Spss Logistic Regression

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

With no annotations, the description carries the full behavioral burden. It discloses the supported modeling features and the environment requirement, which is real value, but says nothing about side effects (whether save_predicted writes new variables into the dataset, whether output files are created), permissions, or failure modes for stepwise selection.

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, front-loaded sentences with no filler; the capability statement leads and the environment prerequisite trails. It is efficient, though it stops short of using the remaining space for the parameter guidance this tool actually lacks.

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?

An output schema exists, so return values need not be explained. But for an 8-parameter statistical procedure with zero schema descriptions, the description leaves the agent without enough information to call it correctly (e.g., accepted values for contrast or print_options, meaning of file_path, behavior of save_predicted).

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% across 8 parameters, so the schema documents nothing. The description only loosely gestures at three of them (stepwise -> method, categorical -> categorical, diagnostics -> print_options); contrast, file_path, dependent, predictors, and save_predicted get no meaning, format, or accepted values, so the agent cannot reliably populate them.

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 gives a specific verb and resource ('Run binary or multinomial logistic regression'), and the 'binary or multinomial' qualifier distinguishes it from the sibling spss_ordinal_regression and from the generic spss_regression. An agent can route to this tool without opening the schema.

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 names supported features ('stepwise selection, categorical predictors, and model diagnostics') and states a hard prerequisite ('Requires IBM SPSS Statistics to be installed'), which implies when the tool is usable. However, it never says when to prefer this over spss_regression or spss_ordinal_regression, nor any exclusions or data requirements.

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