Server Quality Checklist

Tool Scores

• image_understandA
  3.6/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the disclosure burden. It reveals a notable behavioral detail: '服务端会自动注入 Focus Hint 和基础视觉协议', explaining automatic server-side processing. However, it omits potential side effects, authentication needs, rate limits, or response format, leaving some behavioral aspects unclear.

  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 a compact paragraph that front-loads the core purpose, then efficiently covers triggers, image sources, usage, and optional task_type. Each sentence contributes useful information without redundancy, though it is slightly dense and could be broken into clearer sections.

  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?

  The description provides solid context for when to use the tool, image formats, and task_type semantics, which helps an agent select and invoke it. However, since there is no output schema, the description should explain what the tool returns (e.g., text, analysis), but it does not, leaving a significant gap in expected response understanding.

  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 coverage is 100%, so the description does not need to repeat parameter details. The description adds minimal extra meaning by clarifying that 'prompt' should be the user's original question and by summarizing task_type's auto-inference behavior, but this largely mirrors the schema's own descriptions.

  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 identifies the tool as a '通用图像理解工具' (general image understanding tool) and lists trigger scenarios like viewing images, screenshots, interfaces, errors, and layouts. It effectively communicates the resource and action, but does not explicitly distinguish itself from sibling tools (image_ocr, image_compare), relying on the word '通用' to imply a broader scope.

  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 explicit when-to-use instructions: '当用户提到看图/截图/界面/报错/布局，或对话中出现图片附件并询问图片相关问题时调用'—covering common triggers and image attachment scenarios. It also advises to '直接传入用户原始问题即可', giving practical usage direction, though it does not mention when not to use it or alternatives.

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

• image_compareA
  3.9/5.0
  Behavior3/5

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

  The description discloses the return format (structured difference report with type, severity, and description), adding value beyond the schema. However, it does not mention whether the tool is read-only, potential limitations, or edge cases. Since no annotations are provided, the description carries the full burden but only partially fulfills it.

  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 concise sentences, front-loaded with the core action, followed by use cases and output summary. Every sentence adds value with no redundancy or fluff.

  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?

  The description covers the tool's purpose, appropriate scenarios, and output structure, which is adequate for basic understanding. However, it lacks details about edge cases, limitation, or how to interpret the report fields beyond their names. With no annotations or output schema, more context could be expected for a complete picture.

  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 for all three parameters, so the description does not need to add parameter semantics. The description does not elaborate on parameters beyond what the schema already provides, which is acceptable given the high 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 function: '对比两张图片的差异' (compare differences between two images). The specific scenarios (design vs implementation, before/after, spot-the-difference) help distinguish it from sibling tools like image_understand and image_ocr.

  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 cases ('设计稿vs实现、修改前后对比、找不同') that indicate when to use this tool. It does not explicitly mention exclusions or alternatives, but the sibling tool names give implicit context for differentiation.

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

• image_ocrA
  4.4/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It discloses that the tool preserves formatting and reading order and implicitly states image-only input by redirecting PDFs to another tool. However, it does not describe output structure or edge cases, which is acceptable for a simple OCR tool.

  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 concise, front-loaded sentences: purpose, suitable scenarios, and PDF alternative. Every sentence earns its place with no 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?

  Tool is simple and has no output schema, but the output_format parameter covers return types. The description provides essential context (scenarios, PDF limitation) and is sufficiently complete for an 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 baseline is 3. The description does not add significant meaning beyond the schema's parameter descriptions; the only extra context is that formatting/reading order is preserved, which aligns with the output_format parameter but is not essential.

  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 it is a specialized OCR tool that extracts all text from images with high precision while preserving formatting and reading order. This distinguishes it from sibling tools (image_understand, image_compare) which are not focused on text extraction.

  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?

  Explicitly lists suitable scenarios (document screenshots, code screenshots, tables, forms, scanned documents) and provides a clear alternative for PDFs (use MinerU skill). This gives the agent specific 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.