Server Quality Checklist

Tool Scores

• describe_imageC
  2.8/5.0
  Behavior2/5

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

  No annotations are provided, so the description must convey behavior. It mentions using a multimodal model and outputting text, but fails to disclose details like file size limits, accuracy, latency, or any destructive actions. The description is too vague for a tool with no other behavioral signals.

  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 a single sentence in Chinese, which is concise but slightly long. It does not waste words, but the structure is minimal. It earns its place but could be more streamlined while adding missing details.

  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 complexity of 7 parameters (including anyOf conditions and nested objects) and the absence of an output schema and annotations, the description is incomplete. It does not explain the return format, error handling, or valid input combinations, making it hard for an agent to use correctly.

  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 for all 7 parameters (including nested objects), so the schema already explains parameter semantics. The tool description adds no additional information beyond what's in the schema. Baseline score of 3 is appropriate.

  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 function: using a multimodal model to convert images into detailed text descriptions for understanding by pure text models. It implicitly distinguishes from siblings like 'ask_about_image' and 'extract_image_text' but does not explicitly differentiate.

  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 does not mention when not to use it or any prerequisites. The only hint is that output is for pure text models, but no explicit usage instructions.

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

• ask_about_imageB
  3.1/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden for behavioral disclosure. It only states the tool answers questions but omits crucial details such as supported image formats, input constraints, error behavior, or authentication requirements. This is insufficient for an agent to anticipate side effects or limitations.

  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 a single, compact sentence with no fluff. It is appropriately sized for a simple tool, though it could benefit from additional context without becoming verbose. The structure is front-loaded with the core action and resource.

  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 tool's complexity (6 parameters, nested objects, multiple image input methods, no output schema, and sibling tools), the description is far too sparse. It does not explain how to choose between the various image inputs, what the output format looks like, or any usage context. The schema covers parameter details, but the description fails to provide the overarching behavioral and contextual information an agent needs.

  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 baseline is 3. The description adds no additional meaning beyond the schema; it simply restates the purpose. While the schema thoroughly documents each parameter, the description does not explain the semantic distinction between the multiple image input options (URL, path, base64, structured object), which would help the agent choose appropriately.

  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 a multimodal model to answer specific questions about images. This differentiates it from sibling tools like 'describe_image' (general description) and 'extract_image_text' (text extraction), making the purpose distinct and actionable.

  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 the siblings. It does not mention that it is suitable for specific, nuanced questions rather than general descriptions or text extraction, leaving the agent to infer usage from the name alone.

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

• extract_image_textB
  3.1/5.0
  Behavior2/5

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

  No annotations are provided, so the description must fully disclose behaviors. It mentions using multimodal OCR but does not explain what image formats are supported, whether there are size limits, how errors are handled, or what the return format is. The multiple image input methods in the schema are not acknowledged in the description.

  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 a single concise sentence, front-loading the core purpose. However, it omits valuable context that would help the agent, so while efficient, it sacrifices completeness.

  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?

  The tool has 5 parameters with nested objects and multiple image input methods, and no output schema. The description fails to mention what the tool returns (extracted text) or any limitations. It is not sufficiently complete for an agent to use without additional guidance.

  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 all parameters. The description adds no extra meaning beyond 'extract text from images', meeting the baseline of 3. It does not elaborate on how to use the various image input methods.

  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 extracts text from images using OCR, which is a specific verb and resource. It distinguishes itself from siblings 'ask_about_image' and 'describe_image' by focusing on text content extraction rather than description or question answering.

  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?

  No explicit usage guidelines are provided. The description does not specify when to use this tool over alternatives like 'ask_about_image' or 'describe_image'. The purpose is implied but not supported with contextual direction.

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