spss_weight

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

With no annotations, the description carries the burden and does disclose the key behavioral trait: the weighting persists for subsequent procedures on the same file. It also explains how to turn weighting off via weight_variable=None. It does not mention edge cases like missing or negative weights, but the core statefulness is covered.

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 each adding value: core operation, persistence semantics, and environment requirement. The most decision-relevant information, the off switch and statefulness, appears early.

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 two-parameter stateful tool, the description covers the essential call semantics and the persistence behavior that affects downstream procedures; the output schema covers return values. File path format and variable reference conventions are left implicit, but the tool is simple enough that the agent can proceed.

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 has no parameter descriptions (0% coverage), so the description must compensate. It explains weight_variable's meaning and None sentinel, but leaves file_path to be inferred from its name and does not specify expected format or how variables are referenced.

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 identifies the action ('Weight cases') and the resource (a variable), plus the ability to turn weighting off. It is distinguishable from sibling analysis tools like spss_frequencies, but it does not explicitly name a comparable alternative or contrast with it.

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 states that the effect applies to subsequent procedures on the same file, which implies use before analyses that should account for weights. It does not explicitly say when not to use it or suggest alternatives such as spss_filter or spss_select_if for case selection.

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