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YouCam for Beauty & Personal Care

Ai Face Lift Detection

AI-Face-Lift-Detection
Read-only

Run an AI Face Lift 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

C2/5.0
Behavior2/5

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

Annotations indicate readOnlyHint and destructiveHint false, which already cover safety. However, the description adds no behavioral context beyond 'run a task'—no mention of polling, return behavior, or what happens after detection. It fails to disclose any non-obvious traits.

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

Conciseness2/5

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

The single sentence is concise but under-specified. It does not earn its place because it merely repeats the tool name without adding useful information. True conciseness would still convey purpose and context, which this misses.

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?

Despite having an output schema, the description is incomplete for a tool with a non-trivial request structure (anyOf URLs or IDs) and polling options. It fails to explain what the detection task actually does, leaving the agent to guess at the tool's role among many similar face-analysis tools.

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 says nothing about parameters. Schema coverage is 50% (polling has a description, but request lacks a top-level description). With half the schema undocumented and zero param info in the description, the tool fails to compensate for the gap.

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 'Run an AI Face Lift detection task' essentially restates the tool name without explaining what the detection task does or how it differs from sibling tools like AI-Face-Lift. It lacks specific scope or output details, making it tautological.

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?

The description provides no guidance on when to use this tool versus alternatives. It does not mention any prerequisites, exclusions, or distinguish from AI-Face-Lift, which is a likely sibling for similar tasks.

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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