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

With no annotations, the description carries the full burden of behavioral disclosure, and it fails to explain how the tool operates given an empty input schema. The agent cannot tell what side length is used (is there a default? is a value passed some other way?), what the output format is, or whether it returns a formula or a computed number. For a computation tool, this is a substantial 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?

The description is very short and front-loaded with the tool name, and 'Face diagonal' adds a meaningful clarification. However, it borders on under-specification and is partially tautological, essentially restating the tool name before adding the one useful qualifier.

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 math-computation tool with no annotations, no output schema, and an empty input schema, the description is incomplete. It does not state the formula (d = s√2), the assumed side length, the output format, or how the agent should interact with a tool that accepts no parameters. Closely related siblings (cube-space-diagonal, cuboid-diagonal) increase the need for clarity that is not provided.

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 are zero parameters, so the baseline is 4 per the rubric. The description adds no parameter-level detail, but there are no parameters to document. The empty schema leaves the question of how input is supplied unresolved, though this is arguably a behavioral-transparency issue rather than a parameter-semantics one.

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 the resource (cube diagonal) and adds a key clarifying detail: it computes the FACE diagonal, not the space diagonal. This differentiates it from the sibling x402-cube-space-diagonal. However, it lacks an explicit verb (compute/calculate) and relies on the noun phrase to convey the action.

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 explicit when-to-use guidance or named alternatives are provided. The clarification 'Face diagonal' implies the tool is for face-diagonal rather than space-diagonal or cuboid-diagonal calculations, but the agent is left to infer this from the fragment rather than being told when to select this tool over x402-cube-space-diagonal or x402-cuboid-diagonal.

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