Compute mean, median, mode, standard deviation, variance, skewness, kurtosis, quartiles, and IQR from a numeric data array.
Compute descriptive statistics: mean, median, mode, std, variance, skewness, kurtosis, quartiles, IQR, and more.
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | Numeric data array |
Changes observed during successful MCP inspections.
v0.1.11Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnly, idempotent, non-destructive, and openWorld behavior, so the safety profile is covered. The description adds a list of computed metrics but does not disclose edge-case behavior, numeric input requirements, empty-array handling, precision, or return format beyond the stat names.
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 description is a single front-loaded sentence with no wasted wording. It immediately identifies the operation and lists the outputs.
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?
The tool is simple, but without an output schema the description should more clearly specify the return values; 'and more' leaves the output set vague. It is adequate for a one-parameter pure computation tool but lacks edge-case and output-format detail.
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 covers 100% of the single parameter, documenting `data` as a numeric array. The description does not add syntax or input constraints beyond what the schema already provides, so the baseline of 3 applies 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 states a specific verb and resource — compute descriptive statistics — and enumerates the main metrics returned. It is clear what the tool does, but it does not distinguish itself from nearby siblings such as statistics_calc, variance_calc, percentile_calc, or running_stats.
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 alternatives like statistics_calc, variance_calc, or percentile_calc, nor any note about prerequisites or exclusions. The usage is only inferable from the purpose statement.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.