Server Quality Checklist

Tool Scores

• get_weatherC
  2.3/5.0
  Behavior1/5

  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 only states the basic action ('gets and returns') without mentioning critical traits like data sources, accuracy, rate limits, error handling, or authentication needs. This is insufficient for a tool with no annotation coverage.

  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 front-loaded in a single sentence, with no wasted words. However, it's slightly under-specified, as more detail could improve clarity without sacrificing brevity. It efficiently states the core function but lacks depth.

  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 tool's complexity (simple but with no annotations or output schema), the description is incomplete. It doesn't explain return values, error cases, or behavioral context, leaving the agent with insufficient information to use the tool effectively beyond basic invocation.

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

  Parameters2/5

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

  The schema description coverage is 0%, so the description must compensate for undocumented parameters. It mentions 'city' implicitly but adds no meaning beyond what the schema title provides (e.g., format, examples, constraints). With 1 parameter and no schema descriptions, this leaves significant gaps.

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

  Purpose3/5

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

  The description states the tool's purpose ('gets and returns the weather of the city'), which is clear but vague. It specifies the action (gets/returns) and resource (weather), but doesn't differentiate from siblings or provide specific scope details like timeframe or data types. This is adequate but lacks precision.

  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. It doesn't mention sibling tools (add, fetch_news_articles) or contextual factors like when weather data is needed versus other data sources. Usage is implied by the purpose but not explicitly stated.

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

• addC
  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. 'Add two numbers' implies a simple computation but doesn't address potential issues like integer overflow, error handling, or output format. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

  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 at three words, with zero wasted text. It's front-loaded and directly states the tool's function without unnecessary elaboration, making it efficient and easy to parse.

  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 tool's simplicity (2 parameters, no annotations, no output schema), the description is minimal but inadequate. It doesn't explain the return value (e.g., sum as integer), error cases, or behavioral nuances. For even a simple tool, more context would improve agent understanding.

  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 0%, so the schema provides no parameter descriptions. The description 'Add two numbers' implies the parameters are numbers to be added, which adds basic semantic meaning beyond the schema's type definitions. However, it doesn't specify parameter roles (e.g., which is first/second) or constraints, leaving some ambiguity.

  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 'Add two numbers' clearly states the verb ('Add') and resource ('two numbers'), making the purpose immediately understandable. It doesn't distinguish from sibling tools (fetch_news_articles, get_weather) since they're unrelated, but the purpose is specific 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 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. It doesn't mention any context, prerequisites, or exclusions. While the sibling tools are unrelated, the description offers no usage instructions beyond the basic operation.

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

• fetch_news_articlesB
  3.3/5.0
  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 states the tool fetches and returns data, implying a read-only operation, but doesn't mention critical behaviors like rate limits, authentication requirements, error handling, or pagination. For a tool with 4 parameters and no annotation coverage, this leaves significant gaps in understanding how it behaves in practice.

  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 well-structured and appropriately sized. It starts with a clear purpose statement, followed by a parameter list with helpful details, and ends with return information. Every sentence adds value, though it could be slightly more concise by integrating the return statement into the opening sentence.

  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 (4 parameters, no annotations, no output schema), the description is partially complete. It excels in parameter documentation but lacks behavioral context (e.g., error cases, performance limits) and doesn't detail the structure of returned dictionaries. Without an output schema, more information on return values would be beneficial for full completeness.

  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?

  The description adds substantial meaning beyond the input schema, which has 0% description coverage. It explicitly documents all 4 parameters with their purposes and formats (e.g., 'earliest_date (str): Earliest publication date in YYYY-MM-DD format'), and specifies the return type. This fully compensates for the schema's lack of descriptions.

  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: 'Fetches news articles from the WorldNewsAPI based on specified parameters and returns them as a list of dictionaries.' This specifies the verb (fetches), resource (news articles), and source (WorldNewsAPI). However, it doesn't differentiate from sibling tools (add, get_weather), which are unrelated to news fetching, so it doesn't need explicit 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 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. It doesn't mention any prerequisites, limitations, or scenarios where other tools might be more appropriate. The only context is the parameter list, which doesn't constitute usage guidance.

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