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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does list the statistics returned, which is useful, but it does not disclose edge-case behavior such as handling of empty arrays, NaN values, or missing data. The operation is inherently read-only and non-destructive, which is implicitly clear.

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, information-dense sentence with no wasted words. It front-loads the purpose and then lists the outputs in a clear, scannable manner. Every element contributes to understanding the tool.

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?

The tool is simple with one parameter and no output schema, and the description covers the primary output values. However, it omits input constraints and return structure, and does not address edge cases that are relevant for descriptive statistics. The description is adequate for basic selection but not fully complete for confident invocation in unusual cases.

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%, so the description must compensate for the undocumented parameter. However, it only restates that the input is a numeric array, which adds little beyond the schema's array-of-numbers type. It does not clarify minimum length, whether missing values are allowed, or any constraints on the numeric values.

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 identifies the tool as computing summary statistics for a numeric array and names the exact outputs: mean, median, sd, variance, quartiles, IQR, skewness, min/max. This specific list distinguishes it from sibling tools like hypothesis_test or confidence_interval, which serve different statistical purposes.

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 provides no guidance on when to choose this tool over alternatives. It does not mention sibling tools, exclusions, or conditions for use. The intended use is implied by the name and output list, but no explicit when-to-use or when-not-to-use information is given.

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