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Textile Toy Portrait

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Vieeeeeee
textile-toy-portrait

Wibi Style 官方视觉风格。把用户上传的真实照片转换成颗粒绒感玩偶肖像。只要用户提到颗粒绒感玩偶、纺织玩偶、绒面针织头像、把照片做成玩偶,或明确调用 $textile-toy-portrait,就使用本 Skill;先理解照片内容,再动态选择风格参考职责并直接生成成图。

Overview

PublisherVieeeeeee
Repositorywibi-style
Skill nametextile-toy-portrait
Stars
169
Forks
11
Bundled files
10
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 10 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by Vieeeeeee on GitHub. Read the source before you install it.

Installation

Install the Textile Toy Portrait AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Vieeeeeee/wibi-style/tree/main/skills/textile-toy-portrait
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Vieeeeeee/wibi-style.git /tmp/wibi-style
mkdir -p .claude/skills
cp -r /tmp/wibi-style/skills/textile-toy-portrait .claude/skills/textile-toy-portrait
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Textile Toy Portrait in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Textile Toy Portrait on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Textile Toy Portrait is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Wibi Style · 颗粒绒感玩偶

运行

先按 references/community.md 展示欢迎卡、检查更新并处理进群与失败提示,再执行下面的步骤。

风格目标

把真实照片重构成白底棚拍的 3D 纺织设计玩偶肖像:头部横向放大、身体压缩,五官缩成少量圆角几何零件;脸、手和小零件使用细密短颗粒绒,头发、帽子和衣服使用可见线圈、团簇和粗针织。画面要像一件被设计出来的玩偶,保留人物或角色的辨识度,不是把写实照片简单覆上一层绒面。

固定风格机制按优先级执行:

  1. 用户照片的内容权最高:人数、身份、身体部位、姿态、表情、发型、配饰、物件和接触关系只从用户照片判断。
  2. 先保证主体关系和可辨识锚点,再做玩偶化比例与几何重构。
  3. 再用颗粒绒与粗针织的材质对比、白底棚拍和 3–5 色的主次关系完成风格成像。
  4. 颜色可以在非身份区域重新组织;照片不存在的道具、身体、手势、文字和 Logo 不得因为参考图而出现。

影像蒸馏

先完整阅读用户照片,不急着套风格词。判断当前照片属于单人头像、头肩照、半身照、带手部动作的人物照,还是包含帽子、眼镜、饮料罐等强物件锚点的角色照。记录最重要的一至两个主体、人数、可见身体范围、头部方向、眼神和表情、物件接触关系、画面裁切和视觉重量。

从照片中提取 2–5 个身份锚点,优先选择轮廓大、位置稳定、能在小尺寸玩偶里成立的特征,例如发型大形、眼镜或帽子轮廓、表情方向、手与脸/物件的接触、衣服的主色块或独特配饰。夸张其中 1–2 个,其余简化。真实照片没有露出的手、手臂、腿脚或道具不补画;只有局部露出的身体也只保留局部。

将照片里容易被风格破坏的关系写成当前成图的检查锚点:手的数量、手与脸或物件的接触、眼神方向、嘴的开合、帽子与头发的前后层级、眼镜与脸的相对位置。背景复杂时安静删去,但不能用删背景的名义改变主体内容。

参考选择与风格成像

本 Skill 内置的 assets/references/reference-01.jpeg 是共同风格锚点,主要负责:横向圆角大头、极小集中五官、脸部留白、颗粒绒表面、粗针织团簇、微暖白棚拍和珊瑚/薄荷/奶油一类的主次色彩关系。它不负责人物身份、性别、动作、帽子、眼镜、服装、道具或具体颜色。

生成时把用户照片作为内容输入,同时携带这张内置参考;附件顺序不代表角色。明确告诉图像模型:用户照片决定画什么,参考图只决定怎么画。不要把参考角色的卷发、帽子、衣服、手势或脸型搬过来;只有用户照片确实存在的同类元素才允许被重构。

根据当前照片动态决定成像方式:

