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

No annotations are provided, so the description must carry the full behavioral disclosure. It does disclose that rows are returned in the order of the given values, which is a useful trait. However, it does not specify what columns are returned, whether it is a read-only operation (though obvious), or how missing values are handled, leaving some ambiguity for an agent without an output schema.

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 sentence that conveys the core behavior without redundancy. It front-loads the main action and includes the order detail, which is essential. While the phrasing could be more polished, it is efficient and free of extraneous content.

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 tool is simple (two parameters, no output schema), so the description must be self-sufficient. It explains the filtering and ordering but does not describe the return format (e.g., whether it returns full rows or a subset of columns). It also omits edge-case behavior such as what happens when no rows match. This is a moderate gap for an agent expected to call the tool correctly without additional context.

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 schema has zero description coverage, so the description must explain the parameters. It does: 'column' is the field to match, 'values' are the list of acceptable values, and the order of the values determines the order of returned rows. This effectively compensates for the lack of schema descriptions, providing clear semantics for both parameters.

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 retrieves rows from the Reviewvo dataset filtered by a column matching any of the provided values, preserving the given order. The phrase 'for "X vs Y" questions' signals its comparative intent, distinguishing it from generic search or single-row retrieval tools. While the phrasing is slightly awkward, the purpose is unambiguous and differentiates it from siblings like dataset_search and dataset_row.

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 offers a contextual hint ('for "X vs Y" questions') that implies when to use it, but it does not explicitly name alternative tools or state conditions for when not to use it. There is no mention of how it relates to dataset_row, dataset_search, or dataset_top, leaving the agent to infer the intended usage scenario. This is adequate but not explicit guidance.

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