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

With no annotations, the description must carry behavioral disclosure. It reveals that results are returned in the order of the given values, which is a useful detail. However, it does not specify whether full rows are returned, what happens on no matches, or any side effects. The description is not misleading but lacks depth.

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 function and a usage context. It is concise and front-loaded with the action, though the 'X vs Y' phrase could be clearer to some agents.

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 no annotations and no output schema, the description provides essential parameter semantics and ordering behavior. However, it leaves ambiguity about output structure (e.g., does it return all columns or just the matching values?) and does not address edge cases like empty results or data types beyond what the schema implies.

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 effectively does: 'column' is the field to match, and 'values' are the list of values to filter by, with ordering implied. This adds meaning beyond the raw schema definitions.

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 indicates the tool returns dataset rows filtered by a specified column and matching any of the given values, with a specific ordering. It distinguishes itself from siblings like dataset_row (single row) and dataset_search (general search) by stating it's for 'X vs Y' questions, though it lacks an explicit verb like 'retrieves' or 'lists'.

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?

It provides a usage hint via 'for X vs Y questions', suggesting when it should be used, but does not explicitly mention alternatives or state when not to use it. No clear exclusions or comparisons to sibling tools are provided.

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