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spss-studio-mcp

spss-studio-mcp

by CongJyu
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
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Spss T Test

spss_t_test

Run one-sample, independent, or paired t-tests in SPSS to compare means. Requires IBM SPSS Statistics installed.

Instructions

Run SPSS t-test. Supports one_sample, independent, and paired test types. Requires IBM SPSS Statistics to be installed.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "file_path": "<file_path>",
      "test_type": "<test_type>",
      "variables": "<variables>"
    },
    "name": "spss_t_test"
  }
}

Input Schema

NameRequiredDescriptionDefault
file_pathYes
test_typeYes
variablesYes
test_valueNo
grouping_variableNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.9/5.0
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 does disclose a real behavioral constraint — the external IBM SPSS Statistics dependency — which is valuable context. But it says nothing about permissions, side effects, or execution characteristics beyond that, and an output schema exists so return values needn't be covered.

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?

Three short, front-loaded sentences with no filler; the core action leads. Slightly under-specified rather than overly concise, but structurally sound.

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?

For a 5-parameter statistical tool with no annotations and 0% schema description coverage, the description is too thin. It never explains what the parameters mean or how test_value/grouping_variable relate to test_type, leaving the agent to guess.

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

Parameters2/5

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

Schema description coverage is 0% across 5 parameters. The description names the enum values for test_type, but that merely repeats the schema, and it is silent on file_path, variables, test_value, and grouping_variable. With zero schema coverage, the description needed to compensate and does not.

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?

Clear verb+resource ('Run SPSS t-test') and it names the three supported test variants, which is concrete. However, it offers no differentiation from siblings like spss_anova or spss_nonparametric_tests, so an agent can't tell when a t-test is the right choice versus those.

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 description lists the test types but gives no guidance on when to choose one_sample vs independent vs paired, nor any prerequisites beyond SPSS being installed. No mention of alternatives or exclusions.

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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