spss_cox_regression

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

With no annotations available, the description carries the burden of behavioral disclosure. It provides useful context by naming the external installation requirement and describing supported analyses. It does not disclose side effects, failure behavior, or whether the operation writes files or modifies the input dataset, which leaves some behavioral ambiguity.

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 two sentences with no filler. The action and domain are front-loaded, followed by capability and prerequisite details that are relevant for invocation.

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?

The tool has 9 parameters, 5 required, with zero schema descriptions, and the description does not explain how to populate core fields beyond the procedure name. An agent cannot confidently determine status_event_value semantics, categorical variable treatment, or method choice from this definition. The presence of an output schema reduces return-value ambiguity but does not fill the invocation gaps.

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%, so the description must compensate, but it only alludes to stratification and time-dependent covariates. It does not clarify required parameters such as status_event_value, the method enum values (ENTER/FSTEP/BSTEP), categorical handling, or save_survival. The parameter names are somewhat self-explanatory, which prevents a score of 1.

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 identifies a specific procedure ('Cox proportional hazards regression') with a clear verb ('Run') and domain ('survival analysis'). It advertises distinctive capabilities like time-dependent covariates, stratification, and diagnostics, which separates it from most siblings by analytic method. It does not explicitly contrast with spss_kaplan_meier, but the named technique is unambiguous.

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 'for survival analysis' establishes the appropriate data context, and the IBM SPSS prerequisite tells the agent when the tool cannot be used. However, it does not explicitly state when to prefer this tool over survival-adjacent siblings like spss_kaplan_meier or over regression alternatives such as spss_logistic_regression. The usage guidance is implied rather than explicit.

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