AI-Body-Reshape-DetectionRun an AI Body Reshape detection task.
| Name | Required | Description | Default |
|---|---|---|---|
| polling | No | If true (default), keep polling until the task finishes, returning the final result. If false, return immediately without waiting for the task to finish. | |
| request | Yes |
| 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?
Annotations already declare readOnlyHint=true and destructiveHint=false, providing the safety profile. The description adds no behavioral context beyond 'run a task', such as whether results are returned as a detection score or whether the task is asynchronous. It does not contradict annotations, so a neutral score is appropriate.
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 redundancy. It is front-loaded with the action and resource, making it easy to scan.
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?
While the schema and annotations provide decent structural and safety coverage, the description alone does not sufficiently explain the tool's role among many similar detection tools. The output schema exists, so return values are covered, but the lack of differentiation and vague 'detection' meaning leaves the context incomplete for optimal agent selection.
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?
Schema description coverage is 50% (only 'polling' has a direct description; 'request' lacks a top-level description although nested fields are described). The description does not add any clarification about the 'request' parameter or the file source options, failing to compensate for the coverage gap.
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 'Run an AI Body Reshape detection task' clearly specifies the verb (run) and resource (AI Body Reshape detection task), making the basic purpose understandable. However, it does not distinguish this detection tool from its sibling 'AI-Body-Reshape', which likely performs the actual modification, so sibling differentiation is lacking.
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?
The description provides no guidance on when to use this tool versus the many sibling detection/reshaping tools. It does not mention use cases, alternatives, or prerequisites, leaving the agent without context for selection.
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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