describe

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

The description lists the statistics returned, including sample standard deviation and variance, which are behavioral choices. However, it does not mention edge cases (e.g., empty array, NaN handling) or performance characteristics. With no annotations, the description carries the full burden and is only partially adequate.

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 extremely concise: one line stating the purpose and one line listing the statistics. Every word is useful, front-loaded, and no unnecessary information. Perfectly concise for the tool's simplicity.

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 single parameter and no output schema, the description covers the essential behavior: what it expects and what it returns. It could include examples or error behavior, but for a simple descriptive statistics tool, this level of completeness is adequate. The sibling tools suggest a statistical context, and the description fits well.

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 has 0% description coverage, and the description does not add any semantic detail beyond the schema type for the 'data' parameter. It does not explain input constraints, format, or acceptable ranges, which is insufficient for a parameter with no schema description.

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 clearly states the tool returns summary statistics for a numeric sample, listing specific measures. The verb 'describe' matches the output. However, it does not explicitly differentiate from sibling tools like 'dataframe_describe', though the input type (array) implies a different use case.

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?

No guidance on when to use this tool versus alternatives such as 'dataframe_describe' for tabular data or other statistical tools. The description assumes the user knows the context, providing no when-to-use or when-not-to-use hints.

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