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

With no annotations, the description carries the behavioral burden. It does disclose important behavior: rows are selected by 'any of' matching and returned in the provided value order. However, it does not explain exact-match semantics, side-by-side formatting, empty-result behavior, or whether output is limited in any way.

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, focused sentence conveys the core operation and purpose with no redundant content. The key selection and ordering behavior appears early, and the use-case hint is appended cleanly.

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 tool with no output schema and no annotations, the description covers the core invocation need: what rows are returned, how they are filtered, and in what order. Minor gaps remain around exact matching behavior and the visual 'side by side' presentation, but these are not blocking for correct use.

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 has 0% description coverage, so the description must add parameter meaning. It does: 'column' is the field used for filtering, and 'values' are the matching values whose order also determines output order. This is sufficient for the two simple parameters, though it omits details like allowed column names or case sensitivity.

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 identifies the resource (rows of the Eobify dataset), the selection mechanism (column matching any of the given values), and the output ordering (order given). It also conveys the intended use case ('X vs Y' questions), but it does not explicitly differentiate from sibling tools like dataset_row or dataset_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' implies when the tool is appropriate, but the description never names alternative tools or states when not to use it. Given several sibling tools exist, more explicit routing would strengthen this dimension.

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