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

With no annotations, the description carries the behavioral burden. It discloses the core selection logic (column value membership) and the non-default behavior that results are returned in the order the values were given. It does not mention edge cases such as matches not found or exact/case-sensitive matching, but the read/comparison nature 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?

The description is a single dense sentence that front-loads the result and appends the use case, with no redundant words. The wording 'whose column is any of the given values' is grammatically awkward but still efficient.

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 two-parameter read tool with no output schema, the description covers the query logic and intended use, but omits what the returned rows look like, the matching precision, and behavior for empty or partial results. This is adequate for invoking the tool but leaves interpretation of results somewhat underspecified.

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 coverage is 0%, so the description must explain the parameters. It links 'column' to the field being matched and 'given values' to the value list, and adds the ordering semantics tied to the values parameter. It does not explicitly name the parameters or describe constraints like maxItems, which remain only in the 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 identifies the tool's function as returning dataset rows filtered by a given column matching any of the supplied values, with order preservation. Although phrased as a noun phrase rather than an explicit verb, it clearly distinguishes from siblings like dataset_search and dataset_row via the 'X vs Y' comparison intent.

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' tells the agent when this tool is appropriate: comparing two or more specific rows. It does not explicitly name sibling tools as alternatives, but the visible sibling list plus the targeted use case provide adequate context.

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