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

Annotations already declare readOnlyHint=true, non-destructive, and closed-world, so the safety profile is covered. The description adds real behavioral information beyond that, namely the domain restriction that zero input is rejected, which tells the agent to guard against an error case.

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 with zero filler: the operation comes first, followed by a concrete example and the one failure condition. Nothing could be removed without losing information.

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 no explanation, and the single parameter plus the zero exclusion are fully covered. For a trivial one-parameter math tool, an agent has everything needed to call it correctly.

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 100% and the parameter is already documented as 'Non-zero number x for 1/x' with example values including a negative. The description restates the same semantics via 1/x and the example, adding little beyond the schema, so the baseline 3 applies.

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 names a specific operation and expresses it unambiguously as the formula 1/x, reinforced with a worked example (1/4 = 0.25). That pins it apart from the many sibling calculators such as calculator_absolute, calculator_fraction, or calculator_root, even though no sibling is named explicitly.

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?

It supplies a clear precondition, 'Rejects x=0', so the agent knows when the tool will not work. It gives no explicit comparison to alternatives like calculator_root or calculator_fraction, but for a single-purpose arithmetic tool the calling context is unambiguous.

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