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

No annotations are provided, so the description carries the full behavioral burden. It states that rows are returned and that values are ordered, but does not describe read-only behavior, return format, how side-by-side comparison is represented, permissions, or pagination.

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 short and contains no filler, but it is structurally awkward as a fragment and uses unexplained jargon like "X vs Y" questions. It is not front-loaded with a clear action or return behavior.

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 tool with no annotations, no output schema, and 0% schema description coverage, the definition is incomplete. It does not explain the expected response shape or enough operational detail for an agent to invoke it confidently.

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 explain the parameters. It identifies a column filter and a values list and mentions ordering, but omits the schema constraints such as minimum/maximum values, matching behavior, valid column names, and whether ordering affects results or only input interpretation.

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 conveys that the tool returns dataset rows filtered by a column matching any of the supplied values, but it is a sentence fragment with no clear verb. It hints at comparison via "X vs Y" questions, yet does not explain how that differs from sibling tools such as 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" gives an implied use case, which is more than nothing. However, there is no explicit guidance on when not to use it or which sibling should be chosen for other row-access patterns.

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