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 does mention that rows are returned 'in the order given', which is a behavioral trait, but it does not state whether rows are returned in full, how results are paginated, or any side effects (though likely read-only). It lacks details on output format and error handling, which is a significant gap for a tool with no annotations.

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, front-loaded sentence that states the core behavior and use case without unnecessary words. It is concise and efficient, though it could be slightly clearer about the comparison aspect. Overall, it is well-structured and avoids fluff.

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?

Given the tool has no output schema and no annotations, the description is the only source of context. It covers the filtering and ordering logic, but does not describe what the returned rows contain (e.g., all columns or just the compared column), pagination, or any prerequisites. For an agent to correctly interpret the result, more detail is needed.

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 explains that 'column' is the column to filter on and 'values' are the values to match, and that the order of values determines the order of rows. However, it does not elaborate on constraints like min/max length or the array nature, which are already in the schema. It adds some meaning but not exhaustive.

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 the tool selects rows whose column matches any of the given values, preserving the given order, and is aimed at 'X vs Y' comparisons. This distinguishes it from sibling tools like dataset_row (single row) or dataset_search (general search). It is specific about the operation and resource, though it could be more explicit about the side-by-side comparison aspect.

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 description gives a clear use case ('for X vs Y questions'), which implies when this tool is appropriate, but it does not explicitly mention alternatives or when not to use it. There is no comparison to siblings like dataset_search or dataset_top, so the guidance is implied rather than explicit.

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