Server Quality Checklist

Tool Scores

• get_ai_core_topicC
  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. It states the tool retrieves 'comprehensive documentation,' implying a read-only operation, but doesn't disclose behavioral traits like authentication requirements, rate limits, error handling, or the format/scope of the returned documentation. This leaves significant gaps 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.

  Conciseness5/5

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

  The description is a single, efficient sentence that front-loads the core purpose and includes helpful examples. There's no wasted verbiage or redundancy, making it appropriately sized and well-structured for quick understanding.

  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 lack of annotations and output schema, the description is incomplete. It doesn't explain what 'comprehensive documentation' entails (e.g., format, depth), how results are structured, or any operational constraints. For a tool with no structured support, this leaves the agent with insufficient context to use it effectively.

  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 input schema has 100% description coverage, with the parameter 'topic_name' documented as 'Name of the AI Core topic.' The description adds minimal value by providing examples ('e.g., "Model Training", "Deployment"'), but doesn't elaborate on syntax, allowed values, or constraints beyond what the schema states. This meets the baseline of 3 for high schema coverage.

  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: 'Get comprehensive documentation for a specific SAP AI Core topic.' It specifies the verb ('Get') and resource ('comprehensive documentation'), and provides examples of topics. However, it doesn't explicitly differentiate from sibling tools like 'get_ai_core_document' or 'search_ai_core_docs', which prevents a score of 5.

  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 its siblings. It mentions examples of topics but doesn't specify if this is for general topic overviews versus detailed documentation, or how it differs from 'get_ai_core_document' or 'search_ai_core_docs'. There's no mention of prerequisites, alternatives, or exclusions.

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

• get_ai_core_documentB
  3.1/5.0
  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 retrieves content but lacks details on permissions required, rate limits, error handling, or response format. For a read operation tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

  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, efficient sentence that directly states the tool's function without unnecessary words. It is appropriately sized and front-loaded, making it easy to parse quickly.

  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 low complexity (single parameter, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose but lacks usage guidelines and behavioral details, which are important for effective tool selection and invocation in a broader context.

  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 input schema has 100% description coverage, with the 'path' parameter well-documented. The description adds minimal value beyond the schema by specifying it's for 'AI Core documentation page' and referencing 'as returned from search results', but doesn't provide additional syntax or format details. 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.

  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 with specific verbs ('Get the complete content') and resource ('AI Core documentation page by its path'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_ai_core_topic' or 'search_ai_core_docs', which likely have overlapping functionality.

  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 when this tool is appropriate compared to sibling tools like 'search_ai_core_docs' or 'get_ai_core_topic', nor does it specify prerequisites or exclusions for usage.

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

• list_ai_core_categoriesB
  3.3/5.0
  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 describes the tool as listing categories and contents, which implies a read-only operation, but doesn't specify details like whether it returns structured data, pagination behavior, or potential rate limits. For a tool with zero annotation coverage, this is a significant gap in transparency.

  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 with two sentences that are front-loaded: the first states the purpose, and the second provides usage context. There's no wasted text, and it efficiently conveys key information. It could be slightly improved by integrating the usage hint more seamlessly, but overall it's well-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 the tool's complexity is low (0 parameters, no output schema), the description is somewhat complete but has gaps. It explains what the tool does and its usefulness, but without annotations or output schema, it lacks details on behavioral traits like return format or limitations. For a simple list tool, this is adequate but not fully comprehensive.

  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 parameters need documentation. The description adds value by clarifying the scope ('all available documentation categories and their contents'), which isn't captured in the schema. This compensates well for the lack of parameters, making it clear what the tool returns without needing input.

  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: 'List all available documentation categories and their contents.' It specifies the verb ('List') and resource ('documentation categories and their contents'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_ai_core_document' or 'search_ai_core_docs', which might also involve documentation retrieval.

  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 some usage guidance with 'Useful for exploring what documentation is available,' implying this tool is for discovery or browsing. However, it doesn't explicitly state when to use this tool versus alternatives like 'search_ai_core_docs' or 'get_ai_core_topic,' leaving the agent to infer based on context. No exclusions or prerequisites are mentioned.

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

• search_ai_core_docsA
  3.8/5.0
  Behavior3/5

  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 the search behavior (semantic search) and return format (documents with excerpts and scores), which is good. However, it doesn't mention potential limitations like rate limits, authentication requirements, or how 'semantic' differs from keyword search. No contradiction with annotations exists.

  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 two sentences with zero waste: the first states purpose and resource, the second specifies the return format. It's front-loaded with the core functionality and appropriately sized for a search tool.

  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 no annotations and no output schema, the description does well by specifying the return format (documents with excerpts and scores). However, for a search tool with 3 parameters, it could benefit from more behavioral context (e.g., search scope, result ordering). It's mostly complete but has 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 fully documents all parameters (query, category, limit). The description doesn't add any parameter-specific details beyond what's in the schema, such as query examples or category explanations. Baseline 3 is appropriate 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 specific action ('semantically search'), target resource ('SAP AI Core documentation'), and output format ('returns relevant documents with excerpts and relevance scores'). It distinguishes from sibling tools like 'get_ai_core_document' (likely retrieves specific docs) and 'list_ai_core_categories' (lists categories).

  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 searching documentation, but doesn't explicitly state when to use this tool versus alternatives like 'get_ai_core_document' (for retrieving specific docs) or 'get_ai_core_topic' (possibly for topic-based access). No explicit exclusions or prerequisites are mentioned.

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