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

Annotations already declare read-only, idempotent, open-world, and non-destructive behavior. The description adds useful domain behavior: the inversion formula, a concrete input-output example, the undefined zero case, and payment/HTTPS endpoint details. It still does not specify response formatting or error payload shape, but it adds substantial context beyond the annotations.

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 definition is front-loaded and compact: formula first, then example, zero caveat, and operational payment/endpoint details. Every sentence contributes relevant information without unnecessary repetition.

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 mathematical tool, the description covers the core computation, a concrete example, the invalid zero case, and access/payment details. It is nearly complete, though it could explicitly describe the output shape or precision handling.

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 schema provides no parameter descriptions, so the description must carry the semantic load. The worked example helps reveal that q is a four-component quaternion and shows component order and expected rational output, but the description never explicitly documents q, its string representation, or how fractional or decimal inputs are formatted.

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: the inverse of a quaternion, including the defining formula. This clearly distinguishes it from sibling quaternion tools such as quat_mul, quat_norm, quat_pow, and quat_rotate. The worked example reinforces the exact computation.

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?

Usage is largely implied by the mathematical operation, and the description notes the zero-input exclusion, but it does not explicitly say when to choose this tool over related siblings. There is no alternative-routing guidance beyond the inherent purpose of computing an inverse.

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