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

With no annotations, the description must carry the behavioral load, and it does disclose real data-handling semantics: grouping commas and currency are normalized, and non-numeric rows are excluded and counted. It still omits what happens if the column is entirely non-numeric, whether errors are raised, and the exact shape of the result.

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?

One front-loaded sentence that leads with the returned measures and tucks the caveats into a parenthetical. Dense but no wasted sentences; the parenthetical stacks three separate caveats together, slightly blurring the structure.

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?

Absent an output schema, the description helpfully enumerates the six returned fields, but it leaves the input contract (column addressing) and error behavior for a required, undocumented parameter unstated. Adequate for a simple one-parameter tool but with clear gaps.

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?

There is one parameter with 0% schema description coverage, and the description does add the constraint that the column must be numeric. However it does not clarify how the column is identified (name vs. index, case sensitivity, whether unknown columns error), leaving the sole parameter only partly specified.

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 Fair Odds Calculator dataset) and enumerates the returned measures, which separates it from siblings like dataset_top or dataset_compare. No sibling is named explicitly, so it stops short of a 5.

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 never says when to reach for this tool versus dataset_top, dataset_compare, or dataset_search, nor any prerequisites. Usage is only implied by the word 'statistics'.

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