API-Market MCP Server

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

No annotations are provided, so the description carries the full burden. It mentions the tool is an 'API for simulating' and requires a follow-up call, implying it's a two-step asynchronous process. However, it doesn't disclose critical behavioral traits like rate limits, authentication needs, error handling, or what the simulation entails (e.g., whether it modifies the original image). The description is insufficient for a mutation tool with no annotation coverage.

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 two sentences and reasonably concise, but not optimally structured. The first sentence states the purpose, and the second provides a usage note. However, the second sentence could be more integrated, and overall, it lacks front-loading of critical information like parameter guidance. It's adequate but not exemplary.

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?

Given the tool's complexity (AI simulation with 4 parameters), no annotations, and no output schema, the description is incomplete. It doesn't explain the simulation process, output format, error cases, or integration with the follow-up tool. For a tool with rich functionality and no structured support, it should provide more context to be useful.

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 0%, so the description must compensate for all 4 parameters. It adds no meaning beyond the schema—no explanation of what 'color_description', 'editing_type', 'hairstyle_description', or 'image' represent, their formats, or constraints. The description fails to provide any parameter semantics, leaving parameters undocumented.

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 clearly states the tool's purpose: simulating different hair styles using AI models. It specifies the verb ('simulating') and resource ('hair styles'), but doesn't differentiate from siblings like 'ImageFaceSwap' or 'VideoFaceSwap' which might involve similar image manipulation. The purpose is specific but lacks sibling distinction.

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 minimal usage guidance, only stating to call 'get hairstyled image' after receiving a request ID. It doesn't explain when to use this tool versus alternatives like 'ImageFaceSwap' or 'text-to-image', nor does it mention prerequisites or exclusions. No explicit when/when-not guidance is provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.