Server Quality Checklist

Tool Scores

• qwen_visionA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It adds useful context by naming the specific model and explaining the default prompt behavior (150-word description). However, it does not disclose potential error conditions, rate limits, or detailed return format, which leaves gaps given the absence of annotations.

  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, well-structured sentence that front-loads the core purpose, model name, and input types. No redundant words, and it efficiently covers the essential information.

  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 moderate complexity and the presence of a detailed schema, the description sufficiently covers the tool's purpose and default behavior. It does not have an output schema, but the phrase 'answer questions about the image' adequately implies the return value. Minor gaps remain on error handling/edge cases, so it isn't a perfect 5.

  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%, with all four parameters already explained in the schema. The description adds the model name and overall purpose but does not enrich the understanding of individual parameters beyond what the schema provides. Hence a baseline score of 3 is appropriate.

  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 function: using the qwen3-vl-plus vision model to understand an image and answer questions about it. It specifies both the verb (understand/answer) and resource (image), and by emphasizing image input it distinctly separates itself from sibling tools qwen_search and qwen_chat.

  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 implies usage for image-related tasks by stating it handles local file paths or URLs and answers image questions. It gives a clear context but does not explicitly mention alternatives or exclusions; thus it stops short of a perfect score.

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

• qwen_searchA
  4.2/5.0
  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 that the tool performs web search, returns answers with source citations, and is appropriate for current information. This is transparent for a read-only search tool, though it omits details about error handling, rate limits, or citation format specifics.

  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, well-structured sentence that front-loads the core function ('use Qwen to enable web search') followed by the return behavior and suitable use cases. There is no wasted wording, and the semicolon effectively separates the what from the when.

  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 simple search tool with two parameters and no output schema, the description is complete: it explains the purpose, mentions the return format (comprehensive answer with citations), and outlines use cases. It does not mention sibling alternatives explicitly, but all other essential context is present.

  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% with both 'query' and 'max_tokens' documented in the schema. The description does not add additional parameter semantics beyond what the schema already provides, so the baseline score of 3 is appropriate.

  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 uses the Tongyi Qianwen model to enable web search, retrieves the latest information, and returns a comprehensive answer with source citations. This distinguishes it from sibling tools qwen_chat and qwen_vision by emphasizing its search capability and suitability for time-sensitive topics.

  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 explicitly lists suitable use cases: 'suitable for time-sensitive questions, news, events, product information, etc.' This gives clear context for when to use the tool. However, it does not provide explicit when-not-to-use guidance or mention alternative tools, falling short of a full 5.

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

• qwen_chatA
  4.3/5.0
  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 the key behavioral trait of not being connected to the internet, which is a critical limitation for a chat model. It does not discuss other behaviors like statelessness or rate limits, but for a simple single-message chat tool, this is adequate.

  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 entire description is a single well-structured sentence that front-loads the core purpose ('ordinary conversation'), then adds the key constraint ('not connected to internet'), and ends with concrete examples. Every word contributes value, and there is no 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 simplicity of the tool (one required parameter, no output schema, no annotations), the description is fully sufficient. It explains what the tool does, provides examples, and clarifies the offline nature, which is all an agent needs to decide when and how to invoke it.

  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 already fully describes the 'message' parameter (the message content to send), so the schema coverage is 100%. The tool description adds context about the kinds of tasks the message can be used for, but it does not enrich the parameter semantics beyond what the schema provides.

  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 that this tool performs ordinary conversations with the Tongyi Qianwen text model, specifically without internet access. It lists common use cases (summarizing, rewriting, translating, code generation) and distinguishes itself from sibling tools like qwen_search (internet-connected) and qwen_vision (vision-based) by specifying 'text model' and 'not connected to internet'.

  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 implies usage for general text tasks that do not require internet access, which sets expectations. However, it does not explicitly mention when to use qwen_chat over alternatives (e.g., 'use qwen_search when internet is needed'), so the guidance is implied rather than explicit.

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