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

Annotations already declare readOnly, idempotent, non-destructive and closed-world behavior, so the description only needs to add context. It does so by stating the response includes the true total for the filters, letting the agent distinguish a narrow result from an empty library. It says nothing about ordering, pagination beyond the schema's limit, or match-scoring behavior.

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, front-loaded with the resource and the operation, then filter composition, then the example and return semantics. No filler and nothing repeated from the schema verbatim.

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 full schema coverage, annotations and an output schema present, the description carries only what structure cannot: the total-count semantics and a usage example. Missing is any word on result ordering or how it differs from recommend_titles, which is the main ambiguity for an agent choosing among siblings.

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 every parameter is already documented in the schema, including the age range match and the audio-only flag. The description enumerates the same filter set (query, age, topic, language, audio availability) without adding syntax, precedence, or behavior when filters conflict, so the baseline of 3 applies.

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 a specific verb (search) against a clearly named resource (the Vooks library of animated read-along storybooks, audiobooks and ebooks for children) and lists the filter dimensions. It does not explicitly distinguish itself from the closest sibling, recommend_titles, which an agent could reasonably confuse with a discovery-by-filter tool.

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?

It gives a concrete use case ('what should a five-year-old who likes dinosaurs watch') and explains that filters are combined, which tells the agent when this tool fits. It stops short of explicit exclusions or naming alternatives such as recommend_titles or list_topics.

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