Server Quality Checklist

Tool Scores

• analyze_imageC
  2.9/5.0
  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. It only states that AI vision models are used and supported input formats. It does not disclose behavioral traits such as output behavior, failure conditions, accuracy, or limitations (e.g., file size restrictions or model capabilities).

  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 short and front-loaded with the primary purpose. The second sentence lists supported formats efficiently. It could benefit from slight restructuring to separate purpose from input types, but it remains concise and readable.

  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 (4 parameters, nested options, no output schema), the description lacks completeness. It does not explain return values, analysis modes (general, palette, hierarchy, components) beyond the schema, or how to interpret results. The user would need additional context to use this tool 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?

  Schema description coverage is high (75%), so the baseline is 3. The description adds minimal value beyond the schema, such as reiterating supported image source formats. The prompt parameter has detailed instructions in the schema that are not echoed in the description, but the description's mention of 'supports URLs, base64, local file paths' matches the schema's imageSource description.

  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 verb 'analyze' and the resource 'image using AI vision models'. It also specifies supported input types (URLs, base64, local paths). However, it does not differentiate from sibling tools like compare_images or detect_objects_in_image, leaving some ambiguity in scope.

  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 guidance is provided on when to use this tool versus alternatives. For example, if the goal is to compare two images or detect objects, the user would need to infer that other sibling tools are more appropriate. The description offers no exclusions or context.

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

• compare_imagesC
  2.9/5.0
  Behavior2/5

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

  No annotations present, so description carries full burden. It does not disclose behavioral traits like read/write nature, side effects, authorization requirements, or limits beyond an implicit reliance on AI models.

  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?

  Description is a single concise sentence that immediately states the core function. No fluff, but lacks structure like bullet points for clarity.

  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?

  No output schema, but description does not mention what the tool returns (e.g., comparison results or analysis). With moderate complexity and no annotations, it is incomplete.

  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 high (67%). The description adds minimal value beyond the schema, only reiterating supported input formats. Baseline of 3 is appropriate as schema already documents parameters well.

  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?

  Description clearly states the tool compares multiple images using AI vision models and lists supported input formats. It distinguishes from sibling tools like analyze_image which likely works on single images, but does not explicitly contrast with audit_design.

  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 guidance on when to use compare_images over alternatives such as analyze_image or audit_design. No when-not-to-use or prerequisites provided.

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

• analyze_videoB
  3.1/5.0
  Behavior2/5

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

  With no annotations, the description must disclose all behavioral traits. It only mentions source support and that it uses AI vision models, but omits details like processing time, file size limits, supported formats, or that it is a read operation.

  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, front-loading the purpose and source types. No redundant or extraneous words.

  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 video analysis (long processing, nested options, no output schema), the description is too sparse. It does not mention return format, prompt tips, or that processing may be slow.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The description adds little beyond the schema; it restates that video source can be a URL or path, which is already in the schema. With 67% schema coverage, the description should compensate for less documented options but fails to do so.

  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 analyzes a video using AI vision models, and lists supported source types (URLs and local file paths). This verb+resource specification distinguishes it from sibling image-analysis tools.

  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 guidance is provided on when to use this tool versus alternatives like image analysis tools. The absence of any when-to-use or when-not-to-use information makes it difficult for an agent to choose correctly.

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

• audit_designB
  3.3/5.0
  Behavior3/5

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

  The description discloses the algorithms used (K-means, Sobel, WCAG) and involvement of a Vision Language Model, which provides insight into behavior. However, without annotations, it lacks details on side effects, return format, or whether it is read-only. No output schema forces reliance on description for 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.

  Conciseness4/5

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

  The description is a single sentence that efficiently conveys core behavior and techniques. While very concise, it omits important details, but the sentence itself is well-structured and front-loaded.

  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 (nested options, 3 params, no output schema), the description is insufficient. It does not explain the output format, how to use imageSource, or what a successful audit returns. The lack of output schema increases the burden on the description, which is not met.

  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 67%, so much parameter meaning is already conveyed. The description adds marginal value by noting the prompt is optional and custom, but does not elaborate on how options (topK, etc.) affect the audit. The nested options are not explained in the tool description.

  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 design compliance auditing with specific techniques (K-means colors, Sobel edges, WCAG contrast) and VLM critique. It distinguishes itself from siblings like analyze_image and detect_objects by focusing on design compliance auditing.

  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 guidance on when to use this tool versus siblings (analyze_image, compare_images, etc.). It does not mention prerequisites, when not to use it, or alternative tools for different scenarios.

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

• detect_objects_in_imageB
  3.3/5.0
  Behavior3/5

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

  With no annotations, the description partially compensates by disclosing file handling behavior (explicit path vs. temp directory) and use of default parameters. However, it does not cover permissions, rate limits, or result format details.

  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 (three sentences) and front-loaded with the main purpose. It efficiently covers key points without unnecessary verbosity.

  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 5 parameters and no output schema or annotations, the description adequately explains the tool's inputs and basic behavior. However, it lacks details about the return value (annotated image format), error handling, and performance characteristics.

  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%, and the description adds valuable context beyond the schema. For example, it advises against including output structure instructions in the prompt, explains viewport parameters for web screenshots, and details outputFilePath resolution.

  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 detects objects and generates annotated images. It specifies supported image sources (URL, base64, file path). However, it does not differentiate from sibling tool 'analyze_image', which may have overlapping capabilities.

  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 guidance on when to use this tool versus alternatives like 'analyze_image' or 'compare_images'. The description mentions 'optimized default parameters' but does not provide context for appropriate usage scenarios.

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