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

The description discloses the core selection behavior (column matches any value) and ordering (in the order given). Since no annotations are provided, it carries the burden of transparency; it does not address edge cases like missing values, duplicate matches, or case sensitivity, but the primary behavior is clear.

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 sentence with no filler. It front-loads the action (returns rows) and includes the key ordering and usage details.

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?

The description covers what the tool returns, the filtering logic, and the intended scenario. It does not describe the output format or error behavior, but the title and name cover the side-by-side comparison aspect. For a simple two-parameter tool without output schema, it is reasonably complete.

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 description explains both parameters implicitly: 'column' is the field to match on, and 'values' are the set of values to filter by. Since schema description coverage is 0%, this semantic context is valuable, though it doesn't explicitly mention that values is an array.

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 Recallvia dataset filtered by a column matching any of the given values, in the order provided. This distinguishes it from sibling tools like dataset_row (single row) and dataset_search (search across columns), though it doesn't explicitly name them.

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?

It provides the intended use case 'for X vs Y questions', which signals comparison scenarios, but it does not explicitly describe when not to use it or name alternative tools. The context is clear but not exhaustive.

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