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gpt-image-2-style-library — Claude Code skill: what it does

Converts user ideas into production-ready GPT-Image2 prompts using the awesome-gpt-image-2 catalog. Helps configure layout, style tags, and concrete constraints.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓ 
npx skills add freestylefly/awesome-gpt-image-2 --skill gpt-image-2-style-library -a claude-code
Open on GitHub

What gpt-image-2-style-library does

The skill matches an image request against templates from the awesome-gpt-image-2 repository. It identifies the target format, such as posters, UI mockups, infographics, or product photos. Next, it looks up matching style tags, scene tags, and example cases. When multiple templates fit the request, the agent presents two or three options with brief rationale.

Each generated prompt follows a fixed structure: subject, composition, visual materials, label specifications, aspect ratio, and negative details. The skill reads references/style-library.md, which is generated from data/style-library.json. Without this reference file, the agent defaults to model memory and loses verified template names. If the source repository updates, running npm run generate:style-skill rebuilds the reference.

What it helps with

  • match an image request to tested GPT-Image2 style tags and templates
  • structure prompts with explicit layout, materials, and label constraints
  • isolate negative details and avoid typical generation artifacts
  • generate multiple related visual concepts within a single template

Example prompts for the agent

  • Use gpt-image-2-style-library to create an infographic system map prompt
  • Find a template in awesome-gpt-image-2 for a product photoshoot with exact aspect ratio
  • Rewrite my poster concept into a GPT-Image2 prompt with style tags and negative constraints

How to install gpt-image-2-style-library

1Skills CLI (Vercel)

npx skills add freestylefly/awesome-gpt-image-2 --skill gpt-image-2-style-library -a claude-code

2Manually: put the files in place

~/.claude/skills/gpt-image-2-style-library/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/gpt-image-2-style-library/

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Questions about gpt-image-2-style-library

How to install gpt-image-2-style-library in Claude Code?

Run npx skills add freestylefly/awesome-gpt-image-2 --skill gpt-image-2-style-library -a claude-code. The skill file is placed in ~/.claude/skills/gpt-image-2-style-library/SKILL.md.

What does gpt-image-2-style-library do?

It translates natural language image ideas into structured GPT-Image2 prompts. The agent selects relevant templates, formats layout and text requirements, and outputs a copy-ready prompt.

How does the skill maintain its style catalog?

It reads references/style-library.md, which is generated from data/style-library.json. When the upstream repository changes, run npm run generate:style-skill to update the skill data.

Source text

SKILL.md · MIT 
---
name: gpt-image-2-style-library
description: Choose GPT-Image2 / gpt-image-2 visual styles and industrial prompt templates from the awesome-gpt-image-2 style library. Use when an agent needs to create, rewrite, classify, or improve image-generation prompts with repository-backed templates, categories, style tags, scene tags, pitfalls, and example cases.
---

# GPT-Image2 Style Library

Use this skill to turn a user's image-generation intent into a production-ready GPT-Image2 prompt using the awesome-gpt-image-2 style library.

## Example Output

![City life system map example](assets/city-life-system-map.png)

Example request: `用 gpt-image-2-style-library 技能生成城市生命系统图谱`

## Reference

- Read `references/style-library.md` before choosing a template or style.
- The reference is generated from `data/style-library.json` in the repository.
- Prefer the reference over memory when template names, categories, covers, or style tags matter.

## Workflow

1. Detect the user's language and answer in that language.
2. Identify the user's target output: product, poster, UI, infographic, brand, photo, illustration, character, scene, history, document, or special task.
3. Match the request in this order: template category, visual style tag, scene tag, then nearest example cases.
4. If one template is clearly strongest, use it directly. If several are plausible, present 2-3 options with short reasons and ask the user to choose.
5. Build the final prompt with these blocks:
   - subject and task
   - composition and layout
   - visual style and materials
   - text and label requirements
   - aspect ratio and output format
   - constraints and negative details
6. Include the selected template name and any useful example case IDs.

## Output Defaults

- Provide a copyable prompt first.
- Keep constraints concrete: exact text, aspect ratio, readable labels, layout hierarchy, and avoided artifacts.
- For Chinese requests, write the final prompt in Chinese unless the user asks for English.
- For English requests, write the final prompt in English unless the user asks for Chinese.
- When the user asks for multiple concepts, reuse one template and vary subject, composition, palette, and scene.

## Maintenance

When the source repository changes, run:

```bash
npm run generate:style-skill
```

To install the skill into the local Codex skill folder, run:

```bash
npm run install:skill
```

© freestylefly · MIT · freestylefly/awesome-gpt-image-2

See also

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