average

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It discloses that numeric strings are accepted and that commas are not supported, which is important input-formatting behavior. However, it does not reveal what happens with empty arrays, invalid values, or the return type, leaving some behavioral 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 is front-loaded with the core purpose and includes only necessary constraints. No redundant words or irrelevant details, making it highly efficient for an agent to parse.

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 simple math tool, the description covers the key operational aspect and an important input limitation. However, it omits edge-case behavior (e.g., empty array) and the return value structure, which could require the agent to infer or test. Given the lack of output schema, a small addition about return type would improve completeness.

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 input schema is empty, so the description is the only source of parameter meaning. It clearly specifies that the tool expects an Array of numbers, and adds crucial validation rules (numeric strings allowed, commas not supported). This fully compensates for the lack of schema properties.

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 states a specific operation ('Calculates the average (mean)') on a well-defined input ('Array of numbers'). This clearly distinguishes it from sibling tools like median, mode, and countinstances, which perform different statistical or counting functions.

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 makes the tool's use case clear: computing the arithmetic mean of an array of numbers. It does not explicitly mention when not to use it or compare with alternatives, but the context is strong enough that an agent can infer appropriate usage. Sibling tools like median and mode are distinct, so ambiguity is low.

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