epa_drinking_water

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds no behavioral details beyond that—no mention of data coverage limitations, update frequency, pagination behavior, or how the open-world hint manifests. The system type definitions are semantic output context, not behavioral disclosure.

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 front-loaded with the core purpose, followed by a compact enumeration of return fields, then clarifications for system types, and a final cross-reference suggestion. It is efficient, but the system-type definition block is somewhat lengthy and could potentially be abbreviated without losing essential information.

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 tool with only two parameters and no output schema, the description is nearly complete. It states the output nature (public water systems), defines the key system type values, and suggests a concrete analytical use case. It does not describe the output structure (e.g., whether it is an array or object), but such information is not strictly necessary given the service's simplicity and the schema coverage for input.

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 100%—both `state` and `rows` have descriptions. The tool description adds no parameter-specific meaning beyond what the schema already provides; it does mention 'by state' but that is already in the schema's state description. The system type information is about return values, not parameters, so the description adds little to parameter semantics.

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 resource (SDWIS data), the scope (by state), and the returned fields (population served, source type, system type). It goes beyond the tool name by explaining the domain and the data semantics, and it is readily distinguishable from sibling EPA tools like epa_air_quality or epa_facilities.

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 makes the tool's use case explicit: retrieving public water system data for a state and cross-referencing with CDC and Census data for per-capita analysis. It does not name alternative tools or state when not to use it, but the context is clear enough for an agent to select it for drinking-water-related queries.

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