harmonic_mean

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

No annotations are provided, so the description carries the full burden. It usefully discloses the domain constraint that inputs must be positive, but says nothing about behavior on empty arrays, zero/negative inputs, or errors. Partial but not full behavioral disclosure.

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?

A single front-loaded sentence with no filler; every word earns its place and the key domain constraint is included.

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 one-parameter statistical tool with an output schema (so return values needn't be described), the description covers the core purpose and a key domain constraint. It falls short only on error/edge-case behavior, 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?

Schema description coverage is 0% and the single 'numbers' array param is undocumented in the schema. The description adds the meaningful constraint that values must be positive, but does not clarify that input is an array of numbers or how invalid input is handled.

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 ('harmonic mean'), which distinguishes it from the sibling 'geometric_mean' and 'mean' by name. However, it does not explicitly contrast itself with those siblings, so an agent must infer the difference.

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 on when to use harmonic mean versus the sibling 'geometric_mean' or 'mean', and no prerequisites or exclusions stated. The 'positive values' phrase hints at the domain but is not framed as usage guidance.

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