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YouCam for Beauty & Personal Care

Ai Fitzpatrick Skin Type Analysis Detection

AI-Fitzpatrick-Skin-Type-Analysis-Detection
Read-only

Run an AI Fitzpatrick Scale Analyzer detection task.

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

C2.7/5.0
Behavior2/5

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

The description adds no behavioral context beyond the annotations. It does not disclose the async task-based workflow, the polling behavior, or the requirement for a publicly accessible file URL/ID. With readOnlyHint and destructiveHint already provided, the description misses the chance to explain what the detection task entails.

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

Conciseness4/5

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

The description is a single, front-loaded sentence with no redundant words, making it structurally concise. However, its extreme terseness sacrifices substance, though the structure itself is acceptable.

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

Completeness2/5

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

The tool has moderate complexity (task-based with polling, two request modes) and an output schema, but the description provides no context about the invocation workflow or how polling affects results. It is incomplete for an agent to fully understand the tool's operation.

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?

Schema description coverage is 50%, but the description does not compensate by explaining parameters like 'polling' or the request object's alternatives (src_file_url vs src_file_id). It adds no meaning beyond what the schema already provides.

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

Purpose4/5

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

The description clearly states the verb 'run' and the resource 'AI Fitzpatrick Scale Analyzer detection task', identifying a specific function. However, it does not explicitly distinguish from sibling tools like 'AI-Fitzpatrick-Skin-Type-Analysis', which may serve a similar purpose.

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

Usage Guidelines2/5

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

There is no guidance on when to use this tool versus alternatives, nor any mention of prerequisites such as needing a source file or when to enable polling. The description lacks context for selecting the appropriate tool among many similar detection/analysis tools.

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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