Spss Glm Univariate

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

No annotations are provided, so the description carries the full burden, and it does disclose one useful environmental prerequisite (SPSS installation). It says nothing about side effects such as file mutation or the save_predicted parameter writing new columns, nor about output format or failure modes, leaving meaningful behavioral gaps for a statistical procedure.

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?

Three short, front-loaded sentences with no filler; the core capability leads and the prerequisite trails. Efficiently sized for the information offered, though some brevity comes at the cost of missing parameter detail.

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?

An output schema exists, so return values need not be explained. But with zero annotation coverage, zero schema descriptions, and 8 parameters, the description is not complete enough for reliable invocation – it omits argument semantics and any sibling differentiation.

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% for 8 parameters, so the description must compensate. It loosely maps to emmeans, posthoc/posthoc_method, and factors ('factorial designs'), but leaves file_path, dependent, covariates, and save_predicted completely undocumented in both schema and description.

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?

States a specific verb and resource ('Run univariate general linear model (GLM) with factorial designs') and names the capabilities it covers (EMMs, contrasts, post-hoc). It is distinguishable from multivariate siblings like spss_manova, though it never explicitly contrasts itself with spss_anova or spss_genlin, which an agent could easily confuse it with.

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?

Implied usage is present – factorial designs plus EMMs/contrasts/post-hoc signal when the tool is appropriate, and it notes the prerequisite that IBM SPSS Statistics must be installed. However, it names no alternative sibling (spss_anova, spss_genlin, spss_mixed) or the conditions that would route an agent elsewhere.

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