‹ 首页

muapi-ugc-lifestyle-try-on

@samuraigpt · 收录于 1 周前 · 上游提交 3 周前

Generate UGC-style (User Generated Content) lifestyle photos of a person wearing or using your product — authentic, relatable, social-media-native imagery.

适合你,如果想让产品照片看起来像真实用户分享

/ 下载安装
muapi-ugc-lifestyle-try-on.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add samuraigpt/generative-media-skills/muapi-ugc-lifestyle-try-on
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- samuraigpt/generative-media-skills/muapi-ugc-lifestyle-try-on
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify samuraigpt/generative-media-skills/muapi-ugc-lifestyle-try-on
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
3754GitHub stars
~789上下文体积 · 单文件
镜像托管

怎么用

商店整理自技能原文 · 版本 a1c4c98 · 表述以原文为准
它做什么

装上后,Claude 能根据你提供的产品图片和描述,生成模特穿着或使用该产品的 UGC 风格生活照,并进一步优化成更自然的社交平台内容。

什么时候触发

当你提到“UGC”、“试穿”、“生活照”等关键词,或要求生成产品穿搭/使用场景照片时触发。

装好后可以这样说
会使用默认模特和场景生成试穿照。
需上传产品图片,指定场景。
会建议用 kling-v3.0 生成视频。
技能原文 SKILL.md作者撰写 · MIT · a1c4c98

UGC Lifestyle Try-On

Generate UGC-style (User Generated Content) lifestyle photos of a person wearing or using your product — authentic, relatable, social-media-native imagery.

Inputs

| Name | Type | Required | Default | Description | |:---|:---|:---|:---|:---| | product_name | text | yes | — | The product to feature (e.g. "white oversized hoodie", "blue light blocking glasses", "leather crossbody bag"). | | product_image | image_url | yes | — | Product image or photo URL to use as reference for the try-on. | | model_description | text | no | woman, 25-30 years old, natural look, diverse | Description of the model (e.g. "man, athletic build, 20s", "woman, curvy, 30s, warm skin tone"). | | setting | text | no | casual lifestyle, natural lighting | Scene and mood (e.g. "urban street style", "cozy home morning routine", "gym workout", "coffee shop"). | | platform | text | no | instagram | Target platform — "instagram", "tiktok", "pinterest", "amazon". |

Steps

Submit the plan with TWO steps:

Step 1 — Outfit/Product Try-On
  1. Try-on generationmuapi image edit (model=ai-dress-change) if product is wearable clothing, otherwise muapi image edit (model=flux-kontext-pro-i2i):
  2. For clothing/wearables with ai-dress-change:
  3. Product: {{product_image}}
  4. Prompt: {{model_description}} wearing the product naturally in a {{setting}} environment. Authentic UGC-style photo, candid pose, natural expression.
  5. For accessories/non-clothing with flux-kontext-pro-i2i:
  6. Prompt: {{model_description}} using/wearing {{product_name}} in a {{setting}}. The product from the reference image is clearly visible and featured. Natural UGC-style lifestyle photography, authentic candid feel.
  7. Aspect ratio: 4:5 for Instagram, 9:16 for TikTok, 2:3 for Pinterest
Step 2 — UGC Lifestyle Variant
  1. Lifestyle context shotmuapi image edit (model=gpt4o-edit) using the output from Step 1:
  2. Prompt: Make this look like authentic UGC content — add realistic environment context for {{setting}}, adjust lighting to feel natural and unposed, subtle film grain, candid photography style. Keep product {{product_name}} clearly visible and well-lit.

After generation:

  • Present both the try-on and lifestyle variant
  • Offer to generate a 3-image carousel set with different poses/settings
  • Suggest adding a short UGC-style video with kling-v3.0-pro-image-to-video
Notes
  • UGC performs best when it looks "accidental" — avoid overly polished or symmetrical compositions.
  • For TikTok/Reels, suggest animating the best static shot into a video.
  • For Amazon, refer back to the amazon-product-listing skill for white-background variants.
Trigger Keywords

ugc, try on, lifestyle photo, model wearing, outfit photo, wear product, user generated, ugc content, lifestyle try on


Notes for the Executing Agent
  • This recipe is LLM-orchestrated: read each phase, gather any missing inputs from the user, then call muapi CLI commands. Use muapi auth configure first if MUAPI_API_KEY is unset.
  • For model IDs without a CLI alias yet, fall back to the raw endpoint via curl -X POST https://api.muapi.ai/api/v1/<endpoint> -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait <request_id>.
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

评论

登录即可评论;带「已验证安装」的,是发布者名下有本店的安装或持有记录。