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

With no annotations, the description carries the behavioral disclosure burden. It reveals important parsing behavior: grouping commas and currency symbols are handled, and non-numeric rows are excluded and counted. This goes beyond a bare 'compute stats' claim and informs the agent about data-cleaning effects.

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 entire description is one dense sentence that front-loads the metric list before the data-handling caveats. There is no filler or redundant restatement of the 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 one-parameter read-only stats tool with no annotations and no output schema, the description is nearly complete: it enumerates the returned metrics and the input parsing behavior. Minor ambiguity remains about whether 'count' refers to numeric rows or total rows and how excluded rows are reported, but for this low-complexity tool the gaps are small.

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 single column parameter has no schema-level description (0% coverage), so the description must compensate. It does by clarifying that the column must be numeric and belong to the Retainvo dataset, and by noting input formatting quirks. It does not state exact-match or case requirements, but for one string parameter this is adequate.

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 title and description clearly define the tool as computing summary statistics for a numeric column, enumerating the exact metrics: count, min, max, mean, median, and sum. It identifies the specific resource (Retainvo dataset), though it does not explicitly distinguish itself from sibling tools like dataset_top or dataset_compare.

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 intended use case is clear: call this tool when numeric summary statistics for a Retainvo column are needed, and the metric list makes the scope explicit. It does not name alternatives or state when not to use it, but the context is clear enough for an agent to select it over row/search/compare siblings.

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