Server Quality Checklist

Tool Scores

• flux_generateC
  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 full burden for behavioral disclosure. It mentions 'save files to download_path' which indicates file system writing, but doesn't disclose important behaviors like: whether this is a long-running operation, rate limits, authentication requirements, error handling, or what happens if download_path doesn't exist. For a complex 15-parameter image generation tool, 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 a single, efficient sentence that front-loads the core functionality. Every word earns its place: 'Generate an image' (action), 'with a FLUX model' (technology), 'via Replicate' (service), 'and save files to download_path' (output behavior). No wasted words or redundancy.

  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?

  For a complex image generation tool with 15 parameters and no annotations or output schema, the description is insufficient. It doesn't explain what the tool returns (file paths? success status?), doesn't mention error conditions, and provides no context about model-specific behaviors. The 100% schema coverage helps, but the description should do more to guide usage of such a feature-rich tool.

  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 15 parameters thoroughly. The description mentions 'download_path' but adds no additional semantic context beyond what's in the schema. It doesn't explain relationships between parameters (e.g., which models accept image_path) or provide usage examples. 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 action ('Generate an image') and resource ('with a FLUX model via Replicate'), specifying the service provider. It distinguishes from the sibling tool 'flux_models' by focusing on image generation rather than model listing. However, it doesn't explicitly contrast with the sibling tool in the description text itself.

  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 specific models, when to use image_path or mask_path parameters, or any prerequisites for usage. The sibling tool 'flux_models' exists but isn't referenced in usage context.

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

• flux_modelsB
  3.4/5.0
  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 that the tool lists models with 'usage notes and key inputs,' which gives some context about the output format. However, it doesn't describe critical behavioral traits such as whether this is a read-only operation, if it requires authentication, rate limits, or how the data is structured (e.g., pagination, sorting). For a tool with zero annotation coverage, this 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.

  Conciseness5/5

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

  The description is a single, efficient sentence that front-loads the core action ('List supported FLUX models') and adds value with 'usage notes and key inputs.' There is no wasted language, and it effectively communicates the essential information in a compact form.

  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 simplicity (0 parameters, no output schema, no annotations), the description is adequate but could be more complete. It covers the purpose and hints at output content, but without annotations or an output schema, it should ideally specify behavioral aspects like read-only nature or data format. For a low-complexity tool, it's minimally viable but lacks depth in transparency.

  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, meaning there are no parameters to document. The description doesn't need to add parameter semantics, so it naturally meets the baseline. It appropriately focuses on the tool's purpose without unnecessary parameter details.

  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 with a specific verb ('List') and resource ('supported FLUX models'), along with additional context about what information is included ('usage notes and key inputs'). It distinguishes itself from the sibling tool 'flux_generate' by focusing on listing models rather than generating content. However, it doesn't explicitly contrast with the sibling beyond the different action.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines3/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies usage context through 'usage notes and key inputs,' suggesting this tool is for discovering available models and their characteristics. It doesn't provide explicit guidance on when to use this versus 'flux_generate' (e.g., 'use this to find models before generating'), nor does it mention any prerequisites or exclusions. The usage is implied but not clearly articulated.

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