Ai Fabric Virtual Try On Templates
AI-Fabric-Virtual-Try-On-TemplatesList predefined templates.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Output Schema
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
AI-Fabric-Virtual-Try-On-TemplatesList predefined templates.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The annotations (readOnlyHint, idempotentHint, destructiveHint) already establish that this is a safe, non-destructive read operation. The description adds no additional behavioral context, such as what the templates represent or how they are used, but it is consistent with the annotations and does not contradict them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, concise sentence with no filler or redundant information. It is front-loaded with the core verb and object, making it immediately parseable by an AI agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is adequate for a simple list operation, and the presence of an output schema covers return values. However, it lacks context about how this tool relates to sibling virtual try-on tools, specifically that the templates are likely inputs for those operations. A more explicit connection would enhance completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, and the schema confirms this with 100% coverage. The description does not need to explain any parameters since none exist, and the baseline score for zero-parameter tools is 4.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and resource 'predefined templates,' clearly indicating a read-only enumeration operation. It distinguishes from sibling try-on tools which perform actions rather than list templates, though the description itself does not explicitly mention 'fabric' or the domain context beyond the tool name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives, such as other try-on tools or discovery methods. There is no mention of typical workflows, prerequisites, or exclusions, leaving the agent to infer usage solely from the tool name and the fact that it lists templates.
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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