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

Annotations already declare readOnly, idempotent, non-destructive, closed-world, so the safety profile is covered. The description adds real behavioral context beyond that: hybrid retrieval, bilingual query support, and the shape of each result (prompt + recommended model). It omits ranking/pagination behavior, keeping it below 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?

Two dense sentences with zero filler; the scale and search mode are front-loaded, and the follow-up action is stated last where it is most actionable.

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?

With no output schema, the description usefully characterizes the return value (ready-to-use prompt plus recommended model). The only gap is the undocumented 'limit' parameter and result-count behavior, which is minor for a search tool.

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 only 33%, so the description must compensate. It adds meaning for 'query' (Russian or English accepted) and media_type is documented in the schema, but 'limit' is never explained in either place. Partial compensation justifies the baseline 3.

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?

States a specific verb and resource ('Search 3500+ curated prompt templates') plus the retrieval method (hybrid text+semantic) and language scope. An agent can immediately distinguish this from siblings like generate_image or list_models.

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?

Explicitly tells the agent what to do with results ('pass them to generate_image/generate_video'), which is a strong downstream routing hint. It stops short of saying when to search versus calling a generator directly with a hand-written prompt, so it is clear context without full exclusions.

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