Server Quality Checklist

Tool Scores

• generate_imageC
  2.7/5.0
  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 only states the basic action ('生成图像' - generate images) without mentioning important behavioral aspects like: whether this is a read-only or mutating operation, rate limits, authentication requirements, response format (e.g., returns image URL or binary data), error conditions, or processing time. For a complex image generation tool with 9 parameters, this is inadequate.

  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 extremely concise - a single Chinese phrase ('使用Pollinations.ai生成图像') that directly states the tool's purpose. There's zero wasted language or unnecessary elaboration. It's appropriately sized for what it communicates, though it could benefit from additional 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 complexity of an image generation tool with 9 parameters, no annotations, and no output schema, the description is insufficiently complete. It doesn't explain what the tool returns (image data, URL, etc.), doesn't provide usage examples or constraints, and offers no behavioral context. The agent would need to guess about important aspects of tool behavior.

  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 each parameter well-documented in Chinese. The tool description adds no additional parameter information beyond what's already in the schema. According to the scoring rules, when schema_description_coverage is high (>80%), the baseline is 3 even with no param info in the description, which applies here.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose3/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description states the tool '使用Pollinations.ai生成图像' (uses Pollinations.ai to generate images), which provides a clear verb ('生成图像' - generate images) and resource (images). However, it doesn't specify what type of images or differentiate from the sibling 'generate_text' tool beyond the obvious image vs. text distinction. The purpose is understandable but lacks specificity about the generation 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?

  The description provides no guidance on when to use this tool versus alternatives. There's no mention of when to choose this over 'download_image' (which presumably downloads existing images) or 'generate_text' (for text generation). No context about appropriate use cases, prerequisites, or limitations is provided.

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

• generate_textC
  2.7/5.0
  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 using Pollinations.ai but doesn't describe key behaviors like rate limits, authentication needs, response format, or potential errors. For a text generation tool with no annotation coverage, this leaves significant gaps in understanding how it operates.

  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, efficient sentence with zero waste. It's front-loaded and appropriately sized for its purpose, making it easy to parse quickly 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 complexity of a text generation tool with 6 parameters, no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error handling, or behavioral traits, leaving the agent with insufficient context to use the tool effectively beyond basic parameter input.

  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 6 parameters thoroughly. The description adds no additional meaning beyond what the schema provides, such as explaining interactions between parameters or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose3/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description '使用Pollinations.ai生成文本' states the action (generate) and resource (text) but is vague about scope and differentiation. It doesn't specify what kind of text is generated (creative, technical, etc.) or how it differs from sibling tools like generate_image, which also uses Pollinations.ai but for images. The purpose is understandable but lacks 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?

  No guidance is provided on when to use this tool versus alternatives. It doesn't mention prerequisites, limitations, or compare it to sibling tools like generate_image for image generation or download_image for downloading content. The description only states what it does, not when it's appropriate.

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

• download_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. It states the tool downloads images to a local file, implying a write operation, but doesn't disclose behavioral traits like file system permissions, overwrite behavior, error handling, or network dependencies. This is a significant gap for a tool that modifies the local environment.

  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, efficient sentence that directly states the tool's purpose without unnecessary words. It is appropriately sized and front-loaded, making it easy to understand at a glance.

  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 a download operation with no annotations and no output schema, the description is incomplete. It lacks details on what happens after download (e.g., success/failure responses, file validation), behavioral risks, and integration with sibling tools, leaving gaps for an AI agent to use it 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?

  Schema description coverage is 100%, so the schema already documents both parameters ('url' and 'output_path') with clear descriptions. The description adds no additional meaning beyond what the schema provides, such as URL format constraints or path validation rules, resulting in the baseline score of 3.

  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 action ('下载' meaning 'download') and the resource ('Pollinations.ai生成的图像' meaning 'images generated by Pollinations.ai'), specifying both the source and destination. However, it doesn't explicitly differentiate from sibling tools like 'generate_image' or 'generate_text', which would require a 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 like 'generate_image' (which likely creates images) or 'generate_text'. It mentions downloading generated images but doesn't specify prerequisites, such as needing a URL from a previous generation step.

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