spss-studio-mcp

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Spss Genlinmixed

spss_genlinmixed

Run generalized linear mixed models in IBM SPSS to analyze non-normal outcomes with hierarchical or clustered data using fixed and random effects.

Instructions

Run generalized linear mixed model combining GLM with random effects. Supports non-normal outcomes with hierarchical structure. 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>",
      "dependent": "<dependent>",
      "fixed_effects": "<fixed_effects>"
    },
    "name": "spss_genlinmixed"
  }
}

Input Schema

Name	Required	Default
`link`	No
`subject`	No
`dependent`	Yes
`file_path`	Yes
`distribution`	No	NORMAL
`fixed_effects`	Yes
`random_effects`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Sep 12, 2026

TDQS

C2.8/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It contributes one operational fact, the SPSS installation requirement, but says nothing about side effects, permissions, convergence behavior, or whether data is modified. With no annotations and a complex statistical operation, this is a significant gap.

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?

The description is three concise sentences with the core purpose front-loaded. The capability note and installation prerequisite each add distinct value. It is efficient, though it could be slightly more informative without becoming bloated.

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 complex 7-parameter statistical tool with no schema descriptions and no annotations, the description is incomplete. It gives purpose and an installation prerequisite, but omits parameter semantics and usage guidance versus related tools like spss_genlin and spss_mixed. The output schema covers return values, but invocation details remain underspecified.

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 provides no information about any of the 7 parameters. Terms like file_path, dependent, fixed_effects, random_effects, distribution, link, and subject are not clarified or mapped to their meaning. The description does not compensate for the lack of schema documentation.

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 states a specific verb and resource: 'Run generalized linear mixed model combining GLM with random effects.' It adds distinguishing scope with 'non-normal outcomes' and 'hierarchical structure,' which helps separate it from spss_genlin and spss_mixed. It does not explicitly name those siblings, so it falls short of full 5-level differentiation.

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 description implies when to use it: for hierarchical data with non-normal outcomes. It also states the prerequisite that IBM SPSS Statistics must be installed. However, it gives no explicit when-not guidance or alternatives such as spss_genlin or spss_mixed, leaving selection logic largely to inference.

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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