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

With no annotations, the description carries the full burden. It discloses two behavioral traits: filtering by column values and preserving the order of the values. However, it does not mention exact-match semantics, case sensitivity, handling of missing values, or whether the full rows are returned. This is partial transparency for a read-only operation.

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, focused sentence that states the core function and the specific use case. No wasted words; it is front-loaded with the operation and includes the key ordering 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 simple, two-parameter retrieval tool, the description is mostly complete. It explains what rows are returned and in what order. It lacks explicit notes on edge cases or output shape, but those are less critical given the straightforward nature and the absence of an output schema is partially mitigated by the phrase 'rows side by side'.

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 explains the relationship between 'column' and the 'given values' and adds that output order follows the values array. It does not explicitly name the parameters or describe constraints, but the simple schema already provides clear property names and types, so the added value is moderate.

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 the tool's function: retrieving rows from the Duesvo dataset where the specified column matches any of the given values, preserving the given order. The 'X vs Y' phrasing helps differentiate it from sibling tools like dataset_row or dataset_top, though the exact comparison presentation is not detailed.

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 states the intended use case ('for X vs Y questions'), giving clear context for when to choose this tool. It does not explicitly name alternatives or exclusions, but the scenario is specific enough that an agent can infer its niche among siblings.

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