# Illustration and Art Prompt Templates for GPT-Image2: A Complete Guide

> Discover illustration and art prompt templates for GPT-Image2. Explore plain-text and structured JSON formats in this complete guide to enhance your AI art generation.

- Repository: [苍何/awesome-gpt-image-2](https://github.com/freestylefly/awesome-gpt-image-2)
- Tags: deep-dive
- Published: 2026-08-24

---

**The freestylefly/awesome-gpt-image-2 repository defines two distinct prompt templates for GPT-Image2 generation: a plain-text template for manual input located at [`docs/templates.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/templates.md) anchor `tpl-illustration`, and a structured JSON template for programmatic agent control.**

The **GPT-Image2** skill relies on carefully structured prompting to generate high-quality illustrations. According to the source code in `freestylefly/awesome-gpt-image-2`, the system splits visual generation into two complementary approaches: human-readable text prompts and machine-parseable JSON schemas. Both templates are maintained in [`docs/templates.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/templates.md) and consumed by the agent skill defined in [`agents/skills/gpt-image-2-style-library/SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/agents/skills/gpt-image-2-style-library/SKILL.md).

## The Plain-Text Illustration Template

The **Illustration Template** provides a fill-in-the-blanks format optimized for quick experimentation and manual prompt entry. This template uses Chinese placeholders to define visual parameters.

The template structure in [`docs/templates.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/templates.md) follows this pattern:

```text
创作[题材]插画，主角为[角色/主体]。
画风：[日漫/水彩/扁平/厚涂]，线条：[细腻/粗犷]。
配色：[配色方案]，背景：[简洁/复杂场景]。
构图：[近景/中景/远景]，重点表现[细节]。
输出：可用于封面或社媒发布的高质量插画。

```

Key placeholders include:
- **[题材]** - Subject or theme (e.g., sci-fi city, fantasy forest)
- **[画风]** - Art style (anime, watercolor, flat, oil painting)
- **[线条]** - Line work quality (fine/detailed or bold/rough)
- **[配色方案]** - Color palette
- **[构图]** - Composition (close-up, mid-shot, wide shot)

This format is ideal for rapid iteration when testing GPT-Image2 capabilities directly through the interface.

## The JSON Artistic Illustration Template

For **programmatic usage** and agent-driven calls, the repository provides a structured JSON template. This format explicitly separates each visual attribute, enabling input validation and constraint enforcement.

The JSON schema defined in [`docs/templates.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/templates.md) uses the following structure:

```json
{
  "type": "Artistic Illustration",
  "art_style": "Studio Ghibli inspired anime style",
  "scene": {
    "description": "A giant flying whale carrying a small cozy village on its back",
    "details": "Windmills turning, tiny people looking over the edge, fluffy white clouds"
  },
  "palette": "Vibrant sky blue, lush greens, soft pastel accents",
  "technique": "Cel shading, detailed background art, soft glowing magical aura",
  "mood": "Whimsical, adventurous, nostalgic"
}

```

Required fields include:
- **`type`** - Must be set to `"Artistic Illustration"` to trigger the correct rendering pipeline
- **`art_style`** - Specific aesthetic direction (e.g., "Cyberpunk neon aesthetic")
- **`scene.description`** - Primary subject matter
- **`scene.details`** - Fine-grained visual elements
- **`palette`** - Color scheme specification
- **`technique`** - Rendering approach (e.g., "Cel shading", "Oil painting texture")
- **`mood`** - Emotional tone of the output

## Implementing GPT-Image2 Prompts in Code

The [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js) endpoint accepts either format through distinct payload structures. Here are the implementation patterns for both templates.

### Text-Based API Implementation

When using the plain-text template, pass the formatted string to the `prompt` field:

```javascript
const payload = {
  prompt: `创作科幻城市插画，主角为未来飞行车。画风：厚涂，线条：细腻。配色：蓝紫渐变，背景：高楼天际线。构图：远景，重点表现光线反射。输出：高质量社媒海报。`
};

fetch('/api/generate-image', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify(payload)
})
.then(res => res.blob())
.then(blob => {
  const img = document.createElement('img');
  img.src = URL.createObjectURL(blob);
  document.body.appendChild(img);
});

```

The `prompt` field directly accepts the illustration template's placeholder-filled string, allowing the GPT-Image2 model to interpret the visual parameters from natural language context.

