MeiGen AI Design MCP

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

The annotation declares readOnlyHint=true, and the description adds valuable behavioral context by disclosing that return data includes 'pricing and capabilities'—critical information for model selection that is not present in the structured fields.

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?

Single sentence of nine words with zero waste. Front-loaded with verb, immediately qualifying the scope (AI image generation), and ending with specific return attributes (pricing and capabilities).

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 low complexity (1 optional param, read-only), no output schema, and clear sibling context, the description is complete. It compensates for missing output schema by specifying return content (pricing/capabilities).

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?

With 100% schema description coverage for the 'activeOnly' parameter, the baseline is 3. The description does not explicitly reference the parameter or explain filtering semantics beyond the word 'available', but the schema carries the full burden adequately.

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 specific verb 'List' with clear resource 'AI image generation models' and distinguishes from siblings like 'generate_image' and 'comfyui_workflow' by focusing on discovery/inspection rather than execution or workflow management.

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?

While the purpose is clear, there is no explicit guidance on when to use this versus alternatives, or that it should be called before 'generate_image' to select valid model IDs. Usage is implied but not stated.

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