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

No annotations are provided, so the description carries the full disclosure burden, and it discloses essentially nothing: no statement of determinism, of input format expectations (the single parameter is a string, implying comma-separated values), of error behavior on malformed input, or of return shape. It only restates the name.

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 single sentence is short but under-specified rather than concise: it spends its only clause restating the tool name in expanded form without conveying any information an agent did not already have.

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 statistical calculator with no annotations and no output schema, an agent still lacks input encoding, minimum input requirements, and what the returned number represents. The definition is not complete enough to invoke the tool confidently on first try.

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%, so the single parameter is nominally documented and the baseline is 3. However, the schema text ("Values to process") is itself uninformative, and the description adds nothing about whether values are comma-separated, space-separated, or how many are required.

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 merely expands the name's abbreviation ("Mean Abs Deviation: Mean of abs deviation"), which is a tautology rather than a definition. It never says deviation from what (the arithmetic mean?) nor distinguishes itself from near-identical siblings like x402-median-absolute-deviation or x402-mean-absolute-error.

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 statement of when to use this tool, when not to, or which sibling to prefer. Given the many related statistical tools in the list (mean-absolute-error, median-absolute-deviation, mean-of, stddev), the absence of any routing guidance is a real gap.

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