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

The description mentions the ordering behavior ('in the order given') but does not explicitly state the operation is read-only or describe side effects. Since there are no annotations, the description carries full burden but lacks an explicit safety statement.

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 front-loads the core purpose and includes the key detail about ordering. There is no filler or redundant content.

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 filtered retrieval tool, the description covers the essential behavior. It does not specify the output format (e.g., which columns are returned) or error conditions, but given the tool's simplicity, this is a minor gap.

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 description directly explains both parameters: 'column' is the attribute to filter on, and 'values' are the matching values. This adds meaningful semantics beyond the raw schema, clarifying the filtering and ordering behavior.

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 the tool returns rows from the Retainvia dataset that match any of the given values for a specified column, in the provided order. This distinguishes it from sibling tools like dataset_row (single row) and dataset_search (generic search).

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 gives a use case ('for X vs Y questions') but does not explicitly name alternatives or explain when to choose this over dataset_search or dataset_top. Usage guidance is implied rather than explicit.

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