statistics_calc

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. It doesn't say whether all statistics are returned together or selected, what the output shape is, how non-numeric or malformed input is handled, or anything about empty/singleton inputs. The vague 'and more' actively obscures the output set.

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?

A single efficient sentence with the verb and the output list front-loaded. No waste, though 'and more' is a filler phrase that adds ambiguity rather than information.

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 output schema and no annotations, the description should clarify what is returned (all statistics vs. a subset) and how errors are surfaced. Instead it leaves the return contract undefined, which is the key gap for a computational tool whose entire value is its output.

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 single parameter has 100% schema description coverage ('Comma-separated numbers or array'), so the schema already documents input format. The description adds only the framing 'for a set of numbers' and contributes no syntax or format detail beyond the schema. Baseline 3 applies.

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?

States a specific verb (Calculate) and resource (statistics over a set of numbers) and enumerates several concrete outputs (mean, median, mode, standard deviation). It is clear what the tool does, but it does not distinguish itself from near-neighbor siblings such as descriptive_stats, variance_calc, or zscore_calculate.

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 versus the many overlapping statistics siblings. The agent is left to infer selection criteria from the name alone, which is risky given descriptive_stats exists.

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