Server Quality Checklist

Tool Scores

• understand_audioA
  4.1/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries full burden. It mentions supported formats and size limits, and implies an external API call. However, it doesn't disclose potential side effects (e.g., data sent to external service), authentication needs, or whether the operation is read-only. It covers basic behavioral traits but lacks depth for a tool with no annotations.

  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 structured with a warning, usage, args, returns, and additional info. It is somewhat lengthy but front-loaded with critical information (self-call warning). Minor redundancy exists (e.g., listing audio formats both in args and later), but overall each sentence contributes to clarity.

  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?

  With 7 parameters (1 required) and an existing output schema, the description covers all parameters, supported formats (MP3, WAV, etc.), and size limits. It provides sufficient context for an agent to understand input, output, and constraints. No gaps are evident for the tool's complexity.

  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 description coverage is 0%, so the description must compensate. It provides detailed explanations for each parameter: prompt includes examples ('转录音频内容'), audio_url/audio_path clarify single vs multiple, max_tokens gives default/max, and system_prompt describes customization. This adds significant meaning beyond the schema's types and titles.

  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 calls a multimodal model to 'understand audio' (transcription, summary, analysis). It distinguishes from siblings by default (audio vs image/video), but doesn't explicitly differentiate from understand_image or understand_video. A 4 is appropriate for clear purpose but minor lack of 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 provides explicit when-to-use (transcription, summary, analysis) and when-not-to-use (reading source code/metadata). However, it does not mention alternative tools for image or video tasks, which would improve selection. The warning about self-calling if the model is mimo-v2.5 is unique but not a general usage guideline.

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

• understand_imageA
  4.7/5.0
  Behavior4/5

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

  No annotations provided, so description carries full burden. Discloses use of external API, supports multiple image inputs, has size limits (50MB) and format support. Includes system prompt and max_tokens details. Slightly less transparent on authentication or rate limits, but adequate for a read-only tool.

  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 warning, usage guidelines, parameter list, returns, and constraints. However, the warning about not using if same model is repeated, slightly reducing conciseness. Still front-loaded and clear.

  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?

  Given 7 parameters, no schema descriptions, no annotations, and presence of output schema, the description is comprehensive. Covers all parameters, use cases, constraints, and return value. Handles complexity well.

  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 coverage is 0%, but description explicitly explains each parameter's purpose and gives examples (prompt, image_url, etc.). Adds meaning beyond schema, like supported formats and size limits.

  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 it calls a multimodal model to understand images, specifying use cases like analysis, description, OCR, and recognition. It distinguishes from sibling tools (audio and video) by focusing on images.

  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 says when to use (analyze images) and when not to (code/text files, use Read tool). Also warns if the model is the same as the underlying model, don't call it, providing clear alternatives.

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

• understand_videoA
  4.8/5.0
  Behavior4/5

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

  No annotations exist, so the description carries full burden. It discloses the model used, self-call restriction, supported formats, and size limits. However, it omits potential costs, latency, or authentication requirements, but overall provides sufficient transparency for a read operation.

  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?

  Moderately long but well-structured with sections for general info, warning, usage, args, returns, and constraints. Every sentence adds value, no 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?

  Given the complexity (9 parameters, output schema exists), the description covers all parameters, return description, format support, size limits, and usage guidance. Output schema exists, so return details are sufficient. Comprehensive for the tool's purpose.

  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 coverage is 0% (no parameter descriptions in schema), so description carries full burden. It explains every parameter in detail (prompt, video_url, video_path, fps, resolution, etc.) with examples, default values, and ranges, adding substantial meaning beyond the schema.

  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 calls the MIMO multimodal model to understand video, with examples of tasks like describing, summarizing, and recognizing actions. It distinguishes from sibling tools (understand_audio, understand_image) by focusing on video.

  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 states when to use (analyzing, describing, summarizing video content) and when not to use (reading metadata or source code, which should use other tools). Also includes a critical self-call warning for the integrated model.

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