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

Since no annotations are present, the description carries the burden of explaining behavior. It discloses that non-numeric rows are excluded and counted and that formatting like grouping commas and currency is handled, which gives useful transparency about data processing. It does not explicitly state that the operation is read-only, but the statistical nature strongly implies no modification.

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 concise sentence with a parenthetical that adds relevant edge-case behavior. There is no redundant or irrelevant text.

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?

The description identifies the input type, the dataset, and the exact statistics returned, which is sufficient for a simple stats tool without an output schema. It does not detail output formatting, but the listed statistics make the expected result clear.

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 only lists a 'column' string with no description, so the description compensates by indicating it must be a numeric column of the KnownVehicle dataset. It also clarifies how values with commas and currency symbols are parsed, adding meaning 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 identifies the tool's function: computing count, min, max, mean, median, and sum for a numeric column in the KnownVehicle dataset. It distinguishes this from sibling dataset tools by focusing on aggregate statistics rather than rows, columns, or comparisons.

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 implies the tool is appropriate when summary statistics for a numeric column are needed and notes that grouping commas and currency are handled. It does not explicitly mention alternative tools or state when not to use it, so usage guidance is only implied.

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