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

With no annotations provided, the description carries full responsibility for disclosing behavior. It only states a formula-like phrase and gives no insight into how inputs are supplied (zero params), how the interquartile range is defined, how ties/outliers are handled, or what the output format is.

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 very short and readable, but it is more under-specified than concise. It front-loads the core term but omits useful context; it is not wasteful, yet it fails to earn its place by providing sufficient operational detail.

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?

Given the zero-parameter schema and no output schema, the description needs to explain what inputs the tool consumes (likely via context or defaults) and what the result represents. It does neither. The broad sibling list of statistical tools makes the lack of differentiation and usage guidance a significant deficiency.

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 has zero parameters and the description cannot add much semantic detail. The baseline for zero params is 4. The description does clarify that the operation is a mean derived from the interquartile range, which is minimal but sufficient given there is nothing to parameterize.

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 identifies the operation as computing a mean of interquartile values. It distinguishes itself from related stats tools like x402-quartile and x402-midhinge through the specific term 'Interquartile Mean,' but the explanation is terse and doesn't clarify what data is used (e.g., lower/upper quartiles, median) or how it relates to midhinge/trimean variants.

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 explicit guidance on when to use this tool over alternatives like x402-trimean, x402-midhinge, x402-winsorized-mean, or x402-mean-of. The context implies it is for statistical calculation, but no conditions, prerequisites, or exclusions are provided.

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