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

No annotations are provided, so the description carries the full behavioral burden, and it discloses nothing: no input format expectations, no error behavior, no constraints on the size or shape of the predictors input. The agent receives no signal about how the tool behaves at all.

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 text is short, but brevity here is under-specification rather than conciseness. Repeating the same phrase before and after a colon adds no front-loaded information and wastes the only sentence the tool has.

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?

A statistics tool with two structurally ambiguous string inputs, no annotations, and no output schema needs the description to explain input format and result shape. It explains none of this, so an agent cannot reliably 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 nominally 100%, but the schema descriptions are themselves placeholders ('Actual to process', 'Predictors to process'), so no real parameter semantics are conveyed anywhere. The tool description adds nothing about the expected encoding of 'actual' (comma-separated list? array string?) or 'predictors' (a single series or a matrix of multiple predictors), leaving the agent unable to construct a valid call even though required count is 0.

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 is a tautology: it repeats the tool name 'Adjusted R Squared' twice with no verb, scope, or output statement. A domain reader can guess it computes an adjusted coefficient of determination, but the text itself states nothing beyond the title and does not distinguish it from sibling statistical tools such as x402-r-squared or x402-linear-regression.

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, when to use x402-r-squared instead, or what preconditions apply. The description contains zero routing or exclusion information.

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