Server Quality Checklist

Tool Scores

• generate-imageA
  3.6/5.0
  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 mentions the API and model but lacks any details on output format, latency, rate limits, authentication, or failure behavior. This is a significant gap for a tool that generates an image.

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

  Conciseness5/5

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

  The description is a single concise sentence that includes the essential API and model context without unnecessary fluff. It is well-structured and front-loaded with the main action.

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

  Completeness2/5

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

  Given the absence of an output schema and annotations, the description should explain what the tool returns (e.g., image URL, binary data). It does not, leaving a key gap for users. The tool's simple nature doesn't excuse this omission.

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

  Parameters3/5

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

  The schema provides 100% coverage with clear descriptions for both parameters (prompt and num_inference_steps). The description adds no additional parameter semantics, so it matches the baseline of 3.

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

  Purpose5/5

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

  The description clearly states the tool generates an image from a text prompt using the HuggingFace Inference API, naming the specific model (FLUX.1-schnell). This verb+resource+scope is specific and distinguishes it from siblings like geocode, get-weather, etc.

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

  Usage Guidelines4/5

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

  While no explicit alternatives are mentioned, the tool's purpose is clear and distinctly different from its siblings. The description implies usage for image generation, which is contextually unambiguous given the sibling list.

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

• calcA
  3.7/5.0
  Behavior2/5

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

  No annotations are provided, so the description must carry the full behavioral burden. It mentions the core function (returns arithmetic result) but lacks disclosure of edge cases such as division by zero, handling of invalid inputs, or error behavior. This is a significant gap for a mutation-like operation that could fail.

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

  Conciseness5/5

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

  The description is a single, concise sentence that gets straight to the point. Every word contributes to the meaning, with no redundancy or filler.

  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?

  The tool is simple and an output schema exists, so return values are covered. However, the description does not mention potential errors or limitations (e.g., division by zero), which is important for a tool with no annotations. It is adequate but could be more complete.

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

  Parameters3/5

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

  Schema coverage is 100% (all parameters have descriptions), so the baseline is 3. The description merely paraphrases the parameters ('두 숫자와 연산자') without adding extra meaning, format details, or clarifications beyond what the schema already provides.

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

  Purpose5/5

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

  The description clearly states the tool's function: taking two numbers and an operator and returning the arithmetic result. It uses a specific verb ('입력받아 ... 반환합니다') and identifies the resource (calculator). It also distinguishes itself from sibling tools like geocode or get-weather, which are unrelated.

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

  Usage Guidelines4/5

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

  The description implies the tool should be used for arithmetic calculations, and sibling tools are unrelated, so there is no ambiguity. However, it does not explicitly state when not to use it or mention any exclusions (e.g., 'for non-arithmetic operations use another tool'), so it falls short of a 5.

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

• greetA
  3.9/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden. It states the core behavior (returns a greeting) but does not disclose details like output formatting, error handling, or whether there are side effects. For a simple tool, this is acceptable but not exceptional.

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

  Conciseness5/5

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

  The description is a single, concise sentence that covers the tool's purpose without any extraneous words. It is front-loaded with the core action and efficiently communicates the essential information.

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

  Completeness5/5

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

  For a simple tool with a complete input schema and an output schema, the description is sufficient. It explains the function clearly, and the remaining details are covered by the structured fields, leaving no significant gaps.

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

  Parameters3/5

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

  The schema provides complete descriptions for both parameters (name, language) with enums and defaults. The description merely restates that they are inputs and does not add additional semantic context beyond the schema, so the baseline score of 3 is appropriate.

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

  Purpose5/5

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

  The description clearly states the tool returns a greeting based on a name and language, using a specific verb (반환합니다) and a clear resource (greeting). This is distinct from sibling tools like geocode or get-weather, making its purpose unambiguous.

