Server Quality Checklist

Tool Scores

• generate_imageA
  4/5.0
  Behavior4/5

  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 effectively describes key traits: the tool can generate or edit images, supports multiple input types (text prompts, input images), and includes a SynthID watermark on outputs. However, it lacks details on rate limits, error conditions, or performance characteristics, leaving some behavioral aspects unspecified.

  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 front-loaded with the core purpose in the first sentence, followed by specific capabilities and a critical behavioral note (watermark). It uses two concise sentences with no redundant or extraneous information, making it highly efficient and well-structured.

  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 complexity (image generation/editing with 5 parameters) and lack of annotations or output schema, the description provides a solid foundation by covering purpose, capabilities, and key behavior (watermark). However, it does not address output format details (e.g., image resolution, file size) or error handling, which could enhance completeness for an AI agent.

  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, providing clear documentation for all parameters. The description adds minimal semantic value beyond the schema, as it mentions 'text prompts' and 'input images' but does not elaborate on parameter interactions or usage nuances. The baseline score of 3 is appropriate given the comprehensive schema coverage.

  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 tool's purpose with specific verbs ('generate or edit images') and resource ('images'), identifies the underlying technology ('Gemini 2.5 Flash Image (Nano Banana)'), and lists three distinct capabilities: text-to-image generation, image editing with natural language prompts, and multi-image composition. This is comprehensive and unambiguous.

  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 contexts by listing capabilities (e.g., use for text-to-image, editing, or composition) but does not provide explicit guidance on when to choose this tool over alternatives or any prerequisites. Since there are no sibling tools, the lack of differentiation is not penalized, but it remains at an implied level without exclusions or best practices.

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