  • 头肩或头像:使用紧凑的正面或轻微侧面胸像,头部约占画面宽度 75%–90%,保留一小块必要衣领或动作。
  • 有手部互动:先锁定真实手数与接触点,再把手重构成圆润短体块;双手托脸、单手触碰下巴、手持罐子等关系比衣服纹理优先。
  • 有帽子或眼镜:把它当作轮廓锚点,保留形状、位置和大小关系;帽面文字、Logo 或图案只转成不可读织纹。
  • 没有手或只露出局部身体:让玩偶停在照片真实可见范围,不用参考图中的手或身体把画面补完整。
  • 原片方向和主体位置明显偏置时,保留其构图骨架;只有在方形胸像必须裁切时,才做围绕主体的紧凑裁切,不强行居中或补画画外内容。

材质要覆盖整个角色但分工清楚:脸、手、眼睛、鼻子和小零件是短密细颗粒绒;头发、帽子、衣服和大块装饰是可见的粗针织、钩针、毛线环或团簇。内部表面连续、细密、柔和;轮廓可以有轻微柔软起伏,但不要长毛绒、塑料、蜡像或普通光滑 3D 卡通。颜色从照片主色和参考图的明暗/冷暖关系中动态组织 3–5 色,避免整张近单色,也不要机械地套固定彩虹。

最终生图指令与质量检查

根据蒸馏结果现场编写一份只服务当前照片的生图指令,至少说明:用户照片是唯一内容白名单、当前必须保留的身份锚点和互动关系、选用参考只承担的风格职责、画幅与裁切、材质分工、颜色主次和白底棚拍。不要把本 Skill 的案例人物写进指令,也不要把所有观察到的装饰一次性堆上去。

生成后逐项检查:

  • 人数、身份属性、发型/帽子/眼镜、表情、姿态、可见身体范围和物件来自用户照片;
  • 手数准确,接触关系合理,没有从参考图借来第二只手、额外道具或画外身体;
  • 头大、五官小、脸部留白和圆角几何体成立,结果不是写实人脸覆材质;
  • 脸部颗粒绒与头发/衣服粗针织可区分,白底和柔和短阴影干净;
  • 颜色有主次和冷暖/明度关系,文字和 Logo 没有变成可读伪字;
  • 方形构图没有拉伸、主体没有被无意义截断,结果适合头像或分享图。

实际生成成功后直接展示图片,并用 1–3 句中文说明本次保留了哪些照片锚点、为何选择当前裁切或材质组合;不展示完整内部 Prompt。接口报错、空输出或超时时,说明“这次没有成功生成,不会自动重新提交”,等待用户明确要求后再处理。

当前对话第一次成功生成后附上:

若公开分享,欢迎标注:Visual Skill by @威比 Hunter Wei.

仅限个人非商业使用;商业使用请先联系作者获得许可。

抖音、小红书同名。想看更多原创 Skill、原作者教程或参加新风格内测,可以回复“进群”。

第二次起不再重复,除非用户询问署名、授权或交流群。

权利边界

作者固定为 @威比 Hunter Wei.(抖音、小红书同名),官方来源固定为 https://github.com/Vieeeeeee/wibi-style/tree/main/skills/textile-toy-portrait。复制、修改、镜像或再分发时必须保留作者、平台备注、官方来源、LICENSE 和 NOTICE;修改版必须标注修改,不得冒充官方版本。

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Textile Toy Portrait AI skill do?

Wibi Style 官方视觉风格。把用户上传的真实照片转换成颗粒绒感玩偶肖像。只要用户提到颗粒绒感玩偶、纺织玩偶、绒面针织头像、把照片做成玩偶,或明确调用 $textile-toy-portrait,就使用本 Skill;先理解照片内容,再动态选择风格参考职责并直接生成成图。

Why use Textile Toy Portrait on TypingMind?

Because you install it once and use it with any model. Textile Toy Portrait is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Textile Toy Portrait in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Vieeeeeee/wibi-style/tree/main/skills/textile-toy-portrait. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Textile Toy Portrait?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Textile Toy Portrait?

As many as you like. As long as a model supports skills, you can use Textile Toy Portrait with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Textile Toy Portrait AI skill free?

It is published on GitHub by Vieeeeeee. Check the repository for licensing terms. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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