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Readme & install
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Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill openclaw/skills --skill fashion-studio- _meta.json284 B
- SKILL.md10.4 KB
Overview
This skill automates end-to-end generation of e-commerce apparel product pages, from model casting to final multi-page detail layouts. It produces model images, outfit mockups, and an 8-page detail-page set using image-generation models and structured subagent workflows. The skill enforces structured user choices and automated error handling for reliable outputs.
How this skill works
Users upload core garment and logo images (uploaded to a public image host) and provide model preferences or choose a default template. The system delegates text tasks to read-only subagents to produce casting plans, English prompts, outfit concepts, and page prompts, then calls an image model to generate model photos, outfit renders, and eight detail-page images. Structured AskQuestion interactions collect discrete user choices at key steps and retries handle generation failures.
When to use it
- Creating full e-commerce detail pages from a single garment photo and brand logo.
- Rapidly producing multiple model styles and outfit variants for A/B testing.
- Generating commercial studio-style product hero and lookbook images.
- When you need repeatable, auditable image-generation workflows for product listings.
- Teams that require structured decision points and traceable subagent outputs.
Best practices
- Prepare clean high-resolution garment and logo images and upload them to a public file host before starting.
- Use the default model template for speed, or provide concise custom model attributes (age, ethnicity, hair, vibe).
- Keep image-generation prompts focused and avoid excessive length; iterate up to three retries on failures.
- Respond to AskQuestion choices to keep workflow deterministic and reduce ambiguous inputs.
- Review design-analysis Q&A output before generating detail pages to ensure brand alignment.
Example use cases
- A direct-to-consumer brand needs an 8-page product detail layout and multiple hero images for a new tee.
- A marketplace seller wants two outfit variants photographed on different model styles for conversion testing.
- A creative director needs translated English prompts and consistent studio-style images from native-language briefs.
- An agency producing catalog pages at scale with repeatable subagent steps and structured approvals.
FAQ
You need a core garment image, a brand logo, and either default or custom model attributes (age, gender, ethnicity, features).
How are user choices collected?
The workflow uses structured AskQuestion interactions at model selection, model-image selection, and outfit selection to capture discrete decisions.
What happens if image generation fails?
The skill checks common causes, adjusts prompts and retries up to three times, and asks whether to switch to a fallback plan if failures persist.