Server Quality Checklist

Tool Scores

• get_municipality_forecastA
  4/5.0
  Behavior4/5

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

  With no annotations provided, the description takes on the burden of conveying safety and behavior. It clearly indicates a read-only operation ('Get') and discloses the forecast window (up to 7 days) and data source (AEMET). It does not mention potential limitations like response format or external dependencies, but for a simple read tool 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 a single, front-loaded sentence that covers the essential aspects without fluff. Every phrase adds value: action, resource, scope, source, and identifier.

  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—one well-documented parameter and a clear read operation—the description is nearly complete. It covers the return type (daily forecast), time window, and data source. It lacks explicit differentiation from siblings, but the sibling names in the context signal provide that information.

  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 input schema already documents the sole parameter with 100% coverage, including format (5 digits), an example (28079 for Madrid), and a lookup URL. The description only adds 'INE code' which is redundant with the schema, providing no additional semantic meaning beyond the structured data.

  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 verb ('Get'), the resource ('daily weather forecast'), and the scope ('Spanish municipality from AEMET', 'up to 7 days'). It differentiates itself from sibling tools (station observation, weather warnings) by focusing on forecast for a municipality by INE code.

  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 use for municipality weather forecasts and mentions the 7-day limit, but it does not explicitly state when to use this tool versus get_station_observation or get_weather_warnings. No exclusions or alternative instructions are provided, leaving the choice to the agent based solely on tool names.

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

• get_station_observationA
  4/5.0
  Behavior3/5

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

  With no annotations, the description provides some behavioral context by disclosing the time window (~12 hours) and data types (temperature, wind, etc.). It does not mention potential error responses, data availability limitations, or return format details, which would increase transparency.

  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, well-structured sentence that front-loads the verb and resource, then adds specific detail. It is concise and every word adds value.

  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 simplicity (one parameter, no output schema), the description is largely complete: it explains what data is returned and for which time period. It could be enhanced by stating that the result is a list of hourly observations, but this is implied by 'hourly... data.'

  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% with a clear description of the idema parameter including example. The description adds no extra parameter semantics beyond what the schema already provides, so the 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 uses a specific verb 'Get' and identifies the resource clearly: hourly conventional observation data for a specific AEMET station. It distinguishes this tool from siblings (forecast, warnings) by focusing on observed data over a defined time window.

  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 clearly indicates that this is for past observation data (last ~12 hours) for a specific station, which implicitly differentiates it from forecast and warning tools. However, it does not explicitly mention when not to use it or name alternatives.

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

• get_weather_warningsA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so description carries full burden. It discloses that warnings are latest and active, and includes AEMET issuance, but does not explicitly state read-only nature, pagination, or behavior when no warnings exist. For a simple 'get' operation, 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?

  Single sentence that is front-loaded with the core action and resource, and includes useful details without digression. Every word earns its place.

  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?

  Tool has one parameter, no annotations, no output schema, but the description plus schema describe input and output adequately (CAP alerts converted to JSON is in schema). It could mention output format in description, but overall it is sufficiently complete for a simple lookup tool.

  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% with detailed description of the 'area' parameter including pattern and example. The main description's note about 'Spanish region or the whole country' adds a tiny bit of context but does not go beyond schema. Baseline 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?

  States verb 'Get' + resource 'latest active weather warnings (CAP alerts) issued by AEMET for a Spanish region or the whole country', and lists content fields (severity, phenomenon, affected zone, validity). Clearly distinguishes from sibling tools focused on forecasts and observations.

  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?

  Provides clear context: use for active warnings for a Spanish region or the whole country. Does not explicitly mention alternatives or exclusions, but the scope is well-defined and siblings differ in purpose.

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