Server Quality Checklist

Tool Scores

• get_weather_forecast_content_israelA
  4/5.0
  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 only states that it extracts text content, but does not mention side effects, permissions, whether it depends on prior state beyond the stated step, or any potential errors. For a read-like operation, it is missing a safety profile or behavioral caveats, similar to the update_drive example.

  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, completely free of redundancy. It front-loads the action and then gives the sequence dependency. Every word earns its place, achieving maximum conciseness with clear structure.

  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 zero parameters and an output schema (though not shown), the description need not explain return values. It provides the necessary step number and the prerequisite action. It does not address failure conditions or side effects, but for a simple extraction step, the context is sufficient. A 4 reflects that it covers the essentials without over-explaining.

  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 zero parameters and the schema coverage is trivially 100%. With no parameters, the description cannot add parameter meaning, but it does refer to the preceding step to clarify the context of the 'loaded city weather page'. The baseline of 4 is appropriate given the zero-parameter case.

  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 'extracts' and the resource 'text content from the loaded city weather page', distinguishing it as a specific step in the workflow. Its purpose is unambiguous and it does not overlap with the sibling tools, which handle opening, entering, and selecting cities.

  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 gives an explicit precondition: 'Call this after select_weather_forecast_city_israel.' This clearly tells the agent when to use it. It does not mention when not to use it or name alternatives, but given the stepwise nature of the tool chain, this is adequate context for correct invocation.

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

• enter_weather_forecast_city_israelA
  4.1/5.0
  Behavior3/5

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

  With no annotations, the description carries the transparency burden. It clearly discloses that the tool types a city name into a search field, but it does not mention side effects such as whether it clears existing text, waits for suggestions, or submits the search. The behavior is adequately stated for a simple input action, but not deeply detailed.

  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 short and front-loaded with the action and step context. The Args block is minimal and directly maps to the single parameter; no unnecessary words or redundant schema repetition.

  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 one-parameter automation step with an output schema present, the description covers the essentials: what to enter, where, and in what format. The main gap is not explicitly referencing the surrounding workflow, but 'Step 2' provides enough orientation.

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

  Parameters5/5

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

  Schema coverage is 0%, so the description must add param meaning, and it does. It specifies that city_name must be in Hebrew and provides concrete examples ('ירושלים', 'תל אביב', 'חיפה'), which the schema completely omits.

  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 states a specific action ('Enters') on a specific resource ('the requested city name into the search field on the weather site'). This clearly differentiates it from siblings like select_weather_forecast_city_israel and get_weather_forecast_content_israel.

  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 explicit 'Step 2' marker gives some sequencing context, implying this runs after opening the site and before selecting a result. However, it does not name alternatives, state when not to use it, or describe the relationship to sibling tools directly.

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

• open_weather_forecast_israelA
  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 behavioral disclosure burden. It transparently describes the browser-opening and navigation side effect, plus the prerequisite relationship to later city-search actions. It does not detail potential failures or browser state, but for a zero-parameter navigation step this is reasonably transparent.

  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?

  Two short sentences deliver the key behavior and the usage order with no filler. The 'Step 1' label front-loads the workflow position effectively.

  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 zero-parameter setup tool with an output schema and sibling tools indicating the surrounding workflow, this description is complete. It tells the agent what the tool does, when to call it, and how it fits before city-related operations.

  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 input schema is empty, so the baseline is 4. There are no parameter semantics to clarify, and the description sensibly does not invent any.

  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 states a specific action ('opens the browser and navigates to the Israel weather forecast homepage') and identifies it as the first step in a workflow. This clearly separates it from sibling tools that handle city entry, selection, or content retrieval.

  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?

  It explicitly says to call this tool first before searching for a city, giving a clear sequential usage instruction. However, it does not name the sibling alternatives or state explicit when-not-to-use conditions beyond the sequencing.

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

• select_weather_forecast_city_israelA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description carries the transparency burden. It discloses the action (selecting a city result), the target (first result), and the prerequisite (after entering the city). It does not mention failure cases, but for a simple selection step 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 sentences with no filler. It front-loads the action and workflow step, then adds the only necessary sequencing instruction. Every sentence earns its place.

  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 zero-parameter UI interaction step, the description is complete: it names the step, the action, the target, and the required preceding tool. The output schema covers return values, so no additional output documentation is needed.

  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 zero parameters and an empty input schema, so the description does not need to document parameter behavior. The baseline of 4 applies because no parameter explanation is required.

  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 ('Selects') and a concrete resource ('the first city result from the autocomplete dropdown list'). It also distinguishes itself from the sibling enter_weather_forecast_city_israel by clarifying that this tool selects rather than enters a city.

  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 explicitly states when to call the tool: 'right after enter_weather_forecast_city_israel.' It provides clear workflow context but does not explicitly name alternatives or state when not to use it.

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