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

Annotations provide readOnlyHint: true, and the description adds value by explaining results include image URLs, suggests rendering as markdown, and describes behavior with empty query (browse) and semantic search. No contradiction, and it enriches the understanding beyond 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?

The description is concise: three sentences front-load the purpose and usage. Every sentence adds value, and there is no redundancy or verbosity.

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?

Despite no output schema, the description covers return value (image URLs) and how to present them. It explains semantic search, browsing use case, and provides context for using the tool alongside siblings like generate_image. Complete for an agent to use correctly.

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 coverage is 100%, so the baseline is 3. The description adds context for the 'query' parameter (supports natural language, leave empty for browse), which goes beyond the schema's description. This justifies a 4.

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 specifies "search" as the verb, "AI image prompts" as the resource, and highlights semantic understanding as the key differentiator from keyword search. It clearly states what the tool does and distinguishes it effectively.

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 explicitly says when to use: when users need inspiration, explore styles, or say 'generate an image' without a specific idea. It implies alternatives like generate_image but does not name them directly, slightly lowering the score.

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