Multivariate Clustering

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

Annotations already declare this is not read-only, is idempotent, and is non-destructive. The description adds no behavioral context beyond restating configurable inputs; it does not disclose that output datasets are created, whether existing outputs are overwritten, or what permissions are required.

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 compact sentence with no filler and the main verb is front-loaded. Its brevity is not wasted, though it is arguably too terse given the tool's complexity.

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 9-parameter analysis tool with no schema descriptions and a write-like annotation profile, the description is far too thin. It does not explain required inputs, output creation behavior, or method choices, leaving major gaps even though an output schema exists for return values.

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 for 9 undocumented parameters. It mentions analysis fields, initialization method, cluster count, and an optional evaluation table, but leaves required inputs such as in_features, output_features, and the clustering method unexplained, which is insufficient.

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 states a specific verb and resource: '运行多变量聚类' (run multivariate clustering), and lists key configurable dimensions. It does not, however, distinguish this tool from similar siblings such as arcgis_pro_spatially_constrained_multivariate_clustering or arcgis_pro_multi_distance_spatial_clustering.

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 offers no when-to-use guidance, no prerequisites, and no alternatives. It only says the clustering run can be constrained by analysis fields, initialization, cluster count, and an optional evaluation table, which describes inputs rather than usage context.

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