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

There are no annotations, so the description carries full burden. It does disclose a genuine behavioral trait — results come back in the order values were given — and the any-of matching semantics. But it does not disclose return format, whether matching is exact or case-sensitive, or how duplicate/absent values are handled.

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?

A single information-dense sentence with no wasted words: it names the resource, parameter roles, ordering behavior, and use case. Everything present earns its place, making it an excellent example of efficient structure.

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 2-parameter tool with no enums or nesting, the essentials for a correct call (parameter roles and ordering) are covered. Yet with no annotations and no output schema, the description should also convey what the result looks like and any matching caveats; those are omitted, leaving moderate gaps.

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 clarify how the two parameters interact: column is the field matched against, values are the list used for any-of matching, in the given order. However, match type (exact vs substring), case sensitivity, and behavior for unmatched values remain unspecified.

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 specifies a concrete behavior: return rows of the Sittingly dataset filtered by matching any given value in a column, preserving the given order. The 'X vs Y questions' framing adds a distinct use case that separates it from siblings like dataset_search or dataset_row, though the verb is implied rather than explicit.

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 'for X vs Y questions' clause signals an intended scenario, which is useful context. However, it never names sibling tools or states when NOT to use them (e.g., when to pick dataset_search or dataset_row instead), leaving routing partly to inference.

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