Server Quality Checklist

Tool Scores

• ai_chat_completionA
  4.2/5.0
  Behavior4/5

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

  Beyond having no annotations, the description discloses cost (1 credit base), no multipliers, caching behavior (expiration), and localization features. It does not detail rate limits or authentication requirements, but the provided information is sufficient for basic understanding.

  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, using short sentences and bullet-like lists to convey key points. It avoids redundancy and is well-organized for quick consumption, though it could be slightly more structured.

  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 9 parameters and no output schema, the description covers most aspects (model, caching, localization) but omits details on the output format beyond 'structured sources'. It meets minimum viability but leaves some ambiguity about return value structure.

  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 covers 100% of parameters with individual descriptions, but the tool description adds value by explaining expiration semantics, localization context, and cost implications. This enrichment goes beyond the schema's baseline.

  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 gets a chatbot answer from specific models (ChatGPT, Gemini, Perplexity, Copilot) and mentions structured sources. This distinct purpose is well-differentiated from sibling tools like 'account_status', 'web_fetch', and '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 guidance on using expiration for fresh vs cached responses and mentions localization parameters. However, it does not explicitly contrast with sibling tools or state when not to use this tool, though the distinct purpose makes such guidance less critical.

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

• web_searchA
  4.2/5.0
  Behavior4/5

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

  Despite no annotations, the description discloses cost (1 credit base, no multipliers), caching behavior via the expiration parameter, and localization options. It does not mention rate limits or error handling, but given the lack of annotations, it provides significant behavioral insight.

  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 brief and well-structured: outputs, cost, caching advice, localization. Every sentence adds value with no redundant or vague statements.

  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 description covers output structure, cost, caching, and localization. It does not mention error responses or pagination limits beyond max_results, but given the tool's simplicity and the schema's clarity, it is sufficiently complete.

  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?

  Schema coverage is 100%, baseline 3. The description adds value by explaining how to use expiration (0 for always-live, default reuses cached SERPs) and highlighting localization parameters (country, subdivision, city, language, display). This context goes beyond the schema descriptions.

  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 performs Google search and returns structured JSON results including organic results, AI overview, and 'people also ask' questions. It distinguishes from siblings (account_status, ai_chat_completion, web_fetch) as the only search-specific tool.

  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 provides usage tips for localization and caching but does not explicitly compare to sibling tools like web_fetch or state when to use this vs other approaches. The guidance is implicit rather than explicit.

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

• account_statusA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries full burden. It discloses that the tool is free and non-consuming, which is key behavioral info. It does not detail return format or errors, but for a simple read-only operation this is sufficient.

  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 sentence that front-loads the purpose and adds a key behavioral trait. No wasted words, highly efficient.

  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 tool with no parameters, no output schema, and low complexity, the description is nearly complete. It specifies what is returned (remaining credit balance) and that it's free. Could mention data type or user association, but not critical.

  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?

  There are zero parameters, so schema coverage is 100%. The description adds no parameter info because none exist. Baseline score of 4 is appropriate as per guidelines.

  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 the user's remaining credit balance. It distinguishes from siblings (e.g., ai_chat_completion, web_fetch) by being a status query with no parameters and no credits consumed.

  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 notes that the tool is free and does not consume credits, implying it can be used without cost concerns. It does not explicitly state when not to use it, but the context is clear for a simple balance check.

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

• web_fetchA
  4.8/5.0
  Behavior5/5

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

  With no annotations, the description fully discloses key behaviors: default output format, JS rendering, captcha solving, geo-targeting, cost structure (base 1 credit, multipliers for difficulty), caching via expiration, and a link to live pricing. No destructive behavior is indicated, which is consistent with a fetch tool.

  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 compact yet comprehensive; it uses bullet-style formatting for cost multipliers to improve readability. Every sentence provides essential information without redundancy.

  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 8 parameters, 1 required, and no output schema, the description sufficiently covers what the tool returns (Markdown by default, with alternatives), how caching works, cost implications, and anti-bot handling. It is complete enough for an agent to invoke the tool correctly without additional information.

  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 100%, and the description adds significant value beyond the schema: it explains why Markdown is best for LLM, how difficulty multipliers work, that expiration=0 ensures live data, and that geo-targeting parameters (country/city) do not change cost. It also clarifies that subdivision is ignored when city is set.

  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 specific verb+resource: 'Fetch any URL through Massive.' It clearly states the primary function and distinguishes from sibling tools like web_search, which searches the web rather than fetches specific URLs.

  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 explicit guidance on format selection (Markdown best for LLM), difficulty escalation (start low, use higher if low fails), and expiration settings (0 for live data). It also explains cost multipliers. It could explicitly mention when not to use this tool (e.g., use web_search for general queries), but the context is sufficient for appropriate usage.

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