spss_genlinmixed

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

No annotations are provided, so the description carries the full behavioral disclosure burden. It only states that the tool 'runs' a model and requires SPSS to be installed; it does not disclose whether the operation modifies data, writes files, or produces specific outputs. The behavioral traits of execution are left largely unspecified.

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

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

The description is short and front-loaded, with the model type in the first sentence and the key prerequisite in the final clause. It is concise and well-ordered, though it uses its brevity to omit substantive guidance.

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

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

For a complex modeling tool with 7 parameters and multiple sibling model types, the description is materially incomplete. It does not clarify parameter roles, when to select this over spss_genlin or spss_mixed, or what running the model implies operationally. Although an output schema exists, the missing parameter and usage context makes the definition insufficient for correct invocation.

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

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

Schema description coverage is 0%, and the description mentions no parameters by name or semantic role. It never explains file_path, dependent, fixed_effects, random_effects, link, subject, or distribution, so it does not compensate for the lack of schema-level documentation at all.

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

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

The description uses the specific verb 'Run' with the resource 'generalized linear mixed model combining GLM with random effects.' It explicitly identifies the model type and distinguishes it from sibling tools like spss_genlin and spss_mixed by noting it combines GLM with random effects, making the purpose clear and differentiated.

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

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

The phrase 'Supports non-normal outcomes with hierarchical structure' implies when the tool is appropriate, but it does not explicitly state when to use this tool over spss_genlin, spss_mixed, or other modeling siblings, nor does it mention any exclusions. Usage context is implied rather than directly guided.

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