Server Quality Checklist

Tool Scores

• get_themeB
  3/5.0
  Behavior2/5

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

  With no annotations, the description should disclose behavioral traits. It only states it returns a full definition but omits any info on read-only nature, authentication needs, or error behavior. The description is minimal.

  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 sentence that conveys the core purpose without any filler. Highly concise and front-loaded.

  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 presence of an output schema (not shown but exists), the description doesn't need to explain return values. However, it lacks usage guidance and parameter details, making it minimally adequate for a simple tool.

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

  Parameters1/5

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

  Schema description coverage is 0% (no description in schema). The tool description does not explain what the 'name' parameter represents (e.g., theme name, ID, where to find valid values). It adds no meaning beyond the schema property title.

  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 action ('Return'), the resource ('full definition of a theme'), and specific content ('colors, fonts, image style'). It effectively distinguishes from sibling tools like list_themes and create_presentation.

  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 this tool vs alternatives (e.g., list_themes or generate_image). The description lacks explicit when-to-use or when-not-to-use context.

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

• generate_imageB
  3.3/5.0
  Behavior2/5

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

  Annotations are absent, so the description bears full burden. It reveals generation and local path return but omits side effects, permissions, resource consumption, or failure behavior. For a generation tool, more transparency is needed.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

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

  Description is relatively concise but includes a bullet-like arg list that largely repeats schema information. Front-loaded with main purpose, but some redundancy could be trimmed.

  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?

  Despite having an output schema, the description does not explain how the output local path is structured or any server prerequisites. The 'theme' and 'target' parameters lack full context. For a 5-parameter tool, completeness is average.

  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 0%, but the description explains all five parameters: prompt, theme, size, negative_prompt, target. It adds meaning beyond bare schema by clarifying 'theme' appends image_style and 'target' distinguishes content vs background. Minor lack of format constraints.

  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?

  Description clearly states 'Generate a single image' and specifies the server (ComfyUI MCP) and output (local path). It distinguishes from sibling tools like create_presentation and list_comfy_models, which serve different purposes.

  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 this tool vs alternatives. The description does not mention prerequisites, context for selection, or exclusions. It only lists parameters without usage recommendations.

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

• list_themesA
  3.8/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It states a read-only listing operation, which is appropriate, but does not disclose potential pagination, ordering, or performance characteristics. For a simple list, this is adequate but not thorough.

  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?

  Single sentence, no wasted words, directly states the tool's action.

  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 has no parameters and an output schema exists, the description is complete enough for its simplicity. However, it could mention if the list is sorted or if it includes all themes without restrictions.

  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?

  No parameters exist, so baseline 4 applies. The description does not add parameter information because there are none.

  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 'List the available design theme names' uses a specific verb (List) and resource (design theme names), clearly distinguishing from sibling tools like 'get_theme' which retrieves a single theme.

  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 this tool versus alternatives. For example, it does not suggest using this to see all themes before employing 'get_theme' to retrieve details of a specific one.

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

• list_comfy_modelsA
  4.1/5.0
  Behavior2/5

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

  No annotations are provided, and the description does not disclose behavioral traits like idempotency, safety, or error handling. It only implies a read operation but lacks explicit statements about side effects or behavior when prerequisites are not met.

  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: two sentences that front-load the purpose and efficiently provide usage context. Every word earns its place.

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

  Completeness5/5

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

  Given zero parameters and the existence of an output schema (which removes the need to explain return values), the description covers the tool's purpose, examples of what is listed, and prerequisites. It is complete for a simple listing tool.

  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?

  With zero parameters, the baseline is 4 as per instructions. The description adds no parameter information because none exist, and the schema coverage is trivially 100%. No additional meaning is needed.

  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 uses a specific verb 'List' and identifies the resource as 'models available on the ComfyUI HTTP API', with examples (checkpoints/samplers/schedulers). It clearly distinguishes itself from sibling tools like create_presentation or generate_image.

  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 explains its usefulness for viewing backend capabilities and selecting a checkpoint value, and lists the required environment variables (IMAGE_BACKEND, COMFY_API_URL). However, it does not explicitly mention when not to use or provide alternatives.

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

• create_presentationA
  4.5/5.0
  Behavior4/5

  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 reveals that images are auto-generated via ComfyUI, and outlines the expected role of the model. This adds useful behavioral context, though it doesn't address error handling or potential side effects.

  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, front-loading the purpose and then providing instructions and an example. At around 150 words, it is informative without being overly verbose, though minor trimming could improve conciseness.

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

  Completeness5/5

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

  Given the complexity of creating a deck with auto-generated images, the description covers all necessary aspects: input format, model responsibility, image handling, and expected output (file path). The presence of an output schema (indicated in context) ensures return values are documented.

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

  Parameters5/5

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

  Schema coverage is 0%, but the description provides a detailed JSON example of the plan_json parameter, explaining each field and optional elements. This adds significant meaning beyond the schema's type definition, fully compensating for the lack of schema documentation.

  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 'Create a PowerPoint deck from a structured plan and return the file path', providing a specific verb ('create') and resource ('PowerPoint deck'). The example of the JSON plan distinguishes it from sibling tools like generate_image, which produce images instead.

  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 explicitly instructs that 'The orchestrating model is expected to do any web research and produce the slide plan', providing clear context for when this tool should be invoked. It also explains image generation behavior, though it lacks explicit exclusions or comparisons to alternatives.

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