stddev

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

No annotations are provided, so the description must fully disclose behavior. It does not mention whether it computes population or sample standard deviation, nor does it describe any assumptions about the input (e.g., handling of empty arrays or non-numeric values).

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, concise sentence that is front-loaded with the action and result. It contains no unnecessary words.

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 that this is a statistical function with a required array parameter and no annotations, the description is incomplete. It omits critical details such as the type of standard deviation (population vs. sample), the required input format, and the return value characteristics (though an output schema exists, it likely describes the return type but not the statistical method).

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 coverage is 0% and there is only 1 parameter. The description says 'of a dataset' but does not clarify that the parameter is an array of numbers. Baseline for 1 param is not explicitly defined; however, with low schema coverage, the description should compensate but does not add meaning beyond the schema's property 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?

States a specific verb (Calculate) and resource (standard deviation of a dataset), which clearly distinguishes it from siblings like variance or mean. However, it does not explicitly differentiate from the closest sibling 'variance', which is a related but distinct statistic.

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 is provided on when to use standard deviation vs. variance or other spread measures. The description merely states what the tool does without any context for selection.

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