Server Quality Checklist

Tool Scores

• list_citiesB
  3/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states what the tool does (returns a list) without detailing traits like whether it's read-only, has rate limits, requires authentication, or how it handles errors. This leaves significant gaps in understanding the tool's behavior.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is concise with two sentences, but it repeats the same information in Korean and English ('Returns: 사용 가능한 도시 목록'), which is redundant and wastes space. It could be more efficient by combining or eliminating the repetition while maintaining clarity.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's simplicity (0 parameters, no annotations, but has an output schema), the description is minimally adequate. It states the purpose but lacks behavioral details and usage guidelines. The output schema likely covers return values, so the description doesn't need to explain them, but overall completeness is limited due to missing context.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter semantics, so it appropriately avoids discussing inputs. The baseline for 0 parameters is 4, as there's no need for parameter explanation.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: '사용 가능한 도시 목록을 반환합니다' (Returns a list of available cities). It specifies the verb (returns) and resource (list of available cities), making the function unambiguous. However, it doesn't explicitly differentiate from the sibling tool 'get_weather', which likely serves a different purpose but could be related in context.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives. There is no mention of the sibling tool 'get_weather', nor any context about prerequisites, timing, or exclusions. Usage is implied by the purpose but lacks explicit instructions.

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

• get_weatherB
  3.1/5.0
  Behavior2/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It states it retrieves current weather information but doesn't mention whether this is a read-only operation, if it requires authentication, rate limits, error conditions, or what format the returned string contains. The description is minimal and lacks important behavioral context.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is appropriately concise with clear sections (Args, Returns). The first sentence states the purpose directly, and the parameter documentation is efficiently presented. There's minimal wasted text.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness3/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool has an output schema (though not shown here), the description doesn't need to explain return values in detail. However, for a tool with no annotations and only basic parameter documentation, the description could provide more context about what weather information is included, potential errors, or usage limitations to be fully complete.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters4/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The description adds significant value beyond the input schema. While the schema only shows 'city' as a string parameter with a default, the description provides a specific list of valid cities (서울, 부산, 인천, 대구, 대전, 광주, 울산, 제주) and clarifies it's a selection from this set. This compensates well for the 0% schema description coverage.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose: '특정 도시의 현재 날씨 정보를 가져옵니다' (Get current weather information for a specific city). It specifies the verb '가져옵니다' (get) and resource '날씨 정보' (weather information), though it doesn't explicitly differentiate from the sibling 'list_cities' tool.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus the sibling 'list_cities' tool. It doesn't mention prerequisites, alternatives, or contextual usage scenarios beyond the basic function.

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