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, and it discloses nothing: no input format expectations, no output format, no error behavior. The duplicated title sentence adds 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?

Very short, but it is under-specification rather than conciseness: the two clauses are the same phrase repeated, so no sentence earns its place.

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 statistical computation tool with no annotations and no output schema, an agent has no idea what the input format is or what the result looks like. The definition is completely inadequate to call the tool correctly.

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 per the rubric the baseline is 3. However, neither the schema ('Values to process') nor the description clarifies the expected encoding (comma-separated, JSON array, etc.), so no value is added beyond the baseline.

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 the literal string 'Sample Variance: Sample Variance', restating the tool name/title twice without stating a verb or scope. It is a tautology, though the resource ('sample variance') is at least identifiable. It does nothing to distinguish this from siblings like x402-variance-sample, x402-variance, or x402-variance-population.

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 when-to-use guidance whatsoever. Nothing tells the agent when sample variance is preferred over population variance or the sibling statistic tools, even though several near-identical siblings exist.

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