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YouCam for Fashion & Retail

Ai Fabric Virtual Try On

AI-Fabric-Virtual-Try-On

Transform your look with stunning realism! Explore unique fabric styles with photo mode — whether it's the elegance of silky textures or the vibrance of bold prints, the AI Fabric API brings materials to life! Developers can craft immersive experiences that let users see and feel fabrics like never before. Plus, fresh fabric updates are always on the way!

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pollingNoIf true (default), keep polling until the task finishes, returning the final result. If false, return immediately without waiting for the task to finish.
requestYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

D1.4/5.0
Behavior1/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description does not disclose that this is a non-idempotent task-based operation (polling parameter), requires publicly accessible URLs, or any side effects. It only provides promotional content, adding no transparency beyond the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness1/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a verbose marketing paragraph with exclamation marks and imperatives like 'Transform your look!' It fails to front-load the functional purpose and wastes space on 'fresh fabric updates' and 'see and feel fabrics.' Not concise or structurally helpful.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness1/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite having a moderately complex input schema with multiple request variants and polling, the description provides no operational context such as how to obtain templates, file requirements, or async behavior. It is entirely inadequate for correct tool invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description mentions 'photo mode' and 'fabric styles' but never references parameters like template_id, src_file_url, src_file_id, or polling. The input schema already provides descriptions, but the description adds no additional parameter semantics to assist the agent.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose2/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses marketing language like 'Transform your look with stunning realism' and 'Explore unique fabric styles with photo mode' but never explicitly states the tool performs a virtual try-on of fabric on a provided photo using a template. It is vague and doesn't clearly identify the core operation or distinguish it from sibling tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines1/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus sibling tools (e.g., AI-Clothes-Virtual-Try-On) or prerequisites like listing templates or uploading files. There is no mention of when to choose this tool over alternatives.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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