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

With no annotations provided, the description carries the full burden of behavioral disclosure. It usefully explains that rows are selected by matching any of the given values and that the result order follows the order of the provided values. It does not describe error behavior, exact-match semantics, or whether rows are deduplicated, but the core selection and ordering behavior is transparent.

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, compact sentence that conveys the filtering rule, ordering behavior, and intended use case. Every phrase earns its place and there is no redundant or vague filler.

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 tool with only two scalar parameters and no output schema, the description is largely sufficient: it states what rows are returned and in what order. It could be more complete by clarifying whether matching is exact or case-sensitive, and what happens when no rows match, but the core calling context is well covered.

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 for both parameters. It does: 'column' is the field to match against, and 'values' are the candidate values that also determine output ordering. This adds meaningful semantic context beyond the bare schema.

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 states that the tool returns rows from the Consentvia dataset filtered by a column matching any of the provided values, in the given order. It is distinct from sibling tools like dataset_row or dataset_search because it targets multi-row comparison scenarios, though it lacks an explicit action verb like 'returns' or 'compares'.

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 usage context, indicating this tool is for comparing specific rows side by side. However, it does not explicitly mention when to prefer this over sibling tools such as dataset_search or dataset_row, leaving the differentiation to inference.

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