list_models

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

The readOnlyHint annotation already indicates a safe read operation. The description adds valuable behavioral context: the source is the App public model catalog, and with UGCMIND_API_KEY, project-specific overrides may be included, which can affect results. No contradictions with annotations.

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?

Two concise sentences front-load the core purpose and add a relevant caveat. Every word earns its place, with no redundancy or filler.

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?

For a simple read-only list tool with one optional parameter and no output schema, the description is sufficiently complete. It states what is listed and the API key influence. A minor gap is not specifying whether the return includes identifiers or how to use them in generation calls, but this is not critical for basic 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 100%, as the only parameter (activeOnly) is already documented with its purpose and current behavior. The description adds nothing about parameter syntax or meaning, but the schema handles it fully, so the baseline score of 3 is appropriate.

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 uses a specific verb ('List') and identifies the resource ('UGCmind image/video generation model options from the App public model catalog'). It clearly differentiates this tool from sibling generation tools like generate_image and video_generation by focusing on listing model options rather than generating content.

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 implies the tool is for querying available models before generation, and notes that an API key may include project-specific overrides. However, it does not explicitly state when to use this tool versus alternatives, nor does it mention exclusions or prerequisites beyond the API key.

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