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

With no annotations, the description carries the disclosure burden. It conveys that the operation is read-only, filters by exact column equality, and preserves the order of the provided values. It does not disclose behavior for missing values, mismatched columns, or case sensitivity, but the core behavior is sufficiently clear.

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 entire description is one compact sentence with the core behavior front-loaded and the use case appended after an em dash. Every word earns its place, and there is no redundant information.

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 tool, the description is largely adequate: it specifies input semantics, ordering, and purpose. However, the absence of an output schema leaves the return format unspecified, and edge cases like no matching rows or invalid columns are not addressed.

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. It explains 'column' as the matching field and 'values' as the list of accepted values whose order determines the output row order. It does not detail array constraints or whether matching is exact, but it adds meaningful semantics beyond the bare schema.

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 states what the tool does: it returns rows of the RemitDeck dataset whose column matches any of the given values, in the provided order. It distinguishes from siblings like dataset_row and dataset_search by specifying exact-value filtering and multiple row selection, though it lacks a direct verb like 'returns' or 'retrieves'.

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 usage context (comparing entities side by side), but it does not explicitly name alternative tools or state when not to use it. This is implied guidance rather than explicit routing.

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