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 it does disclose meaningful traits: grouping commas and currency symbols are handled during parsing, and non-numeric rows are excluded and counted rather than silently dropped. It does not cover permissions, pagination, or result shape beyond the metric list, which keeps it from a 5.

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 concrete outputs and folds edge-case behavior into one compact parenthetical. Efficient, though the parenthetical is dense enough that it reads as a run-on.

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?

With no output schema and no annotations, the description does list the returned metrics and the parsing edge cases, covering the main gaps. It omits the required format of the column argument, which is the one thing an agent must get right to call the tool.

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% and the single required 'column' parameter has no documented format (name vs. index, case sensitivity, quoting). The description only implies the column must be numeric; it adds no syntax or format detail the schema lacks.

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 resource (a numeric column of the Roofing Quotes UK dataset) and enumerates exactly what is computed (count, min, max, mean, median, sum), so an agent knows precisely what the tool produces. It does not explicitly contrast itself with siblings like dataset_top or dataset_compare, 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?

There is no when-to-use or when-not-to-use guidance, and no sibling tool is mentioned as an alternative. The phrase 'of a numeric column' hints at the input constraint but does not tell the agent when this tool is preferable to dataset_top, dataset_compare, or dataset_row.

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