gpt 图像 2 风格 Libr
- 作者仓库星标 6,954
- 作者仓库 awesome-gpt-image-2
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

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.mdbefore choosing a template or style. - The reference is generated from
data/style-library.jsonin the repository. - Prefer the reference over memory when template names, categories, covers, or style tags matter.
Workflow
- Detect the user's language and answer in that language.
- Identify the user's target output: product, poster, UI, infographic, brand, photo, illustration, character, scene, history, document, or special task.
- Match the request in this order: template category, visual style tag, scene tag, then nearest example cases.
- 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.
- 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
- 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:
npm run generate:style-skill
To install the skill into the local Codex skill folder, run:
npm run install:skill- 流狐分类
- AI 智能
- 作者声明 Agent
- 未找到明确声明;不据此推断已兼容或已测试
- 静态检查
- 88 / 100 · 启发式扫描,不代表运行安全
- 作者 / 版本 / 许可
- @freestylefly · 未声明 license
- 流狐 Token 估算
- 低消耗
- 流狐接入估算
- 即装即用
- 是否需要外部 API Key
- 未发现要求
- 检测到的系统要求
- macOS · Linux · Windows
- 底层运行要求
- 未声明
- 检测到的文件与系统行为
-
- 只读
- 允许写入 / 修改
- 检测到的网络行为
- 仅限本地
- 安装命令数
- 无(仅作为资料)
档案由构建时根据 SKILL.md 与安装命令自动衍生,可能与作者实际意图存在差异。
需要注意: 未限定 allowed-tools,默认拥有全部工具权限。
# Example Output
 Example request: `用 gpt-image-2-style-library 技能生成城市生命系统图谱` City life system map example Example request: 用 gpt-image-2-style-library 技能生成城市生命系统图谱
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.
Detect the user's language and answer in that language. Identify the user's target output: product, poster, UI, infographic, brand, photo, illustration, character, scene, history, document, or special task. Match the request in this order: template category,…
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.
When the source repository changes, run: To install the skill into the local Codex skill folder, run:
# 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

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.
… 作者原文负责流程事实;流狐只索引当前章节、要点、文件与命令。
章节 -> Example Output → Reference → Workflow → Output Defaults → Maintenance
要点 -> - Read references/style-library.md before choosing a template or style. · 1. Detect the user's language and answer in that language. · - Provide a copyable prompt first.
文件/命令 -> 用 gpt-image-2-style-library 技能生成城市生命系统图谱 · references/style-library.md · data/style-library.json · assets/city-life-system-map.png
内容 SHA-256 -> 6c862849e1e3
方法与流程
适用与边界
原文中的明确线索
用 gpt-image-2-style-library 技能生成城市生命系统图谱、references/style-library.md、data/style-library.json、assets/city-life-system-map.png