mean

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

No annotations are provided, so the description carries the full behavioral burden for a pure computation. It discloses nothing about return precision, rounding, error behavior on non-numeric input, or edge cases beyond what the schema's minItems already enforces; for a stateless math function the risk surface is small, so this is only a moderate gap.

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?

Two short sentences, the core behavior front-loaded, and the alternative-tool hint placed second. No filler or restated boilerplate.

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 single-argument pure computation with a fully documented schema and no output schema, the definition covers what an agent needs to invoke it. The remaining omission is edge-case behavior and return precision, which is minor here.

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?

Only one parameter, and schema description coverage is 100%, so the schema already documents 'numbers' as 'Array of numbers to find the mean of'. The description adds no format, range, or count constraints beyond that, which is the expected baseline when the schema does the work.

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 ('Calculates') and resource ('arithmetic mean of a list of numbers'), which is unambiguous. It does not distinguish itself from the closest siblings, median and mode, which an agent might reasonably confuse it with, so it stops short of a 5.

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?

Explicitly routes multi-step or chained computation to batch_calc, giving a clear alternative for one scenario. It offers no guidance on when mean is the right choice versus median/mode, and the batch_calc note is peripheral to the primary use case.

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