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

No annotations are present, so the description carries the full burden. It discloses that rows are returned for any matching value and that the output order follows the given values, which are key behavioral details. It does not mention side effects or pagination, though as a query tool it is presumably read-only; the input schema does cap values at 10, but this is not reflected in the description.

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, direct sentence with no redundant information. It effectively conveys the core functionality without unnecessary elaboration.

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 tool with two simple parameters and no output schema, the description provides sufficient context to understand the operation. It explains the input (column and values) and the output (rows) in a straightforward manner, and the sibling tool list helps place it within the dataset tool family.

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?

The schema provides only names and types with no per-parameter descriptions. The tool description clarifies that 'column' is the column to filter on and 'values' are the values to match, giving basic semantic meaning. It does not specify constraints like whether the column must exist or if matching is case-sensitive, but the overall meaning is adequate for basic use.

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 that it retrieves rows from the TakeoffDeck dataset based on a column and a list of values, preserving the order of the values. It also differentiates itself from sibling tools like dataset_row and dataset_search by focusing on comparing multiple values, making the purpose 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?

The phrase 'for X vs Y questions' provides a clear usage hint that this tool is suited for comparative scenarios. However, it does not explicitly contrast it with alternatives such as dataset_search or dataset_stats, leaving some inference to the agent.

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