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

With no annotations, the description carries the full behavioral burden. It usefully discloses the interpolation method and hints at the paid/limited access model ('5 free trial calls per signed wallet'), but says nothing about input format, output shape, edge cases (empty array, p outside 0-100), or error behavior.

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 core is front-loaded in one tight sentence. The trailing emoji/pricing line is marketing noise but does convey the trial/paid model, so it earns partial keep.

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 simple math utility with no output schema and no annotations, the description explains the computation adequately but omits the input encoding details that matter most given three untyped string parameters and zero schema coverage.

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 none of the three string-typed parameters is documented. The description implies 'p' is the percentile rank and 'values' the array, but the redundant third parameter 'percentile' is never explained, and the required input encoding (JSON array string? CSV?) is left ambiguous.

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?

States a specific verb and resource ('Returns the p-th percentile of an array') and even names the algorithm ('linear interpolation between ranks'). It does not distinguish itself from close siblings like x402-percentile-rank, x402-quartile, or x402-median, so an agent must infer the boundary.

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 when-to-use, when-not, or alternative routing is given. The description never mentions the nearby percentile/quartile/median tools that an agent should choose between, leaving usage entirely to inference.

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