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

No annotations are provided, so the description carries the full burden of behavioral disclosure, and it discloses nothing: no trimming fraction behavior, no input format expectations, no return shape. A pure restatement of the name conveys zero behavioral 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 short, but brevity here reflects under-specification rather than conciseness: the single redundant sentence contributes no information and is not front-loaded around any actionable content.

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?

With no annotations, no output schema, and a description that only echoes the name, an agent has no basis to select or invoke this tool correctly among hundreds of statistical siblings; nothing about trimming semantics or output is explained.

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 description coverage is 100% for the single 'values' parameter, so the schema already documents the input; the description adds no additional meaning (e.g., expected delimiter or numeric format). Baseline 3 applies when the schema does the heavy lifting.

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 is 'Trimmed Std: Trimmed Std', a verbatim restatement of the title with no verb, resource, or explanation of what is computed. It does not distinguish itself from close siblings such as x402-trimmed-mean or x402-winsorized-mean.

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, what 'trimmed' means in this context, or how it differs from the many nearby statistical siblings (trimmed-mean, winsorized-mean, stddev, std-dev-sample). Nothing is provided.

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