Public water systems serving a US state + county and/or city, with health-based SDWA violation summaries. Matching is approximate (service boundaries are not public); the user's water bill names their actual utility.
| Name | Required | Description | Default |
|---|---|---|---|
| city | No | City served (optional) | |
| state | Yes | Two-letter state code, e.g. MD | |
| county | No | County name (optional) |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It honestly discloses the approximate nature of matching, the fact that service boundaries are not public, and suggests the user's water bill as a reliable source. This is valuable transparency beyond what the schema provides, though it does not cover potential edge cases or response details.
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 extremely concise: two sentences with no redundant filler. The first sentence states the core purpose, and the second adds a crucial caveat. Every word earns its place.
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 simple 3-parameter lookup with no output schema, the description conveys the essential result content (public water systems with violation summaries) and the approximation caveat. It does not explain the response structure or specific fields, but the level of detail is adequate for an agent to understand expected outcomes.
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?
The input schema already provides 100% coverage for all three parameters (state, city, county), so the baseline is 3. The description adds minimal extra meaning beyond the schema, only mentioning the combination of state plus county and/or city. It does not elaborate on parameter formats or edge cases.
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 returning public water systems and their health-based SDWA violation summaries for a given state, county, and/or city. The specific resource type and domain are clear, but it lacks an explicit verb like 'list' or 'find.' It distinguishes from the sibling tool 'environment_near' by focusing on drinking water systems.
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 tool should be used to look up water utilities based on location, and the caveat about approximate matching provides context on how to interpret results. However, it does not explicitly state when to prefer this tool over 'environment_near' or mention any exclusions. The advice to consult the water bill is a useful guidance element.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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The three tools clearly address different intents: drinking water system lookups, comprehensive due-diligence scoring, and nearby federal facility records. However, due_diligence and environment_near both cover Superfund and contamination data, so an agent might need to read descriptions carefully to choose between a composite score and raw nearby-site records.
Names are descriptive and readable but follow no consistent structural pattern: drinking_water is a noun phrase, due_diligence is an idiom, and environment_near is a noun with a preposition. While all are lowercase snake_case, the lack of a shared verb_noun or other uniform convention prevents higher consistency.
Three tools is within the well-scoped 3-15 range and each tool earns its place by covering a distinct aspect of environmental screening. There are no redundant or throwaway tools.
The set covers drinking-water compliance, broad property due-diligence scoring, and nearby federal contamination records, which form a coherent baseline for environmental site assessment. Gaps such as direct air-quality monitoring or detailed facility-level lookups are partially mitigated by the due_diligence and environment_near tools, but they are not fully addressed.