trident-mcp

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key traits: it's an async operation (clarifying execution model), mentions polling and result retrieval workflows, and implies quality improvement over single-image methods. However, it doesn't cover potential limitations like error conditions, rate limits, or authentication needs, leaving some behavioral aspects unspecified.

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 highly concise and well-structured in three sentences: first states the core functionality, second provides quality comparison, third explains async workflow. Every sentence adds critical information without redundancy, making it front-loaded and efficient.

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 (async 3D generation), the description is complete enough. It covers purpose, usage context, behavioral aspects (async nature), and references sibling tools for follow-up. With 100% schema coverage and an output schema present, the description appropriately focuses on operational context rather than repeating parameter or return value details.

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 100%, so the schema fully documents all 4 parameters. The description adds no additional parameter semantics beyond what's in the schema (e.g., no extra details on image format, angle requirements, or model version specifics). Baseline 3 is appropriate when the schema handles parameter documentation completely.

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 specific action ('Generate a 3D model'), resource ('from 2-4 reference images'), and key constraint ('taken from different angles'). It explicitly distinguishes from sibling 'image_to_3d' by noting 'significantly better geometry than single-image input,' establishing a clear differentiation.

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 explicit guidance on when to use this tool ('from 2-4 reference images taken from different angles') and when not to use it ('better geometry than single-image input' implies 'image_to_3d' is for single images). It also names specific alternatives for related operations ('use task_status to poll progress and download_model to retrieve the result'), covering both when-to-use and follow-up actions.

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