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?

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the service ('OpenRouter's vision models') and input formats, but fails to describe critical behaviors: whether this is a read-only or mutating operation, potential costs or rate limits, authentication needs, error handling, or what the analysis entails (e.g., object detection, captioning). For a tool with no annotation coverage, this is a significant gap.

  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 highly concise and front-loaded: two sentences that directly state the purpose and key capability. Every word earns its place, with no redundant or vague phrasing. It efficiently communicates the core functionality without unnecessary elaboration.

  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 (7 parameters, no annotations, no output schema), the description is incomplete. It lacks behavioral details (e.g., mutation risks, rate limits), output expectations, and differentiation from siblings. While the schema covers parameters well, the description doesn't compensate for missing annotations or output schema, leaving gaps for an AI agent to operate 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 100%, so the schema fully documents all 7 parameters. The description adds minimal value beyond the schema: it lists the input formats ('base64, file paths, and URLs'), which aligns with the 'type' enum, but doesn't provide additional context like file size limits or URL accessibility. With high schema coverage, 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.

  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: 'Analyze images using OpenRouter's vision models.' It specifies the verb ('analyze') and resource ('images'), and mentions the underlying service. However, it doesn't explicitly differentiate from sibling tools like 'analyze_mobile_app_screenshot' or 'analyze_webpage_screenshot', which appear to be more specialized versions.

  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 'Supports various input formats including base64, file paths, and URLs,' which hints at usage contexts, but lacks explicit when/when-not instructions or alternative recommendations. This leaves the agent to infer usage from tool names alone.

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

• analyze_mobile_app_screenshotC
  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 of behavioral disclosure. It states the tool 'provides insights' but doesn't describe what kind of output to expect (e.g., structured report, recommendations), whether it's a read-only analysis or modifies data, any rate limits, authentication needs, or potential errors. For a tool with 8 parameters and no annotations, this leaves significant behavioral gaps.

  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, efficient sentence that front-loads the core purpose ('Specialized tool for analyzing mobile app screenshots') and lists key analysis areas. It avoids redundancy and wastes no words, though it could be slightly more structured by separating use cases or output expectations.

  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 (8 parameters, no output schema, and no annotations), the description is incomplete. It doesn't explain what the output looks like (e.g., report format, insights structure), behavioral aspects like safety or limitations, or how to interpret results. For a specialized analysis tool with rich parameters, more context is needed to guide effective use.

  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 input schema already documents all parameters thoroughly with descriptions and enums. The description adds no specific parameter semantics beyond implying analysis of 'UI design, user experience, platform conventions, and app functionality,' which loosely relates to parameters like 'focusArea' but doesn't provide additional syntax, format, or usage details. 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.

  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: analyzing mobile app screenshots to provide insights into UI design, user experience, platform conventions, and app functionality. It specifies the resource (mobile app screenshots) and the type of analysis performed, though it doesn't explicitly differentiate from sibling tools like 'analyze_image' or 'analyze_webpage_screenshot' beyond mentioning 'mobile app' specificity.

  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 ('analyze_image' and 'analyze_webpage_screenshot'). It mentions 'mobile app screenshots' but doesn't clarify if it's for mobile-specific analysis only or how it differs from general image analysis tools. No explicit alternatives, exclusions, or prerequisites are stated.

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

• analyze_webpage_screenshotC
  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 of behavioral disclosure. It mentions what the tool extracts but doesn't cover critical aspects like whether it's a read-only operation, potential rate limits, authentication requirements, error handling, or what the output looks like (beyond mentioning extraction). For a tool with 7 parameters and no annotations, this is a significant gap.

  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 (two sentences) and front-loaded with the core purpose. Every sentence contributes meaning without redundancy. However, it could be slightly more structured by explicitly separating functionality from context.

  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 (7 parameters, no output schema, and no annotations), the description is incomplete. It lacks information on behavioral traits, output format details, error conditions, and differentiation from siblings. For a tool that analyzes webpage screenshots with multiple configuration options, this description doesn't provide enough context for an agent to use it effectively beyond basic invocation.

  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%, meaning all parameters are documented in the schema itself. The description doesn't add any parameter-specific details beyond what's in the schema (e.g., it doesn't explain how 'focusArea' or 'format' affect the analysis). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but also doesn't detract.

  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 as 'analyzing webpage screenshots' and specifies what it extracts ('content, layout information, and interactive elements from web pages'), which is a specific verb+resource combination. However, it doesn't explicitly differentiate from sibling tools like 'analyze_image' or 'analyze_mobile_app_screenshot', 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 its siblings ('analyze_image' and 'analyze_mobile_app_screenshot'), nor does it mention any prerequisites, exclusions, or alternative scenarios. It only states what the tool does without contextual usage information.

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