Plain-English explanation of an EPA contaminant by name or code: the EPA name, whether the EPA classifies it as health-based, and how often it appears in our records. Not medical advice.
| Name | Required | Description | Default |
|---|---|---|---|
| contaminant | Yes | Contaminant name or EPA code, e.g. 'TTHM' or '2950'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, indicating a safe, read-only operation. The description adds that the output includes classification and frequency, and includes a disclaimer. No additional behavioral traits (e.g., data source, update frequency) are disclosed beyond annotations.
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?
Two sentences with no filler. The first sentence states purpose and output, the second adds a disclaimer. 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?
Given a simple tool with one fully described parameter and no output schema, the description sufficiently explains what the tool returns (EPA name, health classification, frequency). It could mention data scope or limits, but is otherwise complete.
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 coverage is 100% and the parameter description already explains the input (name or code with examples). The tool description's mention of 'by name or code' adds no new semantics beyond the schema. Baseline of 3 is appropriate.
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 states the tool provides a plain-English explanation of an EPA contaminant, listing the specific output fields (EPA name, health classification, frequency). It distinguishes from sibling tools which focus on cities, water systems, or general search.
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 usage when needing contaminant info but provides no guidance on when to use this tool versus alternatives like 'search' or 'get_city_water'. The disclaimer 'Not medical advice' is a boundary but not usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Multiple tools have overlapping purposes: `search` and `search_cities` both find cities by name, and `fetch` and `get_city_water` both retrieve EPA records for a city. This creates ambiguity for an agent deciding which tool to use.
Most tools follow a verb_noun pattern (e.g., compare_cities, get_city_water), but `fetch` and `search` are single-word imperatives without an object, breaking the consistency slightly.
With 10 tools, the server is well-scoped for a data retrieval domain. Each tool has a distinct role, though some overlap could be consolidated, the count is reasonable.
Core operations (search cities, fetch records, compare, list states) are covered, but the redundancy between `fetch`/`get_city_water` suggests unclear boundaries, and there is no tool to search by water system name or list all contaminants.