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spss_nonparametric_tests

Run Mann-Whitney U, Wilcoxon signed-rank, or Kruskal-Wallis tests on SPSS data to compare groups without normal distribution assumptions. Requires IBM SPSS Statistics.

Instructions

Run common nonparametric tests in SPSS: Mann-Whitney U, Wilcoxon signed-rank, or Kruskal-Wallis. Requires IBM SPSS Statistics to be installed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
file_pathYes
test_typeYes
variablesYes
group_valuesNo
grouping_variableNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Install Server

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states that the tool runs tests and requires SPSS, but it does not disclose whether executing a test modifies data, creates output artifacts, or has side effects in the SPSS session. This is a thin behavioral profile for a command-style tool.

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?

The description is two sentences with no filler. The first sentence front-loads the action and test options, and the second adds a relevant prerequisite. Every sentence earns its place.

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

Completeness2/5

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

The existing output schema reduces the need to explain return values, but this is still a five-parameter tool with conditional parameter requirements and no annotations. The description leaves an agent unable to correctly shape the variables, grouping_variable, and group_values arguments for the selected test type.

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

Parameters1/5

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

Schema description coverage is 0%, and the description does not compensate by explaining any of the five parameters. It does not clarify that Wilcoxon uses two variables, that Mann-Whitney and Kruskal-Wallis require grouping_variable and group_values, or what file_path and variables should contain. The enum list merely repeats the test_type schema values.

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

Purpose4/5

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

The description uses a specific verb ('Run') and a clear resource ('common nonparametric tests in SPSS'), and it names the three supported tests. It distinguishes the tool from parametric sibling tools by the word 'nonparametric,' though it does not explicitly contrast it with a sibling.

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

Usage Guidelines2/5

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

The only usage-related information is the prerequisite that IBM SPSS Statistics must be installed. There is no guidance about when to choose this tool over t_test, anova, or other siblings, and no guidance about when each of the three nonparametric tests is appropriate.

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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