Server Quality Checklist

Tool Scores

• random_numberB
  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 mentions that the tool 'generates' a random number, implying a read-only operation, but doesn't address important behavioral aspects like whether the generation is truly random, if there are any rate limits, or what happens with invalid input ranges. The description adds minimal behavioral context beyond the basic function.

  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 structured and concise. It begins with a clear purpose statement, then provides parameter documentation in a clean Args/Returns format. Every sentence earns its place, and there's no wasted verbiage. The information is front-loaded with the most important details first.

  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 low complexity (2 simple parameters) and the presence of an output schema (implied by 'Returns' section), the description is reasonably complete. It explains what the tool does, documents the parameters, and specifies the return value. However, it could be more complete by addressing potential edge cases or behavioral constraints.

  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 schema description coverage is 0%, so the description must compensate. It does this effectively by explaining both parameters: 'min_val: Minimum value (default: 1)' and 'max_val: Maximum value (default: 100)'. This adds clear meaning beyond what the bare schema provides, though it doesn't explain edge cases like what happens if min_val > max_val.

  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: 'Generate a random number within a range.' This is a specific verb+resource combination that tells the agent exactly what the tool does. However, it doesn't explicitly differentiate from the sibling 'add' tool, which appears to be a mathematical operation rather than a random number generator, so it doesn't fully address sibling distinction.

  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. There's no mention of when this tool is appropriate, what scenarios it's designed for, or how it compares to the sibling 'add' tool. The agent must infer usage from the purpose alone.

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

• addA
  3.7/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It states what the tool does (addition) and the return value, but doesn't disclose any behavioral traits like error handling, precision limits, overflow behavior, or performance characteristics that would be important for an arithmetic operation.

  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 appropriately sized with clear sections (Args, Returns). The main purpose is stated upfront, and each sentence serves a clear purpose. The structure could be slightly improved by integrating the parameter descriptions more naturally rather than as separate labeled sections.

  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 (2 integer parameters, no annotations, but has output schema), the description is reasonably complete. It explains what the tool does, what parameters mean, and what it returns. The output schema existence means the description doesn't need to detail return format, making this adequate for this simple arithmetic function.

  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, the description compensates by clearly explaining both parameters ('First number' and 'Second number'). While it doesn't provide format details beyond what the schema already shows (integers), it adds meaningful semantic context for each parameter.

  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 ('Add two numbers together') and identifies the resource (numbers). It distinguishes from the sibling tool 'random_number' by focusing on arithmetic addition rather than random generation.

  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 arithmetic addition but doesn't explicitly state when to use this tool versus alternatives. No guidance is provided about when not to use it or what other tools might be appropriate for different mathematical operations.

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