Server Quality Checklist

Tool Scores

• get_current_weatherB
  3.3/5.0
  Behavior2/5

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

  With no annotations, the description must carry the full burden of behavioral disclosure. It only restates the purpose and input methods, without mentioning return format, default units, error behavior, or the fact that this is a read-only operation. No additional behavioral context is added beyond what the schema already implies.

  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 is front-loaded with the primary action and resource. It contains no filler, unnecessary qualifiers, or repetition, earning a perfect score for conciseness.

  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 relatively simple with 4 optional parameters all documented in the schema, but the description does not explain what 'current weather conditions' includes in the response, nor does it nod to sibling tools for differentiation. It is minimally complete for a straightforward read operation, but it lacks a clearer sense of the overall context.

  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%, so a baseline of 3 is appropriate. The description adds a small amount of context by linking 'city name' to the location parameter and 'coordinates' to latitude/longitude, but it does not clarify precedence (e.g., location is preferred) or units behavior, which are already in the schema, so no significant extra value.

  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 uses a specific verb ('Get') and identifies the resource ('current weather conditions'), while also specifying scope ('any location worldwide') and method ('by city name or coordinates'). It implicitly distinguishes from siblings like get_forecast by focusing on 'current' conditions, but does not explicitly name alternatives, so it loses a point for lack of direct sibling differentiation.

  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 context with 'any location worldwide' and 'current weather', but it provides no explicit when-to-use or when-not-to-use guidance, nor does it reference sibling tools like get_forecast or get_alerts. This gives a general sense of applicability but falls short of clear alternatives or exclusions.

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

• get_alertsA
  3.6/5.0
  Behavior3/5

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

  With no annotations available, the description carries the full burden. It discloses that the tool is limited to US locations and returns 'active' alerts, which adds context. However, it does not describe the output format, error behavior, or what constitutes 'active,' so transparency is partial.

  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 highly concise, consisting of two short sentences that communicate purpose and limitation with zero wasted words. It is well-structured and front-loaded with the core action.

  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?

  For a simple one-parameter, read-only tool, the description provides the essential context: what it does and a key limitation. It lacks guidance relative to sibling tools, but the tool is simple enough that the description is mostly 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 description coverage is 100%, with the parameter 'state' already described in the schema. The tool description adds no additional parameter semantics beyond what the schema provides, so 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?

  The description clearly states the tool's purpose: 'Get active weather alerts for a US state.' It uses a specific verb ('get') and resource ('active weather alerts') with a geographic scope, distinguishing it from sibling tools like get_current_weather and get_forecast.

  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 does not provide guidance on when to use this tool versus alternatives. It only mentions a constraint ('Only supports United States locations'), but no explicit when-to-use or when-not-to-use instructions are given.

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

• get_forecastA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries the burden of behavioral disclosure. It states the output is a 5-day forecast and supports city/coordinate input, but does not disclose unit defaults, precedence rules, or potential errors; the schema fills some gaps, so a 3 is a fair baseline.

  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 12-word sentence that is entirely information-bearing, with no filler. It front-loads the action and outcome, making it maximally concise.

  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 enough that this one-sentence description plus a well-described schema is adequate. It does not explain return data structure, but an output schema is not present and the forecast format is likely conventional. Sibling differentiation is absent but not critical here.

  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 covers 100% of parameters with detailed descriptions including defaults and constraints, so the description adds little beyond naming the two lookup modes. The baseline of 3 is appropriate because the schema already 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 states the tool returns a 5-day weather forecast using the verb 'get' and resource 'forecast', and specifies both the geographic scope ('any location worldwide') and input methods ('by city name or coordinates'). This distinguishes it from sibling tools like get_current_weather and get_alerts.

  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 multi-day forecasting, and the sibling names suggest alternatives for current conditions and alerts. However, it does not explicitly state when to prefer this tool over others or mention exclusions, so a 4 is appropriate.

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