spss_moderation

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

With no annotations provided, the description carries the full burden for behavioral disclosure. It adds value by explaining that variables are mean-centred and that the interaction term is reported. However, it does not mention potential side effects like data modification or requirements like variable types/numeric ranges, so it is not fully transparent.

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 a single, front-loaded sentence that delivers the essential information without any wasted words. It is concise yet precise.

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 an output schema, so return values are covered by that. The description sufficiently describes the statistical method and purpose for an agent to select the tool correctly, but it could include assumptions like continuous moderator not being explicitly stated.

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. It clarifies the roles of x, moderator, and y through the model formula, but does not explain file_path or specify the expected input types (e.g., variable names vs. column indices). This is partial compensation.

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 ('Run'), names the resource ('mean-centred moderation regression'), and specifies the exact model formula (Y ~ X + W + X*W). It clearly states the output (interaction term) and differentiates from sibling tools like spss_regression and spss_mediation.

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 indicates the tool is for testing moderation effects, which implies when to use it. However, it does not explicitly mention when not to use it or name alternative tools (e.g., if only main effects are needed, use spss_regression).

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