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

No annotations are provided, and the description does not state whether the operation is read-only, whether it returns full rows, or whether there are any limits beyond the schema constraints. The description implies a query operation but leaves important behavioral details unstated.

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 and avoids extraneous detail, fitting the intended purpose into a single sentence. The phrasing is slightly awkward but remains understandable and focused.

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 and no detail about return shape, ordering, or error behavior, the description is incomplete for an agent that needs to know what result to expect. It explains the selection logic but not the full contract of the 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 no parameter descriptions, and the description only loosely maps 'column' and 'values' by saying rows match 'any of the given values'. It does not clarify whether values are exact strings, how column names are specified, or how ordering by the given values is handled.

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 indicates that the tool retrieves rows matching given values in a specified column and frames this as supporting 'X vs Y' comparisons. The title reinforces the side-by-side comparison intent, distinguishing it from simple row retrieval or search.

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 phrase 'for X vs Y questions' gives some usage context, and the sibling tool names suggest alternatives. However, it does not explicitly state when to prefer this tool over dataset_search or dataset_row, nor does it describe matching semantics such as exact match or case sensitivity.

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