How to Use the gpt-image-2-style-library for Generating Infographic Prompts

The gpt-image-2-style-library provides a JSON-based style library with a getStyle() helper that transforms named style templates into ready-to-use GPT-Image-2 prompts through simple placeholder replacement.

The gpt-image-2-style-library is a reusable skill in the freestylefly/awesome-gpt-image-2 repository designed to streamline infographic generation. It packages curated prompt templates as JSON objects with defined placeholders, eliminating manual prompt engineering for common visual formats. This guide covers installation, the core API, and practical implementation patterns drawn directly from the source code.

Installing the gpt-image-2-style-library

You have two installation paths depending on your workflow.

Option 1: Direct NPM Installation

npm install ./agents/skills/gpt-image-2-style-library

Option 2: Using the Provided Install Script

node ./agents/skills/gpt-image-2-style-library/bin/install.mjs

The install.mjs script at agents/skills/gpt-image-2-style-library/bin/install.mjs handles dependency resolution and copies the library assets into your project structure.

Understanding the Style Library Structure

The style definitions live in data/style-library.json. Each entry follows a consistent schema:

{
  "name": "modern-infographic",
  "description": "A clean, data-focused infographic with bold colors.",
  "prompt": "Create a modern infographic titled \"{title}\" showing the following data: {data}. Use a blue-green palette and include icons for each bullet point.",
  "placeholders": ["title", "data"]
}

Key fields include:

• name – Unique identifier passed to getStyle()
• prompt – The template string with bracketed placeholders
• placeholders – Array of required keys you must provide

Loading Styles with the getStyle() API

The skill exports a getStyle(name) function as its primary interface. According to agents/skills/gpt-image-2-style-library/package.json, this is the package entry point.

Basic Usage Pattern

import { getStyle } from 'gpt-image-2-style-library';

// Load the style definition
const style = getStyle('modern-infographic');

// Inspect available placeholders
console.log(style.placeholders); // ['title', 'data']

The function returns an object containing:

• prompt – The template string
• placeholders – Array of required replacement keys
• Optional description and tone metadata

Building Complete Prompts from Templates

Template population uses straightforward string replacement. You must supply values for every placeholder listed in the style definition.

Example: Modern Infographic Style

import { getStyle } from 'gpt-image-2-style-library';

const style = getStyle('modern-infographic');

const prompt = style.prompt
  .replace('{title}', 'Global Internet Usage 2024')
  .replace('{data}', `
- 4.9B users worldwide
- 65% mobile access
- Growth +12% YoY
`);

console.log(prompt);
// Output: Create a modern infographic titled "Global Internet Usage 2024"...

Chaining Multiple Replacements

For styles with many placeholders, use a reducer pattern:

import { getStyle } from 'gpt-image-2-style-library';

const style = getStyle('retro-data-chart');
const data = {
  '{title}': 'Q3 Revenue Breakdown',
  '{metric1}': 'Subscriptions: $4.2M',
  '{metric2}': 'Services: $2.8M',
  '{metric3}': 'Licensing: $1.5M'
};

const prompt = Object.entries(data).reduce(
  (acc, [key, value]) => acc.replace(key, value),
  style.prompt
);

Sending Prompts to the GPT-Image-2 API

The skill integrates with OpenAI-compatible endpoints as defined in agents/skills/gpt-image-2-style-library/agents/openai.yaml. Standard HTTPS requests work with any HTTP client.

Node.js Implementation with node-fetch

import fetch from 'node-fetch';

const API_KEY = process.env.OPENAI_API_KEY;

async function generateInfographic(prompt) {
  const response = await fetch('https://api.openai.com/v1/images/generations', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      Authorization: `Bearer ${API_KEY}`
    },
    body: JSON.stringify({
      prompt,
      n: 1,
      size: '1024x1024'
    })
  });

  const data = await response.json();
  return data.data[0].url;
}

Complete Integration Example

import { getStyle } from 'gpt-image-2-style-library';
import fetch from 'node-fetch';

async function createInfographic(styleName, replacements) {
  // 1. Load style
  const style = getStyle(styleName);
  
  // 2. Build prompt
  let prompt = style.prompt;
  for (const [key, value] of Object.entries(replacements)) {
    prompt = prompt.replace(`{${key}}`, value);
  }
  
  // 3. Generate image
  const response = await fetch('https://api.openai.com/v1/images/generations', {
    method: 'POST',
    headers: {
      'Content-Type': 'application/json',
      Authorization: `Bearer ${process.env.OPENAI_API_KEY}`
    },
    body: JSON.stringify({ prompt, n: 1, size: '1024x1024' })
  });
  
  const result = await response.json();
  return result.data[0].url;
}

// Usage
const url = await createInfographic('modern-infographic', {
  title: 'Renewable Energy Share 2024',
  data: 'Solar: 34%\nWind: 27%\nHydro: 22%'
});

Key Source Files Reference

File Path	Purpose
agents/skills/gpt-image-2-style-library/package.json	Package manifest, exposes getStyle entry point
agents/skills/gpt-image-2-style-library/bin/install.mjs	Installation automation script
data/style-library.json	Core JSON template definitions
agents/skills/gpt-image-2-style-library/agents/openai.yaml	OpenAI-compatible endpoint configuration
agents/skills/gpt-image-2-style-library/references/style-library.md	Human-readable style documentation

Critical Implementation Details

Placeholder names are case-sensitive. The getStyle() function does not normalize keys—{Title} and {title} are treated as distinct tokens. Always match the exact placeholder names defined in style.placeholders.

All placeholders must be populated. The library performs no validation; incomplete templates yield malformed prompts that may degrade image generation quality.

No built-in content filtering. The skill passes prompts directly to the API. Implement your own safety checks if exposing generated images publicly.

Rate limit awareness. OpenAI endpoints enforce request quotas. Batch operations through Promise.allSettled() for multiple infographics:

const jobs = datasets.map(data => 
  createInfographic('modern-infographic', data)
);
const results = await Promise.allSettled(jobs);

Summary

• Install via npm install or bin/install.mjs
• Load styles using getStyle(name) from the package entry point
• Populate templates by replacing placeholders with your data
• Generate images through standard OpenAI API calls
• Reference data/style-library.json for available styles and references/style-library.md for documentation

The gpt-image-2-style-library abstracts prompt engineering into reusable, version-controlled templates while preserving full flexibility for dynamic content injection.

Frequently Asked Questions

What styles are available in the gpt-image-2-style-library?

The library ships with multiple infographic styles defined in data/style-library.json. Inspect this file or read references/style-library.md for the current inventory. Common entries include modern-infographic and retro-data-chart, with community contributions expanding the collection via pull requests.

Can I add custom styles to the library?

Yes. The JSON format is straightforward: add an object with name, description, prompt with {placeholder} tokens, and a placeholders array. Place your entry in data/style-library.json and reload your application. Submit pull requests to the freestylefly/awesome-gpt-image-2 repository to share additions.

Does getStyle() validate that all placeholders are filled?

No. The getStyle() function only retrieves the template definition. Validation occurs implicitly when the GPT-Image-2 API receives the prompt—unfilled placeholders result in literal {key} text in your generated image description. Implement pre-flight checks in your own code if needed.

Is the gpt-image-2-style-library tied to OpenAI specifically?

The default configuration targets OpenAI-compatible endpoints per agents/openai.yaml, but the skill itself is provider-agnostic. The getStyle() output is a plain string suitable for any image generation API accepting text prompts. Adapt the fetch call to your provider's endpoint and authentication scheme.

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