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

With no annotations, the description carries the transparency burden. It discloses the core calculation, which is useful, but it does not describe quartile method, edge-case handling, or return format. For a simple calculation tool this is minimally adequate but not richly transparent.

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 compact and front-loads the mathematical definition before the input instruction. It contains little waste, though 'Provide values array' is terse and ambiguous about how the value should be delivered.

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?

Despite the clear formula, the definition is incomplete as an invocation contract: the required dataset cannot be passed through the empty schema, no output shape is described, and no distinction from adjacent stat tools is provided. An agent cannot rely on this to call the tool 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?

The input schema exposes zero properties, yet the description instructs 'Provide values array.' This creates a critical mismatch: an agent following the description will expect a values parameter that the schema does not define, so there is no structured way to supply the required data.

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 clear verb and resource: calculate the midhinge from a dataset, with a precise definition as the average of the first and third quartiles. The formula distinguishes it from statistical siblings like midrange, trimean, or quartile.

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 guidance on when to prefer this tool over the many related stat tools such as x402-quartile, x402-trimean, x402-iqr, or x402-five-number-summary. The usage context is only implied, with no exclusions or alternatives.

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