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

With no annotations provided, the description carries the full burden of behavioral disclosure, and it discloses nothing. It does not state whether the tool accepts input, how it computes the result, what it returns, or whether it has any side effects. This is a complete absence of behavioral information.

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 short, but this is under-specification, not conciseness. Repeating the tool's name as both the term and its definition adds no value and wastes the opportunity to convey useful information. Every sentence should earn its place; this one does not.

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?

The tool has no annotations, no output schema, and an empty input schema, yet the description provides no explanation of how an agent should invoke it or what to expect in return. An RMSE calculation normally requires inputs, but the description does not even hint at how those are supplied. This is completely inadequate for correct usage.

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 has zero properties, so schema description coverage is trivially 100%. Per the baseline rule for 0-parameter tools, a score of 4 is appropriate since there are no parameter semantics to explain. However, the description does not clarify how the tool obtains the data needed for RMSE, which is a gap better captured under contextual completeness.

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 'Root Mean Squared Error: Root Mean Squared Error' is a pure tautology that restates the tool name without adding any information about what the tool does. It lacks a verb, a resource, or even a definition of the metric. An agent cannot tell from this description what operation is performed or how it differs from sibling statistical tools.

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?

There is no guidance on when to use this tool versus alternatives like x402-mean-squared-error, x402-r-squared, or other regression metrics. The description provides no context, use cases, or exclusions, leaving the agent with zero routing information.

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