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

The description discloses meaningful behavior: rows are returned in the order of the given values, and filtering is by 'any of' those values. However, since no annotations and no output schema exist, the description carries the full burden and does not clarify what the returned comparison actually looks like, whether matches are exact, or how edge cases are handled.

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 compact sentence and front-loads the resource and core filtering behavior. The grammar is slightly awkward and the 'X vs Y' purpose is placed at the end, which is acceptable but not ideal.

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, the core selection and ordering semantics are covered, which is enough to make a plausible first call. However, with no annotations and no output schema, the description should also clarify the return representation and handling of absent matches or duplicate values to be fully 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?

Schema description coverage is 0%, so the description must compensate for the schema's lack of semantic detail. It does clarify that 'column' refers to a dataset column and 'values' are the matching values whose order determines output order. It does not explain value formatting, matching behavior, or maximum constraints beyond what the schema already states.

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 a specific operation: fetching rows of the Siftvo dataset filtered by a column matching any of the given values, in the provided order. It also links the behavior to 'X vs Y' comparison questions, which helps an agent understand its intended role. It does not explicitly contrast this with sibling tools like dataset_row or dataset_search, so it falls short of a 5.

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 explicit use case for when this tool is appropriate. It implies comparison of specific values rather than general exploration or statistics, but it does not state when not to use it or name alternative sibling tools.

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