Real-time air quality by district

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral disclosure burden. It reveals one key behavior: omitting the district parameter returns all 25 districts. It also notes that data is real-time and includes specific metrics (PM10/PM2.5, grade). However, it does not describe the output structure, error handling, or any broader behavioral traits, so transparency is adequate but not rich.

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 front-loaded: the first sentence gives the core purpose, the second covers the optional scope, and the Korean text provides a usage example. Every sentence earns its place, and the structure is easy to scan. It is concise without being under-specified.

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 the tool's simplicity (one optional parameter, no output schema), the description is largely sufficient. It explains the tool's purpose, the data returned, and the option to fetch all districts. However, it does not specify the exact return format or any authentication/rate limits, which would improve completeness—though for a read-only, low-complexity tool, this is a minor gap.

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 a full description for the 'district' parameter: '자치구명 (예: "강남구") — 생략 시 25개 전체', which covers the omit behavior. The tool description essentially repeats this with 'Omit district to get all 25', adding no new semantic information. Since schema coverage is 100%, the description's redundant repetition yields no extra credit.

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 states a specific action: 'Get real-time air quality (PM10/PM2.5, grade) for Seoul districts.' It clearly identifies the resource (Seoul districts) and the data captured (PM10/PM2.5, grade), and the clause 'Omit district to get all 25' further distinguishes it from sibling tools like get_weather or get_city_snapshot. This is a clear, unambiguous purpose.

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 provides a clear usage context: it is intended for air quality queries about Seoul districts, with the example question '"오늘 강남구 미세먼지 어때?" 류 질문에 사용.' This tells an agent when to invoke the tool. However, it does not mention when not to use it or name alternative tools, so it lacks explicit exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.