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

With no annotations provided, the description carries full burden for behavioral disclosure. It explains the selection and ordering behavior but does not mention whether the operation is read-only, has side effects, or any limitations (e.g., result size, error conditions). This lack of safety/behavioral detail is a gap.

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, concise sentence that packs essential information: dataset, filtering logic, ordering, and use case. No redundant words or unnecessary detail, making it highly efficient.

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?

Although there is no output schema, the description clearly states that rows are returned in the given order, which implies the output is a set/array of rows. This is sufficient for the tool's simple purpose, and no further explanation of return structure is needed given the context.

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 covers all parameters (column and values) at 100% coverage, providing type and constraints. The description adds meaning by explaining that 'column' is the field to match against and 'values' are the allowed values, reinforcing the schema. Baseline of 3 is appropriate since no further detail is necessary.

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 title 'Compare rows side by side' and description clearly state the tool's purpose: selecting rows from the Sbarvo dataset based on a column matching any of the given values, ordered as provided. It explicitly mentions the use case 'for X vs Y questions', distinguishing it from sibling tools like dataset_search or dataset_row.

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 indicates when to use this tool ('for X vs Y questions') and specifies the behavior of returning rows in the given order. While it does not explicitly name alternative tools, the context implies this is for comparing specific values, which is sufficient guidance.

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