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

With no annotations, the description carries the behavioral burden and does a good job: it discloses that grouping commas and currency symbols are handled, and that non-numeric rows are excluded and counted. This is genuinely useful beyond the title and schema. It does not mention failure modes or return shape, but the core quirks are 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?

The description is a single dense sentence that front-loads the computed statistics and follows with the key edge-case behaviors. Every clause earns its place; there is no fluff or repetition of the schema.

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 tool with no output schema, the description is nearly complete: it states what statistics are returned and how messy numeric input is handled. A minor gap is the exact output shape and ambiguous phrasing around whether 'count' includes or excludes the non-numeric rows, but the overall context is sufficient for simple use.

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 only provides a string parameter named 'column', and description coverage is 0%. The description compensates by clarifying that the column must be numeric and by explaining how formatted numbers and non-numeric values are treated. This gives the agent enough semantic context to pass a valid column name.

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 together clearly define a summary-statistics tool for a numeric column, enumerating the exact outputs (count, min, max, mean, median, sum). This is specific enough to distinguish it from siblings like dataset_columns and dataset_row: the agent immediately knows it aggregates rather than lists or searches rows.

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 implies when the tool should be used: whenever an agent needs numeric summary statistics for a dataset column. However, it does not explicitly state when not to use it or mention an alternative, such as dataset_top or dataset_search, leaving some routing inference to the agent.

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