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

No annotations are provided, so the description carries the behavioral burden. It usefully discloses that rows are selected by matching a column against given values and that ordering follows the provided value order. However, it says nothing about behavior when no rows match, case sensitivity, duplicate values, or the shape of the returned comparison.

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 sentence that packs the selection logic, ordering rule, and intended use case without any filler. It is front-loaded with the main behavior and ends with the purpose clause, making it maximally scannable.

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?

For a simple two-parameter read-style tool with no output schema, the description provides the essential invocation facts: what is returned (rows), how they are filtered, and in what order. It omits edge-case behavior and response formatting, but these are less critical given the low complexity and the visual title 'Compare rows side by side'.

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 input schema has no descriptions for `column` or `values`, and schema description coverage is 0%, so the description must compensate. It does so by clarifying that `column` is the attribute to match and `values` are the accepted values, and it adds the important semantic that values are considered in the given order. This adds real meaning beyond the bare type constraints.

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 states a clear functional behavior: it returns rows of the Mustvo dataset whose column matches any of the supplied values, in the supplied order. It also frames the use case as 'X vs Y' questions, which helps distinguish it from more general row/search/stats tools, though it does not explicitly name those siblings.

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 a clear, concrete context for when to use this tool over alternatives like dataset_row or dataset_search. It does not explicitly list when not to use it or name alternative tools, so it stops short of full exclusionary guidance.

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