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CongJyu

spss-studio-mcp

by CongJyu

Spss Repeated Measures Anova

spss_repeated_measures_anova

Run within-subject repeated-measures ANOVA in IBM SPSS Statistics; provide within-factor name, number of levels, and one variable per level.

Instructions

Run SPSS repeated-measures ANOVA (within-subject GLM). Provide within-factor name, number of levels, and one variable per level. Requires IBM SPSS Statistics to be installed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
levelsYes
file_pathYes
variablesYes
include_pairwiseNo
within_factor_nameYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden. It usefully discloses the hard requirement that IBM SPSS Statistics be installed, plus the shape of the analysis (within-subject). It does not say whether the tool writes output files, what permissions are needed, or how it behaves on unbalanced designs, and with no annotations that gap is notable.

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

Conciseness4/5

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

Two compact sentences, front-loaded with the operation and followed by the required inputs and prerequisite. No wasted words, though the parameter sentence is a bare list rather than explanatory.

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

Completeness3/5

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

An output schema exists, so return values need not be explained, and the SPSS-installed prerequisite is covered. Still missing are guidance on the undocumented file_path/include_pairwise parameters and any routing signal against the many sibling statistical methods, leaving the definition only adequate for a complex analysis tool.

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

Parameters3/5

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

Schema description coverage is 0%, so the description must compensate. It maps three of five parameters (within-factor name, levels, variables) but says nothing about file_path or include_pairwise, leaving those semantics entirely undocumented.

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?

States a specific verb (Run) and resource (SPSS repeated-measures ANOVA / within-subject GLM), which is enough to separate it from the between-subjects spss_anova and from spss_manova or spss_glm_univariate. It never names a sibling explicitly, so it falls just short of the top tier.

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 parenthetical 'within-subject GLM' implies the design this tool is for, which is implicit when-to-use guidance. It gives no explicit condition for choosing it over spss_anova, spss_mixed, or spss_manova, and no prerequisites beyond the software install.

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