spss_crosstabs

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

With no annotations provided, the description carries the full transparency burden. It discloses the external dependency (SPSS must be installed), the action (run CROSSTABS), and optional behavioral components (chi-square, row/column percentages). This is adequate for a non-destructive statistical tool, though it does not discuss side effects or detailed failure modes.

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 concise sentences, front-loaded with the primary action and output. Every sentence adds meaningful information, and there is no redundancy or filler.

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 6-parameter tool with no schema descriptions, the description covers the core purpose, variable roles, optional analyses, and a critical prerequisite. The output schema likely covers return structure. It omits explicit guidance on file_path format or variable-level restrictions, but overall it is complete enough for effective tool selection and 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?

The schema has 0% description coverage, so the description must compensate. It clarifies that row_variable and column_variable are categorical and that the three boolean flags correspond to chi-square and row/column percentages. It does not explain file_path, but the parameter name is self-explanatory.

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 a specific verb and resource ('Run SPSS CROSSTABS') and clearly defines the output as a 'contingency table between two categorical variables.' This distinguishes it from sibling statistical tools like correlations or t-tests, which target different variable types and analyses.

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 clearly states the intended use case: analyzing the relationship between two categorical variables. It does not explicitly name alternative tools or exclusion criteria, but the categorical-variable framing provides sufficient usage context among the statistical sibling tools.

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