Get plain-language explanations of monitoring methods and limitations.
Args: topic: One of "how_monitors_work", "regulatory_vs_lowcost", "what_readings_mean", "why_numbers_differ", "representativeness", "data_quality", "what_monitors_measure".
Returns monitoring explainer document (markdown).
| Name | Required | Description | Default |
|---|---|---|---|
| topic | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses the return format (markdown document) and lists the allowable topic values, which is helpful. However, it does not explicitly state that the operation is read-only, what happens on invalid input, or any other behavioral traits. The tool appears safe, but the description omits this context.
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 concise and well-structured, with a brief purpose statement followed by a list of accepted topic values and a clear return type. Every sentence adds value and there is no redundant information. The front-loaded purpose statement ensures quick understanding.
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 retrieval tool with one parameter, the description covers the essential inputs and outputs. The presence of an output schema likely explains the return document's contents, so the description need not elaborate further. Minor gaps remain around error handling, but these are not critical for such a straightforward tool.
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 schema provides only the parameter name 'topic' with no description or enum, resulting in 0% coverage. The description compensates by enumerating all acceptable values, which gives the agent concrete options. While it doesn't explain the meaning of each topic, the labels are largely self-explanatory and the compensation is effective.
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's purpose: providing plain-language explanations of monitoring methods and limitations. This distinguishes it from sibling KB tools like kb_get_health_effects or kb_get_guidelines, which focus on different topics. The specific verb 'get' and resource 'explanations of monitoring methods' make the intent explicit.
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 for questions about monitoring methods and their limitations, but it does not explicitly mention when to use this tool over siblings. No alternatives or exclusions are provided. The allowed topics give some contextual guidance, but the usage guidelines remain implicit rather than clearly stated.
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.