: structured prompt ready for GPT-Image2 API
console.log(result.prompt);

The skill returns prompt blocks for subject, composition, visual style, text/labels, aspect ratio, and constraints — all sourced from style-library.json.

Direct Catalog Access for Custom Agent Logic

For agents requiring programmatic template selection, query style-library.json directly:

import { readFile } from 'fs/promises';

const lib = JSON.parse(
  await readFile('data/style-library.json', 'utf-8')
);

// Find templates matching specific criteria
const infographicTemplates = lib.templates.filter(t =>
  t.styles.includes('Infographic') &&
  t.scenes.includes('Tech')
);

// Access template metadata
console.log(infographicTemplates.map(t => ({
  title: t.title.en,
  anchor: t.anchor,
  guidance: t.guidance
}));

This pattern enables custom ranking algorithms or UI presentations beyond the default skill behavior.

Reference Documentation for Transparency

The agents/skills/gpt-image-2-style-library/references/style-library.md file provides human-readable documentation generated from the JSON catalog. Agents should surface this reference when:

• Users request explanation of selected templates
• Debugging template matching decisions
• Providing style previews (paired with files in assets/)

Example asset: assets/city-life-system-map.png illustrates system diagram styling options.

Key Integration File Paths

File	Purpose	Path
Skill manifest	Workflow definition	agents/skills/gpt-image-2-style-library/SKILL.md
Package metadata	npm/registry integration	agents/skills/gpt-image-2-style-library/package.json
CLI installer	Cross-agent setup	agents/skills/gpt-image-2-style-library/bin/install.mjs
Master catalog	Template/style/scene data	data/style-library.json
Human reference	Generated documentation	agents/skills/gpt-image-2-style-library/references/style-library.md
Visual assets	Example outputs	agents/skills/gpt-image-2-style-library/assets/

Summary

• GPT-Image2 style library integration requires installing the npm package gpt-image-2-style-library and registering it via npx skills add or the global CLI installer.
• No network dependencies at runtime—the skill operates entirely on local JSON data from style-library.json.
• Template matching follows a ranked hierarchy: category → visual style → scene tag → example cases, as defined in SKILL.md.
• Cross-agent compatibility is built into bin/install.mjs, which populates ~/.claude/skills, ~/.codex/skills, and ~/.agents/skills directories.
• Production prompts are assembled from structured blocks and delivered copy-ready for GPT-Image2 API consumption.

Frequently Asked Questions

What AI coding agents are compatible with GPT-Image2 style library?

Claude Code, Codex, Cursor, and any agent implementing the skills framework can integrate this library. The bin/install.mjs script specifically targets ~/.claude/skills, ~/.codex/skills, and ~/.agents/skills directories for automatic discovery.

Does the skill require internet access after installation?

No. The skill reads exclusively from local files—primarily data/style-library.json—making it safe for sandboxed environments. No external API calls occur during template matching or prompt generation.

How can I customize templates for my organization's brand?

Modify data/style-library.json to add custom styles, scenes, or templates, then reinstall the skill. The JSON schema supports organization-specific anchors, guidance text, and example cases. Regenerate references/style-library.md to keep documentation synchronized.

What is the difference between npx skills add and npm install -g?

npx skills add uses the native agent CLI (when available) for cleaner versioning and dependency management. npm install -g followed by gpt-image-2-style-library install all works universally but requires manual reinstallation for updates.

{
  "mcpServers": {
    "instagit": {
      "command": "npx",
      "args": ["-y", "instagit@latest"]
    }
  }
}