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Muapi Ugc Lifestyle Try On

skill-samuraigpt-generative-media-skills-ugc-lifestyle-try-on · by SamurAIGPT

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

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Install

$ agentstack add skill-samuraigpt-generative-media-skills-ugc-lifestyle-try-on

✓ scanned · ✓ verified, works with Claude Code, Cursor, and more.

Security review

✓ Passed

No issues found. Passed automated security review. · v0.1.0 How review works →

  • Prompt-injection patterns
  • Secret / credential exfiltration
  • Dangerous shell & filesystem operations
  • Untrusted network calls
  • Known-malicious package signatures

What it can access

  • Network access Used
  • Filesystem access No
  • Shell / process execution No
  • Environment & secrets No
  • Dynamic code execution No

From automated source analysis of v0.1.0. “Used” means the capability is present in the source — more access means more to trust, not that it’s unsafe.

View the full security report →

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Reliability & compatibility

Security review passed
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3mo ago

Declared compatibility

Claude CodeClaude Desktop

Compatibility is declared by the source manifest. End-to-end runtime verification is coming, see below.

Preview Execution monitoring

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About

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):
  • 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.
  • 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.
  • 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:
  • 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/ -H "x-api-key: $MUAPI_API_KEY" -H 'content-type: application/json' -d '{...}' and poll with muapi predict wait .
  • Substitute {{input_name}} placeholders with the user's actual inputs before issuing each call.

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

Install and usage instructions live in the source repository linked above.

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Versions

  • v0.1.0 Imported from the upstream source.