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

No annotations are provided, so the description carries the full behavioral burden, but it says nothing about computation behavior, input handling, edge cases, or return values. The malformed phrase adds no useful context.

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?

It is very short, but the single sentence is incomplete and garbled rather than concise and front-loaded. It does not earn its place because it fails to communicate the tool's action.

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 statistical calculation tool with no annotations or output schema, the description should at minimum explain what is calculated from `values`. Instead it is incomplete and does not compensate for missing structured behavioral context.

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 has 100% description coverage for the single `values` parameter, so the schema already documents the parameter adequately. The description adds no parameter meaning beyond the schema, which matches the baseline of 3 when schema coverage is high.

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 restates the tool's name and appends a broken phrase, "Mean of standard error of," which does not state a clear verb or what is computed. It is effectively tautological rather than explanatory, though the name itself hints at the statistical concept.

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 siblings such as x402-standard-error, x402-sample-mean, or x402-stddev-sample. No context, exclusions, or alternatives are provided.

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