spss_quick_cluster

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

No annotations are provided, so the description must carry behavioral context. It discloses that save_cluster_variable creates a new variable and print_anova adds an ANOVA table, and it notes the SPSS requirement. However, it does not explain side effects on the dataset, missing-data handling, or failure behavior.

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 compact and uses a terse syntax-style format that conveys the core command and key options without excessive prose. The required-SPSS note is useful context, though the parameter explanations are embedded in a slightly scattered way.

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?

Given six parameters, no annotations, and an output schema, the description gives a usable but incomplete picture. It covers the main purpose and optional behaviors, but omits details like variable type requirements, missing data behavior, and guidance for selecting between cluster methods, leaving the agent to infer too much.

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 adds meaning by mapping n_clusters and max_iterations to CLUSTER(k) and MXITER(n), and it explains save_cluster_variable and print_anova. However, file_path and variables rely entirely on their self-explanatory names, with no further detail.

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 tool as performing K-means clustering and mentions the SPSS QUICK CLUSTER command. It explains what save_cluster_variable and print_anova do, but it does not explicitly differentiate this from sibling cluster tools like spss_cluster_hierarchical or spss_twostep_cluster.

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 provides the SPSS requirement and a command template but gives no guidance on when to choose this tool over alternative clustering methods. It does not state prerequisites such as numeric variables or when k-means is appropriate versus hierarchical or two-step clustering.

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