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 of behavioral disclosure. It mentions the analysis uses 'GPT-4o-mini', which hints at AI-based processing, but doesn't disclose critical traits like rate limits, authentication needs, response format, error handling, or whether it's a read-only or mutating operation. For a 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.

  Conciseness4/5

  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. It's appropriately sized and front-loaded with the core action. However, it could be slightly more structured by explicitly separating purpose from technical details, but overall it avoids waste and is easy to parse.

  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 an AI-based image analysis tool with no annotations and no output schema, the description is incomplete. It doesn't explain what the analysis returns (e.g., text description, labels, confidence scores), any limitations (e.g., image size, content restrictions), or error conditions. For a tool that likely produces rich output, this lack of context makes it inadequate for an agent to use 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 single parameter 'imageUrl' documented as 'URL of the image to analyze'. The description adds no additional meaning beyond this, such as URL format requirements, supported image types, or size limits. Since the schema does the heavy lifting, the baseline score of 3 is appropriate, but no extra credit is earned.

  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: 'analyzes the image content using GPT-4o-mini' with a specific verb ('analyzes') and resource ('image content'). It distinguishes from the sibling tool 'analyze_image_from_path' by specifying it works with URLs rather than file paths. However, it doesn't explicitly mention what kind of analysis is performed (e.g., object detection, description generation, etc.), keeping it at a 4 rather than a perfect 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 alternatives. It doesn't mention the sibling tool 'analyze_image_from_path' or explain the difference between URL-based and path-based image analysis. There's no context about prerequisites, limitations, or appropriate use cases, leaving the agent with minimal usage guidance.

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

• analyze_image_from_pathA
  3.6/5.0
  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 of behavioral disclosure. It mentions that the tool 'analyzes its content using GPT-4o-mini,' which adds useful context about the analysis method. However, it doesn't disclose important behavioral traits like whether this is a read-only operation, potential rate limits, authentication needs, or what kind of analysis results to expect. The description doesn't contradict annotations (since none exist), but it leaves significant 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 appropriately sized at two sentences. The first sentence states the core purpose, and the second adds important usage guidance about path requirements. There's no wasted text, and information is front-loaded. It could be slightly more concise by combining ideas, but it's efficient overall.

  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 has no annotations, no output schema, and a simple single parameter, the description provides adequate basic information about what the tool does and path requirements. However, for an analysis tool, it should ideally mention what kind of analysis is performed (e.g., object detection, captioning, etc.) or what format the results take. The description is complete enough for basic understanding but lacks depth about the analysis output.

  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 the single parameter 'imagePath' with its description. The description adds some context about path requirements ('valid path for the server execution environment') but doesn't provide additional semantic meaning beyond what's in the schema. With high schema coverage, the baseline is 3 even without extra parameter information in the 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 tool's purpose: 'Loads an image from a local file path and analyzes its content using GPT-4o-mini.' This specifies both the action (loads and analyzes) and the resource (image from local file path). However, it doesn't explicitly differentiate from its sibling 'analyze_image' tool, which likely handles images differently (e.g., from URLs or base64).

  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 provides clear context about when to use this tool: when you have a local file path accessible from the server execution environment. It mentions the need for 'valid path for the server execution environment (e.g., Linux path if the server is running on WSL),' which helps guide usage. However, it doesn't explicitly state when NOT to use it or mention the sibling tool as an alternative for different image sources.

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