Server Quality Checklist

Tool Scores

• web_searchC
  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. It mentions using Tavily API but doesn't describe key behavioral traits like rate limits, authentication needs, response format details beyond 'Search results context', or potential limitations (e.g., result freshness, source reliability). This leaves significant gaps for a tool performing external queries.

  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 and front-loaded, with the core purpose stated first. The 'Args' and 'Returns' sections add structure, though they could be integrated more seamlessly. Every sentence earns its place, but minor improvements in flow could enhance clarity without adding bulk.

  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 (external API call), lack of annotations, and presence of an output schema, the description is partially complete. It covers the basic purpose and parameters but misses behavioral details like error handling or usage constraints. The output schema existence reduces the need to explain return values, but more context on operation traits would improve completeness.

  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 description adds minimal semantics beyond the input schema. It defines 'query' as 'Search query string', which aligns with the schema's title 'Query' and type 'string'. With 0% schema description coverage, the description compensates slightly but doesn't elaborate on query formatting, length limits, or examples. The baseline is 3 since it provides basic meaning but lacks depth.

  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: 'Search the web for information using Tavily API.' It specifies the verb ('Search') and resource ('the web'), and mentions the underlying API. However, it doesn't explicitly differentiate from sibling tools like 'ask_specialized_claude' or 'roll_dice', which serve different purposes but aren't directly comparable search alternatives.

  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 or other search methods, nor does it specify contexts where web search is appropriate versus when it might not be (e.g., for internal data). Usage is implied by the purpose but lacks explicit guidelines.

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

• roll_diceA
  4.1/5.0
  Behavior3/5

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

  With no annotations provided, the description carries full burden. It discloses the core behavior (rolling dice with specific notation) and mentions the return format ('Formatted dice roll results'), but lacks details about error handling, rate limits, or specific formatting of outputs. The description doesn't contradict any annotations since none exist.

  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 efficiently structured with a clear purpose statement, parameter explanations in a labeled 'Args' section, and return information. Every sentence earns its place by providing essential information without redundancy. The information is front-loaded with the core functionality stated 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 moderate complexity (2 parameters, no annotations, but has output schema), the description is mostly complete. It explains parameters well and mentions return formatting. The output schema existence means it doesn't need to detail return values, but could benefit from more behavioral context about error cases or limitations.

  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 description coverage is 0%, so the description must compensate fully. It provides clear semantic explanations for both parameters: 'notation' is explained with examples and meaning ('2d20k1 = roll 2d20, keep highest 1'), and 'num_rolls' is explained with its default value and purpose. This adds significant value beyond the bare schema.

  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 ('Roll dice') with precise resource specification ('with D&D-style notation') and provides a concrete example ('e.g., 2d20k1'). It distinguishes itself from sibling tools like 'ask_specialized_claude' and 'web_search' by focusing on dice rolling functionality.

  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 through the example notation and default parameter, but doesn't explicitly state when to use this tool versus alternatives. No guidance is provided on when not to use it or what alternatives might exist for similar tasks.

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

• ask_specialized_claudeA
  4.6/5.0
  Behavior4/5

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

  With no annotations provided, the description carries full burden and does well. It discloses this is 'meta-AI' (Claude calling Claude), mentions different personas per task_type, includes error handling details (raises ValueError for unrecognized task_type, Exception for API failures), and describes the return format. It doesn't mention rate limits or auth specifics, but covers key behavioral aspects.

  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 well-structured and appropriately sized. It starts with a clear purpose statement, explains the meta-AI concept, details parameters with examples, and covers returns and errors. Every sentence adds value with zero waste, and it's front-loaded with the most important information.

  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?

  Given the tool's complexity (AI calling AI with multiple specializations), no annotations, and 0% schema coverage, the description is remarkably complete. It explains the tool's unique nature, all parameters thoroughly, provides examples, documents return values and errors. With an output schema present, it doesn't need to explain return format details, making this description comprehensive for its context.

  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?

  With 0% schema description coverage, the description fully compensates by explaining all 3 parameters. It defines 'prompt' as 'User input for Claude to process', lists all valid 'task_type' values with their purposes, and explains 'max_tokens' as 'Response length cap' with default and maximum values. This adds significant meaning beyond the bare schema.

  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: 'Call a specialized Claude model for targeted reasoning tasks.' It specifies the verb ('Call'), resource ('specialized Claude model'), and distinguishes it from sibling tools (roll_dice, web_search) by focusing on AI reasoning rather than random generation or web search.

  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 provides clear context for when to use this tool: for 'targeted reasoning tasks' with different 'task_type' specializations. It doesn't explicitly state when NOT to use it or name alternatives among siblings, but the specialization context is well-defined.

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