spss_t_test

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

With no annotations, the description must carry the burden. It notes that IBM SPSS Statistics must be installed, which is a key prerequisite, and lists supported test types, but it doesn't disclose error behavior or parameter relationships.

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?

A single sentence with no filler; it front-loads the verb and resource and includes only core 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?

Given the tool's complexity (5 params, 3 required, and types with different parameter needs), this description is too thin to guide correct usage. It doesn't explain which params apply to which test type or how to structure the variables array.

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?

The input schema has zero descriptions for its 5 parameters, and the description only partially illuminates test_type by naming its three enum values. File path, variables, test_value, and grouping_variable remain obscure.

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 clearly states the action ('Run SPSS t-test') and lists the three supported test types, which distinguishes it from sibling statistical tools.

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?

It implies usage for t-tests by naming the tool and enumerating supported types, but it doesn't explicitly state when to prefer this over alternatives like ANOVA or nonparametric tests.

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