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

With no annotations, the description carries the full burden of behavioral disclosure. It does disclose that grouping commas and currency are handled and non-numeric rows are excluded and counted, which is valuable context beyond the schema. However, it does not mention error handling for empty/missing columns, return format, or other edge cases, leaving some gaps.

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 sentence that front-loads the list of statistics, then adds the data handling note. Every word earns its place; it is concise, clear, and well-structured with no redundancy.

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?

Given the simplicity of the tool (one parameter, no output schema), the description covers purpose and data handling well. It implies the return includes those statistics but does not explicitly state the return structure or error behavior. Minor gaps remain, but the overall context is adequate for an agent to use it correctly.

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 provides only a bare 'column' string with no description (0% coverage). The description adds meaning by clarifying the column is expected to be numeric and explaining how non-numeric rows are handled. This compensates for the schema gap, though it does not specify format constraints beyond that, which is sufficient for a single parameter.

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 explicitly states the tool computes count, min, max, mean, median, and sum for a numeric column, specifically of the FlatRateBook dataset. This is a specific verb+resource that distinguishes it from siblings like dataset_columns (which lists columns) and dataset_search (which searches).

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 does not provide any when-to-use guidance or exclusions. It only describes what the tool does, leaving the agent to infer when to use it versus alternatives. There is no mention of conditions, alternatives, or context that would help select this tool over siblings.

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