muapi-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.
- License 许可
- Apache-2.0
- 最近更新
- 2026-11-11
- Stars
- ★ 1.6k
- Forks
- 474
01 前言 Front Matter
- name
- muapi-ugc-lifestyle-try-on
- slug
- muapi-ugc-lifestyle-try-on
- version
- 1.0.0
- description
- Generate UGC-style (User Generated Content) lifestyle photos of a person wearing or using your product — authentic, relatable, social-media-native imagery.
- acceptLicenseTerms
- true
03 SKILL.md 正文
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 | Target platform — "instagram", "tiktok", "pinterest", "amazon". |
Steps
Submit the plan with TWO steps:
Step 1 — Outfit/Product Try-On
- Try-on generation —
muapi image edit(model=ai-dress-change) if product is wearable clothing, otherwisemuapi image edit(model=flux-kontext-pro-i2i):- For clothing/wearables with
ai-dress-change:- Product:
{{product_image}} - Prompt:
{{model_description}} wearing the product naturally in a {{setting}} environment. Authentic UGC-style photo, candid pose, natural expression.
- Product:
- For accessories/non-clothing with
flux-kontext-pro-i2i:- 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.
- Prompt:
- Aspect ratio: 4:5 for Instagram, 9:16 for TikTok, 2:3 for Pinterest
- For clothing/wearables with
Step 2 — UGC Lifestyle Variant
- Lifestyle context shot —
muapi image edit(model=gpt4o-edit) using the output from Step 1:- 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.
- Prompt:
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-listingskill 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
muapiCLI commands. Usemuapi auth configurefirst ifMUAPI_API_KEYis 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 withmuapi predict wait <request_id>. - Substitute
{{input_name}}placeholders with the user's actual inputs before issuing each call.
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deja-vu memory — search the user's past AI coding sessions with the deja CLI. Holds what they already settled and never wrote into the repo (naming rules, banned or already-tried tools, required checks before merge, preferred values, who owns what). Use before your first edit in a task, before you call a change done or ready to merge, before you recommend a tool, library, design or reviewer, before re-debugging an error that may already be solved, when they say 'didn't we fix this before', 'what did we decide about X' or 'I already have that', and before telling them something on this machine does not exist.
deja-reflect
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