Server Quality Checklist

Tool Scores

• image_generateA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the behavioral burden. It adds useful context about output format (inline base64 or download URLs), but does not disclose prerequisites like API key requirements, cost, rate limits, or failure behavior, so its transparency is partial.

  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 two focused sentences with the verb+resource front-loaded and zero redundancy. It efficiently communicates purpose, mechanism, and output format.

  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?

  The description, combined with a fully described schema and an output schema, gives an agent enough to invoke and interpret results. It lacks explicit usage alternatives and deeper behavioral caveats, but for a simple generation tool it is sufficiently complete.

  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 descriptions cover 100% of the parameters, so the baseline is 3. The description adds no additional parameter semantics beyond the schema's own details, though it does reinforce the 'one or more' notion via 'Generate one or more images'.

  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 'generate' with a clear resource ('images') and source ('text prompt'), which precisely defines the tool's purpose. It also distinguishes itself from sibling tools like vision_analyze and vision_ocr, which analyze or OCR images rather than create them.

  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 context for when to use the tool is clear: generating one or more images from a text prompt. However, it does not explicitly state exclusions or mention alternatives such as vision_analyze/vision_ocr, stopping short of the highest level of guidance.

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

• vision_ocrA
  4.4/5.0
  Behavior4/5

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

  No annotations exist, so the description carries the full behavioral burden. It discloses the core behavior of extracting exact, verbatim text and implies a non-destructive operation. However, it does not mention potential limitations (e.g., language/accuracy) or explicitly state that it is read-only, though this is strongly implied.

  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 concise and front-loaded with the purpose. It consists of two sentences: the first defines the tool, the second provides usage and an alternative. Every sentence contributes meaning without redundancy.

  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?

  With 9 parameters, all covered by schema descriptions, and an output schema present, the description adds the essential context: when to use and when not, plus clear differentiation from a sibling. It does not explain return values because the output schema covers that. Slight gap is lack of mention of mutual exclusivity of image inputs, but that is covered in the schema.

  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 baseline is 3. The description adds useful context about image types but does not provide parameter-specific semantics beyond what the schema already contains. No additional value for the 9 parameters.

  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 function: 'Extract exact text from an image (OCR).' It uses a specific verb and resource, provides concrete examples, and explicitly differentiates from vision_analyze by stating it is 'Not for explaining or understanding images (use vision_analyze).'

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

  Usage Guidelines5/5

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

  Provides explicit when-to-use guidance: 'Use when the user wants literal text copied verbatim from a screenshot, code image, terminal output, document, or receipt.' It also gives a clear exclusion and alternative: 'Not for explaining or understanding images (use vision_analyze).'

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

• vision_analyzeA
  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 clearly indicates non-mutating analysis behavior (understand/explain/describe) and clarifies the tool is for reasoning rather than exact extraction. It doesn't mention model defaults or fallibility, but given the output schema exists, the main behavioral traits are adequately conveyed.

  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?

  Three sentences: state purpose, give positive use cases, give negative use case with alternative. Front-loaded and every sentence serves a clear function with zero waste.

  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?

  For an analysis tool with a rich schema and output schema present, the description covers purpose, usage, and exclusion. It doesn't need to explain return values because the output schema handles that. Complete for an AI agent to select and invoke 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 baseline is 3. The description adds a small semantic hint about prompt framing ('understand, explain, or describe') but doesn't significantly enhance parameter understanding beyond the schema's existing descriptions.

  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 first sentence uses a specific verb-resource combination ('Understand, explain, or describe an image') and explicitly distinguishes from the sibling tool vision_ocr by stating 'Not for verbatim text extraction (use vision_ocr)'. This makes the purpose crystal clear and differentiates it from alternatives.

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

  Usage Guidelines5/5

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

  The description states concrete use cases ('screenshots, UI, diagrams, charts, or error messages that need reasoning') and explicitly excludes OCR with a direct reference to vision_ocr. This is an ideal when/when-not/alternatives pattern.

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