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

With no annotations, the description must carry behavioral disclosure. It does add one genuinely useful operational fact — a free-trial quota of 5 calls per signed wallet, implying a metered/auth model — but says nothing about the return shape (a single scalar?) or what happens with mismatched or empty inputs.

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?

Two short sentences with the definition front-loaded and the input instruction immediately after. The appended trial-call/promo clause is the only element that is not strictly about invoking the tool.

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 4-parameter tool with no annotations and no output schema, the description resolves only half the inputs and gives no indication of the result. An agent still cannot tell whether to send yTrue/yPred or actual/predicted, or what it gets back.

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 description coverage is 0% and no parameter is described in the schema, so the description must compensate. It names only yTrue and yPred, leaving the equally present actual/predicted parameters entirely unexplained and their relationship to yTrue/yPred ambiguous; it also calls them "arrays" while the schema types them as strings.

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 names a specific metric and defines it operationally ("harmonic mean of precision and recall") from actual and predicted labels, which is enough to distinguish it from neighboring metric tools like x402-recall or x402-confusion-matrix. It does not explicitly name a sibling alternative, so it stops short of 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 guidance on when to use this tool versus the many related classification-metric siblings, and no stated prerequisite for how the label inputs should be shaped. The only condition given is "Provide yTrue and yPred arrays," which is a bare instruction rather than usage guidance.

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