MeiGen AI Design MCP

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

Substantial value beyond readOnlyHint annotation: discloses that results include image URLs and provides specific rendering instructions ('render them as markdown images'). Also clarifies the semantic search behavior. Does not cover rate limits or pagination details, preventing a 5.

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?

Three sentences with zero waste: defines capability, explains output handling (critical given no output schema), and specifies usage context. Front-loaded with the most important distinction (semantic vs keyword search).

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?

Compensates well for missing output schema by explaining that results contain image URLs and how to display them. Covers primary use cases and search behavior. Could note that all parameters are optional (0 required), but schema structure makes this evident.

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?

Input schema has 100% description coverage (query, category, limit, offset, sortBy all well-documented). The description does not add parameter-specific guidance beyond what's in the schema, meeting the baseline expectation for high-coverage schemas.

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?

Excellent specificity: states the tool 'Search[es] AI image prompts with semantic understanding' and distinguishes its capability from keyword matching. The phrase 'visually and conceptually similar results' precisely defines the search behavior, differentiating it from sibling tools like generate_image or get_inspiration.

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?

Provides explicit when-to-use guidance ('Use when users need inspiration, want to explore styles, or say "generate an image" without a specific idea'), implicitly distinguishing from generate_image. Lacks explicit 'when not to use' or named alternative tools, which would be needed for a perfect score.

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