Server Quality Checklist

Tool Scores

• generate_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 full burden. It mentions the API and return format but lacks critical behavioral details: no information on rate limits, authentication needs, error handling, or what happens if generation fails. For a generative tool with zero annotation coverage, this is insufficient.

  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 well-structured with sections for Args and Returns, making it easy to scan. It's concise with no wasted sentences, though it could be more front-loaded by emphasizing the core purpose first.

  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's complexity (image generation with 4 parameters) and no annotations, the description is moderately complete. It covers parameters and return format, but lacks behavioral context and usage guidelines. The output schema exists, so describing return values isn't needed, but other gaps remain.

  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 0%, so the description must compensate. It lists all 4 parameters with brief explanations (e.g., 'Text description of the image to generate' for prompt), adding meaning beyond the schema's titles. However, it doesn't fully detail constraints like valid aspect ratio formats or performance options, leaving gaps.

  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: 'Generate an image using Fooocus Stable Diffusion API.' It specifies the verb ('Generate') and resource ('image'), though it doesn't explicitly differentiate from sibling tools like list_available_styles. The purpose is specific but lacks sibling comparison.

  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. The description mentions the API but doesn't specify scenarios, prerequisites, or exclusions. It's a basic functional statement without usage context.

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

• get_server_infoB
  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 the full burden of behavioral disclosure. It states that the tool 'Returns: Dictionary containing server configuration information,' which provides some output context, but it doesn't describe other behavioral traits such as whether this is a read-only operation, potential rate limits, authentication requirements, or error conditions. For a tool with zero annotation coverage, this is a significant gap in transparency.

  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 and front-loaded: it starts with the core purpose in the first sentence and follows with return information. There's no wasted text or redundancy. However, it could be slightly more structured (e.g., separating purpose and return into distinct sections), but it's efficient and clear.

  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's complexity (simple read operation with no parameters) and the presence of an output schema (which handles return values), the description is somewhat complete. It covers the purpose and mentions the return type, but it lacks behavioral context like safety or usage guidelines. With no annotations and simple schema, the description does the minimum viable job but leaves gaps in transparency and guidelines.

  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?

  The tool has 0 parameters, and the input schema has 100% description coverage (though empty). The description doesn't need to add parameter information since there are none, so it appropriately focuses on the tool's purpose and output. This meets the baseline of 4 for tools with no parameters, as there's no parameter semantics to explain.

  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: 'Get information about the Fooocus MCP server configuration.' This specifies both the verb ('Get information') and the resource ('Fooocus MCP server configuration'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'generate_image' or 'list_available_styles' (which have different purposes), so it doesn't reach the highest score.

  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 any specific contexts, prerequisites, or exclusions for usage. While the purpose is clear, there's no explicit advice on when this tool is appropriate compared to other tools in the server, leaving the agent to infer usage based on the tool name alone.

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

• list_available_stylesA
  3.5/5.0
  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 states the tool lists styles and returns a dictionary organized by category, which is helpful. However, it lacks details on potential side effects, error conditions, or performance aspects (e.g., caching, rate limits), leaving gaps in behavioral understanding.

  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 and well-structured: the first sentence states the purpose, and the second clarifies the return format. Every sentence adds value without redundancy, making it front-loaded and efficient.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's low complexity (0 parameters, no annotations, but has an output schema), the description is reasonably complete. It explains what the tool does and the return format, and the output schema likely covers return values in detail. However, it could benefit from more behavioral context or usage guidance to be fully comprehensive.

  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?

  The input schema has 0 parameters with 100% coverage, so the schema fully documents the lack of inputs. The description doesn't add parameter details, which is unnecessary here. A baseline of 4 is appropriate for zero-parameter tools, as no compensation is needed.

  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: 'List all available styles for image generation.' It specifies the verb ('List') and resource ('available styles for image generation'), making the function unambiguous. However, it doesn't explicitly differentiate from sibling tools like 'generate_image' or 'get_server_info', which would be needed for a score of 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 sibling tools like 'generate_image' (which might use styles) or 'get_server_info', nor does it specify prerequisites or contextual triggers. This leaves the agent without usage direction.

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