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

No annotations are provided, so the description carries the burden of behavioral disclosure. It adds non-obvious details: grouping commas and currency are handled, and non-numeric rows are excluded and counted. This meaningfully informs result interpretation beyond the title.

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 output statistics and then adds edge-case handling details. There is no filler or redundant restating of the tool name or title.

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 one-parameter, read-only statistics tool, the description is nearly complete. It enumerates the returned values and key parsing/cleaning behaviors, though the meaning of 'excluded and counted' is slightly ambiguous and there is no explicit output shape.

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%, and the schema only says the 'column' parameter is a string. The description clarifies that the value must refer to a numeric column, which adds meaning, but it does not specify the expected identifier format, such as whether it must match dataset_columns names or be case-sensitive.

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 names the tool's exact outputs (count, min, max, mean, median, sum) and clearly scopes it to a numeric column of the RollCallWorks dataset. This is a specific verb-plus-resource statement that distinguishes it from row-level or search siblings.

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 establishes clear context: use this when aggregate numeric statistics for a column are needed. It does not explicitly say when not to use it or name alternatives, but the sibling tools' purposes are distinct enough that this description provides adequate situational guidance.

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