spss_repeated_measures_anova

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

No annotations are provided, so the description carries the full burden. It only mentions the requirement for IBM SPSS to be installed and the input structure. It does not describe what happens when run (e.g., output format, side effects, errors, or processing time).

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 sentences, front-loaded with the primary action, and every sentence adds value. It is concise and well-structured without unnecessary detail.

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 moderate complexity, and an output schema exists, so return values are presumably covered. The description gives enough to run the analysis but omits the optional pairwise parameter and any assumptions or limitations. It is minimally viable but lacks richer context.

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%, but the description adds meaning for the core parameters by explaining to provide a within-factor name, number of levels, and one variable per level. However, it does not explain the optional 'include_pairwise' parameter.

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 tool runs SPSS repeated-measures ANOVA (within-subject GLM), which is a specific verb+resource. It distinguishes from sibling tools like spss_anova and spss_glm_univariate by specifying the repeated-measures/within-subject design.

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 implies the use case (repeated measures) but provides no explicit comparison to alternatives or exclusions. It says to provide within-factor name, levels, and variables, but does not mention when to choose this over spss_mixed or regular ANOVA.

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