### JSON-Based API Implementation

For agent-driven generation, wrap the JSON template in a `jsonPrompt` field:

```javascript
const payload = {
  jsonPrompt: {
    "type": "Artistic Illustration",
    "art_style": "Studio Ghibli inspired anime style",
    "scene": {
      "description": "A giant flying whale carrying a small cozy village on its back",
      "details": "Windmills turning, tiny people looking over the edge, fluffy white clouds"
    },
    "palette": "Vibrant sky blue, lush greens, soft pastel accents",
    "technique": "Cel shading, detailed background art, soft glowing magical aura",
    "mood": "Whimsical, adventurous, nostalgic"
  }
};

fetch('/api/generate-image', {
  method: 'POST',
  headers: { 'Content-Type': 'application/json' },
  body: JSON.stringify(payload)
})
.then(res => res.blob())
.then(blob => {
  const img = document.createElement('img');
  img.src = URL.createObjectURL(blob);
  document.body.appendChild(img);
});

```

Using `jsonPrompt` ensures type-safe parameter passing and enables backend validation against the schema defined in [`SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/SKILL.md).

### Dynamic Template Selection

To support runtime template switching, implement a builder function that routes to the appropriate format:

```javascript
function buildPrompt(type, data) {
  if (type === 'text') {
    return `创作${data.theme}插画，主角为${data.hero}。画风：${data.style}，线条：${data.line}。配色：${data.palette}，背景：${data.background}。构图：${data.composition}，重点表现${data.focus}。输出：高质量插画。`;
  } else {
    return {
      type: "Artistic Illustration",
      art_style: data.style,
      scene: { description: data.sceneDesc, details: data.sceneDetails },
      palette: data.palette,
      technique: data.technique,
      mood: data.mood
    };
  }
}

```

This utility allows the GPT-Image2 skill to accept user preferences and format them appropriately for either manual or automated workflows.

## Skill Architecture and Integration

The **GPT-Image2 Style Library** skill ([`agents/skills/gpt-image-2-style-library/SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/agents/skills/gpt-image-2-style-library/SKILL.md)) orchestrates template consumption. It validates incoming requests against the JSON schema for programmatic calls or sanitizes text prompts for the plain-text template. The skill ensures that parameters like `art_style` and `technique` map to valid generation options supported by the underlying model.

## Summary

- **Two template formats** exist in [`docs/templates.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/templates.md): a plain-text Chinese template for manual entry and a JSON schema for programmatic control.
- **Text templates** use the `prompt` field in API calls and support rapid experimentation with visual parameters like 画风 (art style) and 配色 (color palette).
- **JSON templates** use the `jsonPrompt` field with explicit keys: `art_style`, `scene`, `palette`, `technique`, and `mood`.
- **Implementation flexibility** allows dynamic switching between formats using builder functions that route to [`api/generate-image.js`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/api/generate-image.js).

## Frequently Asked Questions

### What is the difference between the text and JSON templates in GPT-Image2?

The text template (`tpl-illustration`) is a human-readable format with Chinese placeholders for quick manual entry, while the JSON template provides machine-readable structure with explicit keys for `art_style`, `palette`, and `mood` for automated agent integration.

### Where are the prompt templates defined in the repository?

The templates are defined in [`docs/templates.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/docs/templates.md) under the `tpl-illustration` anchor. The skill interface that consumes these templates is documented in [`agents/skills/gpt-image-2-style-library/SKILL.md`](https://github.com/freestylefly/awesome-gpt-image-2/blob/main/agents/skills/gpt-image-2-style-library/SKILL.md).

### Can I mix Chinese and English content in the prompt templates?

Yes. The plain-text template uses Chinese structural markers (创作, 画风, 配色) but accepts English content within the brackets. The JSON template accepts any language in its string values.

### Which template should I use for programmatic image generation?

Use the **JSON Artistic Illustration template** for programmatic usage. It provides type safety through structured fields like `scene.description` and `technique`, making it easier to validate inputs and maintain consistent outputs in automated workflows.