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

Annotations already declare readOnlyHint=true, destructiveHint=false, and openWorldHint=false, so the safety profile is covered. The description adds a genuine behavioral trait beyond that: it discloses that an empty list is rejected, which lets the agent avoid a known failure mode before calling.

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?

Three short sentences, each doing distinct work: purpose, worked example, and the edge-case constraint. It is front-loaded with the core action and has no filler.

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?

An output schema exists, so return values need not be described, and the single parameter is fully documented. The remaining gap is contextual: for a tool sitting in a family of statistically overlapping calculators, the description does not establish its niche versus calculator_mean, leaving the agent to guess when this is the right pick.

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?

There is a single parameter with 100% schema description coverage, so the baseline is 3. The worked example '[10, 20, 30] → 20' goes beyond the schema by concretely illustrating both the accepted input shape and the expected output, adding real clarity about what the tool returns for a given input.

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 gives a specific verb and resource ('calculate the arithmetic mean of a list of numbers'), which is unambiguous on its own. However, it never distinguishes itself from the very similar sibling calculator_mean (or calculator_weighted_average), so an agent facing both mean and average tools gets no help choosing, which prevents 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?

'Use this tool to calculate...' merely restates the purpose rather than giving selection guidance. With calculator_mean, calculator_median, calculator_mode, and calculator_weighted_average all in the sibling list, the absence of any when-to-use/when-not-to-use or alternative routing is a notable gap.

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