Server Quality Checklist

Tool Scores

• describeB
  3.3/5.0
  Behavior2/5

  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 mentions support for multiple providers, which adds some context, but lacks details on behavioral traits such as rate limits, authentication needs, error handling, or what the output looks like (e.g., format, length). For a tool with no annotations, this is a significant gap in transparency.

  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 sentences, front-loaded with the core purpose, and efficiently mentions provider support without unnecessary details. Every sentence contributes directly to understanding the tool's functionality, with zero waste or redundancy.

  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?

  Given 4 parameters, no annotations, and no output schema, the description is adequate but incomplete. It covers the basic purpose and provider context, but lacks details on output format, error cases, or integration with sibling tools. For a tool of this complexity, more contextual information would be beneficial to ensure proper usage.

  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 schema already documents all parameters thoroughly. The description adds minimal value beyond the schema by mentioning provider support, but doesn't elaborate on parameter meanings, interactions, or usage examples. Baseline 3 is appropriate as the schema handles most of the parameter documentation.

  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's purpose: 'Get an AI-generated description of an image.' It specifies the action (get description) and resource (image), but doesn't explicitly differentiate from sibling tools like 'describe_region' or 'detect' which might have overlapping functionality.

  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 mentions 'Supports multiple providers (Gemini, OpenAI, Claude),' which implies usage context for provider selection. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'describe_region' or 'analyze_colors,' nor does it specify scenarios where this tool is preferred or excluded.

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

• analyze_colorsA
  3.5/5.0
  Behavior3/5

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

  With no annotations provided, the description carries full burden. It discloses the algorithm (K-Means clustering), color space (LAB), and output format (colors sorted by frequency with human-readable names). However, it doesn't mention performance characteristics, error conditions, or limitations like image format support.

  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 perfectly concise with two sentences that each add value: first explaining the core functionality and method, second describing the output format. No wasted words or redundant information.

  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?

  For a tool with no annotations and no output schema, the description provides adequate but minimal context. It explains what the tool does and what it returns, but doesn't address error handling, performance, or integration considerations that would be helpful 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?

  Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, maintaining the baseline score.

  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 specific action ('Extract dominant colors'), resource ('from an image region'), and method ('using K-Means clustering in LAB color space'). It distinguishes from potential siblings by specifying color analysis rather than general description or detection.

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

  Usage Guidelines2/5

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

  No guidance is provided about when to use this tool versus alternatives like 'describe' or 'detect'. The description focuses on what the tool does, not when it's appropriate or what problems it solves.

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

• detectA
  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. It discloses key behavioral traits: it returns bounding boxes, uses Gemini for support, and specifies the coordinate format (normalized 0-1000 as [ymin, xmin, ymax, xmax]). However, it does not cover aspects like rate limits, error handling, or performance characteristics.

  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 and efficiently adds necessary details in two sentences. Every sentence earns its place by clarifying the tool's function, technology used, and output format 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?

  Given the tool's complexity (object detection with two parameters) and no annotations or output schema, the description is fairly complete. It covers the purpose, technology, and output format, but could benefit from more details on behavioral aspects like error cases or limitations to be fully comprehensive.

  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 schema already documents both parameters. The description adds some context by implying the 'prompt' parameter is for specifying what to detect, but it does not provide additional syntax or format details beyond what the schema provides, aligning with the baseline for high 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 specific action ('detect objects in an image') and the resource ('image'), and it distinguishes from sibling tools like 'analyze_colors' or 'describe' by focusing on object detection with bounding boxes rather than color analysis or general description.

  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 for object detection in images, but it does not explicitly state when to use this tool versus alternatives like 'describe' or 'describe_region'. It mentions 'Uses Gemini for native bounding box support', which hints at a specific context, but lacks clear exclusions or named alternatives.

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

• describe_regionA
  4.1/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It explains the core functionality (cropping and describing) and mentions a prerequisite relationship with detect(), but doesn't cover important behavioral aspects like error handling, performance characteristics, or what the detailed description output looks like. It provides basic context but lacks comprehensive behavioral transparency.

  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 perfectly concise with just two sentences that each serve a distinct purpose: the first states what the tool does, the second provides usage guidance. There's zero wasted text, and the information is front-loaded with the core functionality stated immediately.

  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?

  Given the tool's moderate complexity (image processing with multiple parameters) and the absence of both annotations and an output schema, the description provides adequate but incomplete context. It explains the purpose and usage relationship well, but doesn't address what the detailed description output contains or provide behavioral details that would be helpful for an AI agent to understand the tool fully.

  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?

  With 100% schema description coverage, the input schema already documents all 4 parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema, so it meets the baseline expectation but doesn't provide additional semantic context about how parameters interact or affect the operation.

  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 specific action ('Crop an image to a bounding box and describe that region in detail') and distinguishes it from sibling tools by explicitly mentioning 'Use this after detect() to zoom in on specific objects.' This provides both the verb+resource combination and 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 Guidelines5/5

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

  The description provides explicit guidance on when to use this tool ('Use this after detect() to zoom in on specific objects') and implies alternatives by distinguishing it from the 'describe' sibling tool (which presumably describes entire images rather than cropped regions). This gives clear context for tool selection.

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