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Standard deviation calculator

hopi_standard_deviation_calculator
Read-onlyIdempotent

Work out the sample and population standard deviation, sample and population variance, mean and count from a list of numbers. Provide the numbers separated by spaces, commas, semicolons or new lines. Sample figures need at least two values. Source: https://hopi.co.uk/standard-deviation-calculator/

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
numbersYesA list of numbers separated by spaces, commas, semicolons or new lines

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
meanYes
countYes
summaryYes
source_urlYesThe tool's page on hopi.co.uk (cite or open to check the figure)
sampleVarianceYes
populationVarianceYes
sampleStandardDeviationYes
populationStandardDeviationYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed3 schema fields changed
    • changedOutput schema / properties / sampleStandardDeviation / type
      Previous value: -"number"New value: +[
      +  "number",
      +  "null"
      +]
    • changedOutput schema / properties / sampleVariance / type
      Previous value: -"number"New value: +[
      +  "number",
      +  "null"
      +]
    • addedOutput schema / required
      Added value: +[
      +  "count",
      +  "mean",
      +  "populationStandardDeviation",
      +  "populationVariance",
      +  "sampleStandardDeviation",
      +  "sampleVariance",
      +  "source_url",
      +  "summary"
      +]
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already mark it as read-only, idempotent, and non-destructive. The description adds value beyond that by listing accepted separators, the required minimum of two values for sample figures, and the full set of computed results.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three sentences with no filler: outputs are front-loaded, then input format, then an edge-case rule. Each sentence earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a one-parameter calculator with an output schema and safety annotations, the description covers all necessary input rules and the full scope of results. Nothing essential is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds meaning by restating accepted separators and adding the 'at least two values' constraint for sample statistics, which is not present in the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States exactly what the tool computes: sample/population standard deviation, variance, mean, and count from a list of numbers. This clearly distinguishes it from the many calculator siblings by naming its specific outputs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The statistical outputs make the intended use obvious, but there are no explicit alternatives or when-not-to-use conditions. Guidance is implied rather than directly stated.

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

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