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

With no annotations, the description carries the burden of explaining behavior. It usefully discloses that rows are filtered by column match and ordered by the given values, but it does not describe the output structure, handling of missing values, exact matching semantics, or whether the tool merely returns rows or actually renders them side by side.

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 a single, tight sentence that front-loads the core behavior and ends with a practical use case. There is no redundant phrasing or filler.

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?

The tool is simple with only two required parameters, and the description covers the selection logic. However, without an output schema or annotations, more detail about the return format, exact-match behavior, and edge cases (e.g., values not found, duplicate values) would make the description fully complete.

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 0%, so the description must compensate. It does: 'column' is the field used to match, and 'values' are the comparison values; the phrase 'in the order given' adds important semantic meaning for the values array. Minor details like case sensitivity and column existence are not addressed, but the core meaning of both parameters is clear.

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 operation: retrieve rows from the DoorsetBook dataset filtered by a column matching any of the given values, in a specified order. This distinguishes it from siblings like dataset_row, dataset_search, and dataset_top by describing a precise selection and ordering behavior.

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 explicit 'for "X vs Y" questions' provides a clear intended use case. It does not name sibling alternatives or state when not to use the tool, but the context is clear enough for an agent to select it appropriately.

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