Get health evidence summaries for a pollutant and population group.
Args: pollutant: "NO2", "PM2.5", "PM10", or "O3". population_group: "general", "children", "elderly", "respiratory", "cardiovascular", or "pregnant" (default "general").
Returns health effects document (markdown).
| Name | Required | Description | Default |
|---|---|---|---|
| pollutant | Yes | ||
| population_group | No | general |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description bears the burden of disclosure. It does state the output format ('Returns health effects document (markdown)') and the verb 'Get' implies read-only behavior. However, it lacks explicit mention of side effects, error behavior, or data sources, which would increase transparency further.
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 compact and well-structured: a one-sentence purpose, then a formatted Args block with valid values and default. Every line contributes useful information, with no redundancy or fluff.
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 two simple parameters and a single markdown output, the description covers allowed inputs, default, and output type. It lacks details about error conditions or edge cases, but given the low complexity, it is nearly 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?
The description goes far beyond the input schema by enumerating allowed values for both pollutant ('NO2', 'PM2.5', 'PM10', 'O3') and population_group ('general', 'children', etc.) and specifying the default. This provides essential semantic meaning that the schema (with only titles) lacks.
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 action ('Get health evidence summaries') and the resource ('pollutant and population group'), which distinguishes it from sibling kb_get_* tools that target other content types. The purpose is specific and unambiguous.
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 use when health evidence is needed, but it does not explicitly contrast with sibling tools like kb_get_guidelines or kb_get_practical_advice. There is no when-not guidance, leaving some ambiguity for an agent deciding between related knowledge-base tools.
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.
Three tools (assess_location_aq, get_current_aq, get_aqi_summary) all provide current air quality and health context, creating potential misselection. The assess tool is positioned as the default entry point, but the boundaries between detailed readings, AQI summary, and comprehensive assessment could confuse an agent. Other tools are more clearly distinct.
Most tools follow a verb_noun pattern (get_current_aq, list_monitors, chart_aq_trend), but three use noun phrases (regulatory_stats, time_patterns, trend_analysis). The kb_ prefix is used consistently for knowledge base lookups. Overall conventions are mostly consistent with minor deviations.
15 tools is at the upper end of the ideal range and each serves a distinct function within the air quality domain, from current conditions to historical trends, comparisons, and regulatory compliance. No tool feels redundant, and the count is appropriate for the server's stated purpose.
The tool set covers current conditions, historical data, trend analysis, temporal patterns, location comparisons, regulatory statistics, monitor discovery, and a knowledge base for guidelines, health effects, and practical advice. This is a comprehensive surface with no glaring missing operations for the domain.