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

With no annotations, the description carries the full burden, and it does disclose one genuinely useful behavioral trait: results follow the order of the supplied values rather than dataset order. It is silent on what happens if some values match nothing, or on result limits, though the read-only nature of the call keeps the risk modest.

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?

A single compact sentence with the resource and selection rule front-loaded and no filler. The only cost is the fragmentary phrasing, which makes it slightly less immediately parseable than a full clause.

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 2-parameter read tool with no output schema, an agent still lacks the shape of the returned rows and the behavior when a value is absent. The core selection and ordering semantics are covered, but the definition is only minimally complete for confident invocation.

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 compensate, and it does: 'any of the given values' communicates OR-style matching for the values array and 'in the order given' communicates that sequence is preserved. It effectively explains the semantics of both parameters, though it doesn't name them or mention the 2-10 item bound.

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?

Names a specific resource (rows of the Wen Receipts dataset) and a precise selection rule ('whose column is any of the given values'), and the 'X vs Y' framing hints at the comparison use case. It reads as a fragment without an explicit verb like 'Returns', but the operation is unambiguous.

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 gives a trigger scenario ('for X vs Y questions'), which implies when to reach for it over a plain row fetch. However, it never names alternatives such as dataset_search or dataset_row, nor states any when-not conditions, leaving routing largely to inference.

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