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

With no annotations, the description carries the full behavioral burden. It discloses the core filtering and ordering semantics, but omits read-only status (implied by 'rows'), error behavior, output format beyond 'the rows', and any constraints such as the 2–10 value limit.

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 sentence that front-loads the resource and core operation. It is compact with no obvious filler, though the noun-phrase style is slightly less direct than a full verb-led sentence.

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 with no annotations or output schema, the description covers the essential return selection and ordering. However, it leaves gaps around acceptable column values, array length constraints, and the read-only nature, so an agent still needs to infer details from the schema alone.

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 identifies both parameters by role ('column' matches against 'given values') and adds the meaningful ordering rule ('in the order given'), but provides no format or constraint details (e.g., column name syntax, string types, min/max array length) to fully make up for the empty schema descriptions.

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 states a specific dataset ('Strength Standards Calc') and a specific row-selection operation: rows whose column matches any of the given values, in the given order. It distinguishes itself from siblings like dataset_search or dataset_top by its 'X vs Y' comparison framing, though it does not name those alternatives directly.

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 an implied usage context ('for "X vs Y" questions') but does not explicitly say when to use this tool instead of siblings like dataset_row or dataset_search. No exclusions or prerequisites are stated.

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