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 mentions filtering by column values and preserving order, but does not explain whether it returns grouped rows, how multiple matches per value are handled, result ordering within a value, or any access constraints.

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 definition is short and free of filler, but it is structured as an awkward noun phrase rather than a clear action statement. It is not front-loaded with what the tool does, making it harder to parse quickly.

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 no annotations, no output schema, and 0% schema coverage, the description should do more to explain return behavior and comparison mechanics. It leaves the agent without enough information to predict the result shape or call it correctly in edge cases.

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 define the two parameters. It implies that "column" is the column to check and "values" are the values to match, and that order matters, but it does not clarify exact-match versus partial-match behavior, case sensitivity, or value formatting.

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 indicates that the tool retrieves dataset rows where a specified column matches any of the given values and that ordering matters for "X vs Y" questions. However, it is a sentence fragment without a clear verb and does not distinguish this operation from siblings 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 only usage hint is "for 'X vs Y' questions," which implies a comparison scenario but gives no explicit when-not guidance or references to alternative tools. It is enough to infer a narrow use case, but not enough to route confidently among siblings.

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