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

With no annotations provided, the description carries the full behavioral burden and does disclose meaningful traits: locale formatting is normalized ('grouping commas and currency are handled') and dirty data is handled deterministically ('non-numeric rows are excluded and counted'). It stops short of describing error behavior for missing columns or how the exclusion count is surfaced.

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 metrics list and appends the parsing/cleaning caveats. Dense but every clause earns its place; no filler.

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 aggregation tool with no output schema, the description effectively documents the return payload by listing exactly which metrics come back. The main omission is what happens on an invalid or non-numeric column name.

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% for the single 'column' parameter, but its name and the description's 'numeric column' phrasing convey that a numeric column reference is expected. It does not clarify the accepted format (exact header string vs. index) or casing, so it only partially compensates for the coverage gap.

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?

States a specific operation (summary statistics) on a specific resource (a numeric column of the SIM Only Deals Compare dataset) and enumerates the exact metrics returned. It is clearly distinguishable from siblings like dataset_columns or dataset_row, though it does not explicitly name them.

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 'of a numeric column' implies the column must be numeric, but there is no explicit guidance on when to reach for this tool versus dataset_columns or dataset_top, and no mention of prerequisites such as resolving a valid column name first.

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