Server Quality Checklist

Tool Scores

• find_weather_stationC
  2.9/5.0
  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 states the tool returns a list of stations with name, ID, and distance, which is helpful. However, it doesn't cover critical aspects like whether this is a read-only operation, potential rate limits, error conditions, or data freshness. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

  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 concise and well-structured, using two clear sentences that efficiently convey the tool's purpose and output. It avoids unnecessary details and is front-loaded with the main action. However, it could be slightly more polished in English translation (e.g., 'Nächstgelegene' as 'nearest'), but this doesn't significantly impact 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 moderate complexity (one parameter, no annotations, but with an output schema), the description is adequate but incomplete. It explains the output format (list with name, ID, distance), which is good since an output schema exists. However, it lacks details on usage context, parameter specifics, and behavioral traits, making it minimally viable but with clear gaps for effective tool selection.

  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 description coverage is 0%, with one parameter ('location') undocumented in the schema. The description implies the parameter is a location for finding nearby stations but doesn't specify format (e.g., coordinates, city name) or constraints. It adds some semantic context ('specified location') but doesn't fully compensate for the lack of schema documentation, aligning with the baseline for minimal parameter info.

  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: 'find nearest DWD weather stations' and 'returns a list of weather stations near the specified location'. It uses specific verbs ('find', 'returns') and identifies the resource ('DWD weather stations'). However, it doesn't explicitly differentiate from sibling tools like 'get_current_weather' or 'get_weather_forecast', which prevents a score of 5.

  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 like 'get_current_weather' or 'get_weather_forecast'. It mentions what the tool does but offers no context about use cases, prerequisites, or exclusions. This lack of comparative guidance limits its utility for an AI agent in selecting the right tool.

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

• get_weather_forecastB
  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 mentions the return format (hourly forecasts and daily summaries with min/max temperatures and precipitation totals), which is helpful. However, it doesn't address critical behavioral aspects like rate limits, authentication requirements, error conditions, or data freshness that would be essential for an agent to use this tool effectively.

  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 extremely concise and well-structured. The first sentence clearly states the core purpose, and the second sentence efficiently describes the return format. Every sentence earns its place with no wasted words, making it easy for an agent to parse quickly.

  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 that there's an output schema (which should document the return structure), the description doesn't need to explain return values in detail. However, for a weather forecast tool with 2 parameters and no annotations, the description should provide more context about parameter usage and behavioral constraints. The current description is adequate but leaves gaps in usage guidance and behavioral transparency.

  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 description provides no information about parameters beyond what's in the schema. With 0% schema description coverage, the schema only shows parameter names and types without explaining their meaning. The description doesn't compensate by explaining what 'location' should contain (e.g., city name, coordinates) or what 'days' represents. This meets the baseline for minimal parameter information.

  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: retrieving weather forecasts for a location. It specifies the verb 'abrufen' (retrieve) and resource 'Wettervorhersage' (weather forecast), making the intent unambiguous. However, it doesn't explicitly differentiate from sibling tools like get_current_weather, which prevents a perfect score.

  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. With siblings like get_current_weather and get_weather_alerts available, there's no indication of when this forecast tool is preferred over current conditions or alert tools. The description only states what it does, not when it should be used.

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

• get_current_weatherA
  3.8/5.0
  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 describes what data is returned (temperature, humidity, wind, precipitation, cloudiness) but doesn't mention important behavioral aspects like rate limits, authentication requirements, data freshness, or error conditions. For a tool with no annotations, this is a significant gap.

  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 perfectly concise and well-structured. Two sentences efficiently convey the purpose and return data. The first sentence states what the tool does, and the second enumerates the returned data types. Every sentence earns its place with no wasted words.

  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?

  Given the tool's simplicity (1 parameter, no annotations, but with output schema), the description is reasonably complete. The output schema will handle return value documentation, so the description appropriately focuses on purpose and data types. However, it could benefit from more behavioral context given the lack of annotations.

  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?

  With 0% schema description coverage and only 1 parameter, the description doesn't provide any specific information about the 'location' parameter beyond what's implied by the tool's purpose. However, for a single-parameter tool with clear purpose, the baseline is 4 as the description adequately conveys what information is needed without needing detailed parameter documentation.

  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 specific action ('Aktuelles Wetter für einen Ort abrufen' - retrieve current weather for a location) and resource (weather data). It distinguishes from siblings by focusing on current conditions rather than forecasts (get_weather_forecast), alerts (get_weather_alerts), or station finding (find_weather_station).

  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 for current weather data, but doesn't explicitly state when to use this tool versus alternatives. While the purpose differentiates from siblings, there's no explicit guidance about when to choose this over get_weather_forecast or other weather-related tools.

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

• get_weather_alertsA
  4.2/5.0
  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 key behavioral traits: it returns current warnings from DWD (data source), includes specific data fields (type, severity, description, validity period), and supports location-specific or nationwide queries. However, it doesn't mention rate limits, authentication needs, error conditions, or whether the data is real-time/cached.

  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 perfectly concise and front-loaded: the first sentence states the core purpose, the second explains what's returned, and the third clarifies parameter usage. Every sentence adds value with zero redundant information. The German text is efficiently structured.

  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?

  Given the tool's moderate complexity (weather alerts retrieval), no annotations, 1 parameter with 0% schema coverage, but WITH an output schema (so return values don't need description), the description is mostly complete. It covers purpose, return data, and parameter semantics adequately. The main gap is lack of behavioral details like rate limits or authentication, but the output schema handles return structure.

  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?

  With 0% schema description coverage (parameter 'location' has no description in schema), the description compensates well by explaining the parameter's purpose: 'Kann für einen bestimmten Ort oder deutschlandweit abgefragt werden' (can be queried for a specific location or nationwide). This clarifies that the location parameter is optional (null = nationwide) and what it controls. Since there's only 1 parameter, this is sufficient.

  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 purpose: 'Amtliche Wetterwarnungen abrufen' (retrieve official weather warnings) and specifies it returns current warnings from DWD including type, severity, description, and validity period. It distinguishes from siblings like get_current_weather (current conditions) and get_weather_forecast (future predictions) by focusing specifically on alerts/warnings.

  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 provides clear context for when to use this tool: for retrieving weather warnings, either for a specific location or nationwide. However, it doesn't explicitly state when NOT to use it or mention specific alternatives among the siblings (e.g., use get_current_weather for current conditions instead of warnings).

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