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

No annotations are provided, so the description carries the full burden. It does disclose meaningful behavior: filtering by column values and returning rows in the given order. However, it does not mention safety characteristics, response format, or how edge cases like duplicate or missing values 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 efficient sentence with no redundant content. It front-loads the result behavior and ends with the use-case context, making the core meaning immediately visible.

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 description covers the core selection and ordering behavior, which is sufficient for a simple two-parameter tool. However, without an output schema or annotations, it omits the response format and edge-case behavior, leaving some context missing for an agent.

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 gives some meaning by relating 'column' to the attribute being matched and 'values' to the set of allowed matches, but it does not explain constraints like minItems/maxItems or what a valid column is, leaving the agent to rely on the schema alone.

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 identifies what the tool does: it selects rows of the Proofzo dataset based on a column matching one of the given values, preserving the given order. It distinguishes its comparison use case ('X vs Y questions') from siblings, though it does not name an alternative explicitly.

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' provides a clear use-case context for when this tool is appropriate. It does not state exclusions or name alternative tools, but the context is strong enough for an agent to infer the intended scenario.

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