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

Annotations already declare readOnlyHint=true, openWorldHint=false and destructiveHint=false, so safety is covered; the description adds real behavioral value by naming the return payload (prompt text, model, result media, run link), which matters since no output schema exists. It stops short of describing result ordering, pagination, or whether results are cached/indexed, so it is not fully transparent.

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, each earning its place: purpose, routing rule, return shape. The corpus definition is front-loaded and there is no redundant restatement of the name or schema.

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 compensates by summarizing the returned fields and by pointing to the sibling for the trending case. For a simple three-parameter read tool this is nearly complete; only result ordering and any rate/indexing caveats are unaddressed.

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%, so query, kind, and limit are already documented in the schema, making 3 the baseline. The description only loosely echoes the query semantics ('style/subject/model lookups') and says nothing about the kind enum values or the limit ceiling beyond what the schema states.

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 ('Keyword search over the community prompt library') and immediately scopes the corpus ('tested AI image and video prompts with the results they produced'). It explicitly distinguishes itself from the sibling trending_prompts, so the agent can route without opening either schema.

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?

Gives positive guidance ('Use for style/subject/model lookups') and an explicit exclusion with the alternative named ('For trending or most-used prompts call trending_prompts instead'). Both the when and the when-not are stated rather than inferred.

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