Server Quality Checklist

Tool Scores

• ocr_extractA
  4.5/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden of behavioral disclosure. It reveals key behaviors: it returns a specific JSON structure, and unclear characters are dropped rather than guessed. This adds meaningful context beyond a bare description, though it does not cover potential rate limits or authentication requirements.

  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 well-structured. The first line states the core purpose, followed by an 'Args' section and a 'Returns' section. Every sentence adds value—no filler or redundancy.

  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 a tool with three parameters and an output schema, the description is remarkably complete. It includes parameter semantics, return format, a behavioral caveat about OCR accuracy, and the scope limitation. This allows an agent to select and invoke the tool correctly without additional context.

  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 schema provides only parameter names and defaults, but the description explains each parameter's semantics: image_source can be a local path or HTTP(s) URL, prompt is optional instructions, and temperature is sampling temperature with a default of 0.2. This compensates well for the 0% 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 extracts visible text from images, with the explicit constraint 'OCR only, no scene description'. This distinguishes it from sibling tools like analyze_image and detect_elements, making its purpose unambiguous.

  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 provides clear use context: it is for OCR text extraction, not scene understanding. It explicitly excludes scene description, which helps the agent avoid using this tool for image analysis tasks. However, it does not name sibling alternatives directly, so a 4 is appropriate.

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

• detect_elementsA
  4.6/5.0
  Behavior5/5

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

  With no annotations, the description fully discloses behavioral traits: it explicitly notes the precision/recall tradeoff ('prefers false negatives over false positives') and the mandatory bounding box output. This provides meaningful insight beyond the basic input/output schema.

  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 well-structured with a one-sentence summary, a key behavioral note, and clearly labeled Args and Returns sections. Every sentence provides useful information without redundancy.

  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?

  Despite having an output schema, the description provides a concrete example of the return JSON, and covers input, output, and behavioral policy. For a tool with 3 parameters and moderate complexity, this is complete and sufficient.

  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?

  The input schema has 0% description coverage, but the description fully compensates by explaining all three parameters: image_source as a local path or URL, prompt as optional instructions with an example, and temperature with a default. This adds significant semantic meaning beyond the schema.

  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 'Detect objects in an image with mandatory bounding boxes,' providing a specific verb and resource. However, it does not explicitly differentiate from sibling tools like analyze_image or ocr_extract, so the purpose is clear but lacks sibling differentiation.

  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 implies usage for object detection with a 'conservative by design' behavior, giving clear context on when to use the tool. It does not explicitly state exclusions or alternative tools, so it falls short of the highest rating.

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

• analyze_imageA
  4.9/5.0
  Behavior5/5

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

  No annotations are present, so the description carries full burden. It discloses anti-hallucination safeguards, a confidence flag ("存疑"), mandatory bbox behavior, and temperature's effect on hallucination. Rich behavioral disclosure beyond basic operation.

  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?

  Well-structured with Args/Returns sections, but slightly verbose with the mode definitions. Still, every line adds value, so minor deduction only for length.

  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?

  All parameters, return format, and behavioral traits are covered, including the custom flag. The description is self-contained for a 4-param tool with no schema annotations.

  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 has zero descriptions; the description fully compensates by defining image_source as path/URL, enumerating mode values with their outputs, and explaining prompt/temperature semantics beyond defaults.

  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?

  Starts with a clear verb+object ('Analyze an image') and immediately differentiates from siblings by explicitly pointing to ocr_extract for OCR and describing distinct modes (general, ui_screenshot, ocr, detect). This leaves no ambiguity about the tool's scope.

  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?

  Includes a mode list that explains which analysis to run, explicitly defers OCR to the dedicated ocr_extract tool, and notes mandatory bbox for detect mode. This gives the agent clear when-to-use and when-not-to-use guidance.

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