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

With no annotations, the description carries the full burden, and it does disclose two real behaviors: equal-length arrays are required and a constant actual array yields null. It also notes the free-trial/payment gating. It does not say what error is returned on mismatched lengths or whether the result is a fraction or percent.

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 computational statement is front-loaded in one efficient clause, followed by the constraints. The trailing emoji trial-call promo is noise relative to the math, but it is short and does not obscure the core.

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 numeric tool with four undocumented, non-required parameters and no output schema, the description should resolve the a/p vs actual/predicted ambiguity and the string-array format. Those gaps mean an agent could invoke it with the wrong parameter pair and never know.

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 0% and all four parameters are bare strings, yet the description only explains "actual" and "predicted" — it never mentions the "a" and "p" aliases or clarifies that all four are string-encoded arrays. A caller cannot tell which pair to supply or in what serialization.

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?

It names a specific verb and resource ("Computes R-squared comparing actual and predicted arrays") and even states the algorithm (residual and total sums of squares), so the operation is unambiguous. It never distinguishes itself from close siblings such as x402-adjusted-r-squared or x402-r2-score, which is the only thing keeping it from a 5.

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 statement of when to pick this over the adjusted R-squared or r2-score siblings, and no prerequisites or preconditions beyond the same-length constraint. The agent has to infer the use case (regression fit evaluation) from the math itself.

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