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Ai Face Reshape Detection

AI-Face-Reshape-Detection
Read-only

Run an AI Face Reshape 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

D1.8/5.0
Behavior2/5

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

Annotations declare readOnlyHint, openWorldHint, and destructiveHint=false, but the description adds no behavioral context beyond that. It does not mention the polling parameter, file input requirements, or task lifecycle, so the agent cannot anticipate asynchronous behavior or expected outputs.

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 description is a single short sentence with no wasted words, but it is under-specified to the point of being uninformative. Conciseness without substantive content is not a strength.

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 and annotations, the tool description is inadequate for safe invocation. It omits core context such as what the detection result contains, how to provide input files, and how polling works, making it incomplete for an agent operating among many similar 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 input schema covers 50% of parameters, but the description adds no parameter-related meaning. It does not explain the 'request' anyOf structure, the difference between src_file_url and src_file_id, or the polling flag, leaving the agent to rely solely on the schema.

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 restates the tool title ('AI Face Reshape detection task') with the generic verb 'Run', so it is essentially a tautology. It does not explain what a 'detection task' actually does or how it differs from sibling tools like AI-Face-Reshape or AI-Body-Reshape-Detection.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. With dozens of similar sibling tools, the agent receives no decision support at all.

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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