spss_kaplan_meier

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

No annotations are provided, so the description carries the behavioral burden. It discloses an important prerequisite (IBM SPSS Statistics must be installed) and describes the produced results. It does not discuss side effects or failure behavior, but for an analysis command the read-only nature is reasonably implied.

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 sentences with no filler. The action and outputs are front-loaded, the prerequisite is placed at the end, and nothing repeats the schema's structural information.

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 output schema covers return values, but the description still leaves gaps around parameter semantics, especially status_event_value and optional strata/percentiles. For a well-known statistical method, the description is minimally adequate, though it could be more useful with explicit guidance on event/censoring coding and comparison methods.

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%, yet the description adds almost no parameter-level meaning. It does not explain status_event_value, strata, percentiles, or compare_method beyond what the names and enum already suggest, so it fails to compensate for the schema's lack of descriptions.

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 names the exact statistical procedure ('Kaplan-Meier survival analysis') with a clear verb ('Run') and states the main outputs: survival curves and group comparison. This distinguishes it from sibling tools like spss_cox_regression and other analysis procedures.

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 description gives clear context by specifying survival analysis with a log-rank test and group comparison. It does not explicitly mention when to choose it over alternatives like cox_regression, but the statistical context is clear enough for an informed agent.

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