datasets_goodreads_books_search

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

With no annotations, the description carries the full burden of behavioral disclosure. It honestly discloses the dataset's provenance and non-exhaustive nature ('crawled public catalog', 'not a full catalog'), which is valuable. It also lists sort options. However, it does not explicitly mention that this is a read-only operation, return format, pagination behavior, or any other operational quirks beyond what the schema already implies. It adds some context but leaves many behaviors undisclosed.

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: two sentences plus a sort list. It front-loads the core purpose in the first sentence and uses the second to add important context about data source and limitations. The sort enum feels slightly redundant with the schema but is still a useful inline reference. Overall, it is well-structured without wasted words.

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?

Given 20 parameters, full schema coverage, and no output schema, the description provides the essential purpose and data source context. However, it lacks some context that would help an agent fully understand the tool, such as the output shape, examples, or relationship to other dataset tools (e.g., facets, item). It is adequate but not richly complete for a high-complexity 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?

The schema provides 100% parameter coverage with descriptive text for all 20 parameters, so the baseline is 3. The description's only parameter-related addition is repeating the sort enum, which is already fully documented in the schema. There is no extra semantic value added for parameters, so it stays at the baseline without earning a higher score.

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 clearly states the tool searches a Goodreads books dataset, specifying the crawled public catalog in a search index and noting it is not a full catalog. This provides a specific verb (search), resource (Goodreads books dataset), and scope (partial crawled catalog), but it does not explicitly contrast with sibling tools like goodreads_search or datasets_goodreads_books_item, so it stops short of a 5.

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 implies usage by defining the dataset source and limitation ('not a full catalog'), which suggests when to use this tool (search this crawled dataset) and hints that it may not suffice for full catalog needs. However, it gives no explicit when-to-use/when-not-to-use guidance or alternatives, so it relies on implication rather than clear direction.

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