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

  Usage Guidelines3/5

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

  The description implies usage when a greeting is needed, but it does not explicitly state when to use this tool versus alternatives. Since sibling tools are unrelated, no exclusions are necessary, but explicit guidance is absent.

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

• geocodeA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses that the tool uses the Nominatim OpenStreetMap API, implying an external network dependency, but does not mention rate limits, attribution requirements, or fallback behavior. This is moderate context but not comprehensive.

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

  Conciseness5/5

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

  The description is a single, concise sentence with an appositive clarifying the API. It front-loads the action and result, with no wasted words or redundant detail.

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

  Completeness4/5

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

  With a low-complexity tool, one fully described parameter, and an output schema (which presumably defines the coordinate structure), the description covers the core use case. It could mention usage policy or rate limits for the external API, but that is optional for basic invocation.

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

  Parameters3/5

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

  Schema description coverage is 100%, with the query parameter fully described including examples. The description adds little beyond the schema—it restates that city names or addresses are accepted—so a baseline of 3 is appropriate.

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

  Purpose5/5

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

  The description clearly states the verb 'returns' coordinates (latitude/longitude) from a city name or address, which distinguishes it from sibling tools like get-weather or generate-image. The resource and output are explicit and unambiguous.

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

  Usage Guidelines4/5

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

  The description implies the tool is for geocoding queries and mentions the underlying API, giving clear context. However, it does not provide explicit when-to-use or when-not-to-use guidance, though no similar sibling tool exists to differentiate against.

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

• get-weatherA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the behavioral disclosure burden. It mentions the use of the Open-Meteo API and the dual output (current + daily), but does not disclose potential limitations like data freshness, error behavior, or rate limits. For a read-only weather tool, this 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.

  Conciseness5/5

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

  The description is a single, compact sentence that is front-loaded with the core function. Every word adds value with no redundancy or filler.

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

  Completeness4/5

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

  The tool is simple and the description covers the essential purpose. Since an output schema exists, the need to describe return values is reduced. It doesn't mention edge cases or prerequisites, but the complexity is low, making the description reasonably complete.

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

  Parameters3/5

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

  The schema covers 100% of parameters with individual descriptions, so the description adds little beyond confirming the role of the forecast period as the forecast duration. Baseline of 3 is appropriate since the schema does the heavy lifting.

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

  Purpose5/5

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

  The description clearly identifies the tool as a weather data retriever using latitude/longitude and forecast period, specifying it returns both current conditions and daily forecasts. This distinguishes it from sibling tools like geocode or time.

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

  Usage Guidelines4/5

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

  The description implies the intended use case: obtaining weather for a given location and forecast range. It doesn't explicitly state when not to use it or mention alternatives, but there are no competing weather tools among the siblings, so the context is clear.

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

• timeA
  4.5/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden. It clearly discloses the two behavioral modes (with city and without city), which is the key behavioral nuance. It does not mention edge cases or errors, but for a simple read-only time lookup, this is adequate.

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

  Conciseness5/5

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

  The description is two short sentences, front-loaded with the primary purpose. Every word earns its place, and there is no redundancy.

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

  Completeness5/5

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

  Given the presence of an output schema and the simplicity of the tool, the description covers all essential aspects: what it does and how the parameter affects behavior. It does not need to explain return values because the output schema handles that.

  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 schema already fully documents the 'city' parameter with enum values and descriptions (100% coverage). The description adds semantic value by explaining that omitting the city returns the full list, which complements the default='all' in the schema.

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

  Purpose5/5

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

  The description clearly states the tool returns the current time for a specific city, using the specific verb '반환합니다' (returns) and resource '특정 도시의 현재 시간' (current time of specific city). It also explains the fallback behavior when no city is specified, which distinguishes it from sibling tools like get-weather.

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

  Usage Guidelines4/5

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

  The description implies when to use the tool: when you need the current time for a city. It also clarifies the behavior when no city is provided (returns full list). However, it does not explicitly mention alternatives or exclusions, so it stops short of a 5.

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