실시간 대기질(미세먼지, 초미세먼지, 오존 등)을 조회합니다.
Args:
location: 지역명 (예: "서울", "강남", "부산", "제주"). 15개 주요 지역 지원.
Returns:
PM10, PM2.5, 오존, 이산화질소, 일산화탄소, 아황산가스 수치와 등급
| Name | Required | Description | Default |
|---|---|---|---|
| location | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It discloses real-time behavior, location limitations, and the returned pollutant types/grades. It does not mention units, possible errors for unsupported locations, or data update cadence, but it covers the core behavioral contract.
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, front-loaded with the main purpose, and uses clean Args/Returns sections. Every sentence earns its place with no redundant filler.
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 single-parameter read-only lookup, the description provides enough to call the tool successfully for typical inputs. It could be improved by listing the 15 supported regions or pointing to list_supported_options, but the examples and return summary make it largely sufficient.
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 defines location only as a string with no documentation, so the description provides meaningful additional guidance: location type, examples like 서울/강남/부산/제주, and a 15-region support limit. It stops short of listing the exact supported regions, which would be more complete.
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 fetches real-time air quality data and enumerates specific pollutants (미세먼지, 초미세먼지, 오존 등). It names a distinct resource and is easily distinguished from siblings like get_weather_forecast or get_economic_stats.
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 gives practical location examples and notes that 15 major regions are supported, which implies usage context. However, it does not explicitly say when to prefer this tool over alternatives or how to confirm whether a particular location is supported.
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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