Server Quality Checklist

Tool Scores

• search_google_cloud_docsA
  4.2/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It discloses behavioral traits: it returns 'actual content' (not just links), specifies the output format (JSON with fields like results array and otherRelatedDocs), mentions it returns 'top 3 docs' (implying ranking/limiting), and notes it handles 'free-form query in natural language'. However, it doesn't mention rate limits, authentication needs, or error handling, leaving some gaps for a search tool.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is well-structured with sections (WHEN TO USE, TRIGGERS, INPUT, EXAMPLE QUERIES, OUTPUT, SUPPORTED TOPICS), but it is overly verbose. Sections like 'SUPPORTED TOPICS' with 80+ mappings and extensive trigger lists could be condensed, as some details (e.g., specific service names) are redundant with the clear usage guidelines. It front-loads key info but includes excessive examples that don't all earn their place.

  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 complexity (search with natural language queries) and lack of annotations/output schema, the description is mostly complete. It covers purpose, usage, parameters, output format, and examples. However, without an output schema, it should ideally explain return values more thoroughly (e.g., content format, pagination), and it misses some behavioral aspects like error cases or performance hints, leaving minor gaps.

  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 100%, so the schema already documents both parameters (query and product) with examples. The description adds minimal value beyond the schema: it repeats that query is 'free-form search query in natural language' and product filters by 'specific GCP product', but doesn't provide additional syntax, format details, or constraints. This meets the baseline of 3 when schema does the heavy lifting.

  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: 'Search Google Cloud documentation with any free-form query. Returns relevant documentation with actual content.' This specifies the verb (search), resource (Google Cloud documentation), and output (documentation with content). It distinguishes from sibling tools like 'fetch_google_cloud_doc' (likely fetches a specific doc) and 'get_api_reference' (focuses on API docs).

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description includes an explicit 'WHEN TO USE' section stating this is the 'PRIMARY tool for GCP-related queries' and should 'ALWAYS' be used for GCP topics. It provides extensive 'TRIGGERS' with specific examples (e.g., services, configuration questions, best practices) and 'SUPPORTED TOPICS' with 80+ mappings, clearly differentiating when to use this over alternatives like 'list_google_cloud_products' (which likely lists products without searching content).

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

• fetch_google_cloud_docA
  4.4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the tool's behavior: it fetches and extracts content, returns JSON with specific fields, mentions content truncation at 20,000 chars, and provides common path examples. The only minor gap is it doesn't mention error handling or rate limits.

  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 with clear sections (WHEN TO USE, INPUT, OUTPUT, COMMON PATHS, TIP) and front-loaded with the core purpose. While somewhat lengthy due to the examples, every section serves a purpose and there's minimal redundancy. The TIP section is particularly efficient.

  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 single-parameter tool with no annotations and no output schema, the description provides excellent completeness. It explains the tool's purpose, when to use it, input format, detailed output structure with field descriptions, practical examples, and guidance on alternatives. The output description effectively substitutes for a missing output schema.

  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 100%, so the schema already fully documents the single 'path' parameter. The description repeats the parameter explanation in the INPUT section and provides extensive examples in COMMON PATHS, but doesn't add significant semantic value beyond what the schema provides. This meets the baseline for high schema coverage.

  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 with specific verbs ('fetch and extract content') and resource ('Google Cloud documentation page'). It distinguishes from sibling tools by specifying it's for exact documentation paths, unlike 'search_google_cloud_docs' for unknown paths or 'list_google_cloud_products' for product listings.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description includes an explicit 'WHEN TO USE' section that provides clear guidance: use when you know the exact documentation path. It also explicitly names an alternative tool ('search_google_cloud_docs') for when you don't know the path, creating a complete usage framework.

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

• get_api_referenceA
  4.7/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool returns (JSON with specific fields), provides examples of supported services and resources, and includes example usage patterns. It doesn't mention rate limits, authentication requirements, or error handling, but provides substantial behavioral context.

  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 with clear sections (purpose, when to use, input, supported services, output, examples). Every sentence adds value, and the information is front-loaded with the core purpose followed by practical guidance. No wasted words or redundant 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?

  For a tool with 2 parameters, 100% schema coverage, and no output schema, the description provides complete context. It explains what the tool does, when to use it, detailed parameter semantics, supported values, output structure, and example usage. This is comprehensive given the tool's complexity and available structured data.

  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 description coverage is 100%, so the baseline is 3. The description adds significant value by providing a comprehensive list of supported services and resources for each service, which goes beyond the schema's generic descriptions. It also clarifies the relationship between service and resource parameters through examples.

  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 with specific verb ('Get') and resource ('REST API reference documentation for a specific Google Cloud service'). It distinguishes from sibling tools by focusing specifically on API reference documentation rather than general documentation, product listings, or search.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description includes an explicit 'WHEN TO USE' section with four specific scenarios for using this tool, providing clear guidance about when it's appropriate. It differentiates from siblings by focusing on API endpoints, methods, and parameters rather than general documentation needs.

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

• list_google_cloud_productsA
  4.7/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden. It discloses behavioral traits such as the output format (JSON with specific fields) and the scope of products included (listing 20+ categories). However, it lacks details on potential limitations like rate limits, pagination, or freshness of data, which would be helpful for a comprehensive list 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 well-structured with clear sections (purpose, usage, output, products included, tip), making it easy to scan. Each sentence adds value, such as explaining the output format, listing product categories, and linking to sibling tools. There is no redundant or verbose content, and the information is front-loaded with the core purpose.

  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 (listing products with no parameters) and lack of annotations or output schema, the description is complete. It covers purpose, usage guidelines, output details, product scope, and integration with other tools. This provides sufficient context for an AI agent to understand when and how to use this tool effectively.

  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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately does not discuss parameters, maintaining focus on the tool's purpose and usage. A baseline of 4 is applied as it compensates well for the lack of parameters by providing rich context elsewhere.

  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 ('List') and resource ('all available Google Cloud products with their documentation paths'), making the purpose specific. It distinguishes from sibling tools like 'fetch_google_cloud_doc' by focusing on listing products rather than fetching documentation, and from 'search_google_cloud_docs' by being comprehensive rather than filtered.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines5/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The 'WHEN TO USE' section provides explicit guidance with multiple scenarios (e.g., user wants to see GCP services, exploring products, finding product IDs). It also mentions an alternative tool ('fetch_google_cloud_doc') in the TIP, clarifying when to use this vs. others. The examples of user queries further reinforce appropriate contexts.

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