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

With no annotations and no output schema, the description carries the full burden of behavioral disclosure. It names the computed statistics but does not state return format, input parsing rules, error behavior, or whether the operation is read-only.

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 short and front-loaded, wasting no words on filler. It could be slightly more informative without losing conciseness.

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 one-parameter tool with no annotations or output schema, essential call-time details are missing: how the numbers string should be formatted and what the response contains. Given the large sibling set including get_stats, more disambiguation is needed.

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 schema covers the only parameter, so the baseline is 3. The description adds nothing about the expected string format, separators, or ordering, and the schema's 'Numbers to process' is too vague to fill that gap.

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 tool as a statistical utility and names three outputs (mean, median, variance), which gives a basic sense of purpose. However, it lacks a strong verb and does not distinguish this aggregate tool from very similar siblings like get_stats, x402-mean-of, or x402-median.

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 explains when to use x402-stats instead of get_stats or the individual statistic tools. The intended use is only implied by the word 'Stats' and the listed metrics.

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