hotspot_analysis

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

No annotations exist, so the description should explain behavior. It does not mention side effects (e.g., output creation), permissions, performance, or whether it is read-only. The single sentence is insufficient.

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 very concise (one sentence) and to the point, but it lacks structure and omits essential information. While brevity is good, it sacrifices completeness.

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 the tool has nested parameters and an output schema, the description is severely incomplete. It does not explain input/output, supported geometries, or results, making it hard for an agent to use correctly.

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%, meaning the description adds no parameter details. Although the schema itself includes descriptions for some parameters (e.g., input_field, distance_band), the tool description fails to elaborate on how to use them, leaving the agent without necessary context.

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 names the specific statistical method (Getis-Ord Gi*) and the result (hot/cold spot clustering), clearly indicating the tool's purpose. However, it does not distinguish from sibling tools like spatial_autocorrelation, which also analyze 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?

No guidance on when to use this tool versus alternatives, no prerequisites, data requirements, or context provided. The description is too brief to inform selection.

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