Server Quality Checklist

Tool Scores

• generate_qr_codeC
  2.9/5.0
  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 discloses that the tool 'Returns base64-encoded SVG image data that can be saved or displayed,' which is useful behavioral context. However, it lacks details on permissions, rate limits, error handling, or whether the operation is idempotent—critical for a generation tool with no annotation coverage.

  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 appropriately sized and front-loaded, with two sentences that efficiently convey the core functionality and output. Every sentence adds value: the first defines the action and output, the second notes styling support. No wasted words, though it could be slightly more structured for a perfect 5.

  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 (3 parameters, no output schema, no annotations), the description is partially complete. It covers the output format and styling but lacks details on error cases, performance, or integration with siblings. Without annotations or output schema, more behavioral context would improve completeness for safe agent use.

  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 description adds minimal value beyond the input schema, which has 100% coverage. It mentions 'custom styling' and 'multiple visual styles,' hinting at the 'style' parameter, but doesn't elaborate on the semantics of styles or other parameters. With high schema coverage, the baseline is 3, as the schema already documents parameters well.

  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: 'Generate a QR code with custom styling.' It specifies the verb ('Generate') and resource ('QR code'), and mentions the output format ('base64-encoded SVG image data'). However, it doesn't explicitly differentiate from sibling tools like 'generate_qr_urls_batch' (batch processing) or 'preview_qr_url' (preview functionality), which would be needed for a score of 5.

  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?

  The description provides no guidance on when to use this tool versus alternatives. It mentions 'custom styling' and 'multiple visual styles,' but doesn't compare to siblings like 'generate_qr_urls_batch' for bulk operations or 'preview_qr_url' for testing. There's no explicit when/when-not usage context, leaving the agent to infer based on tool names alone.

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

• preview_qr_urlA
  3.8/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: the tool generates a shareable URL (not the QR image itself) and that the URL leads to a web interface for viewing, customizing, and downloading. However, it omits details like authentication requirements, rate limits, or whether the URL is permanent, which are important for a tool involving web resources.

  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 in the first sentence and adds useful context in the second. Both sentences earn their place by clarifying the output and its use, with zero wasted words, making it highly efficient and well-structured.

  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 moderate complexity (2 parameters, no output schema, no annotations), the description is mostly complete. It explains what the tool does and the nature of the output (a web interface link), but it could improve by addressing potential behavioral gaps like URL lifespan or error handling. Since there's no output schema, the description adequately covers the return value context.

  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, so the schema already documents both parameters ('url' and 'style') adequately. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, but it doesn't need to compensate since the schema is comprehensive. Baseline 3 is appropriate here.

  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 ('Generate a shareable web preview URL for a QR code') and the resource ('QR code'), distinguishing it from sibling tools like 'generate_qr_code' (which likely creates the QR image directly) and 'generate_qr_urls_batch' (which handles multiple). The verb 'generate' and target 'web preview URL' are precise.

  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 by mentioning the output ('a link to the web interface where users can view, customize, and download the QR code'), suggesting it's for interactive previews rather than direct generation. However, it lacks explicit guidance on when to use this tool versus alternatives like 'generate_qr_code' or 'get_available_styles', leaving the context somewhat inferred.

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

• generate_qr_urls_batchA
  3.9/5.0
  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. It discloses key behavioral traits: the tool generates download URLs, returns a ZIP file, and has a maximum batch size of 100 URLs. However, it lacks details on permissions, rate limits, error handling, or what happens if URLs are invalid, which are important for a batch processing 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?

  The description is front-loaded with the core purpose, followed by usage context and key constraints, all in three concise sentences with zero waste. Each sentence earns its place by adding value without 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 the tool's moderate complexity (batch processing with 2 parameters) and no annotations or output schema, the description is adequate but has gaps. It covers the purpose, output format, and limits, but lacks details on authentication, error responses, or file naming conventions in the ZIP, which could be helpful for an 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 fully documents both parameters. The description adds no additional meaning beyond what the schema provides, such as explaining parameter interactions or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

  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 ('Generate QR code download URLs'), resource ('multiple URLs at once'), and distinguishes from siblings by emphasizing batch processing for multiple URLs versus single QR generation. It explicitly mentions the output format (ZIP file) and scope (max 100 URLs).

  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 context for when to use this tool ('Perfect for batch processing CSV files or lists'), but does not explicitly mention when not to use it or name alternatives like 'generate_qr_code' for single URLs. It implies usage for bulk operations without detailing exclusions.

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

• get_available_stylesA
  4.4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It describes the tool as a read operation ('Get a list'), which implies it's non-destructive and likely read-only, but doesn't explicitly state permissions, rate limits, or return format details. The description adds basic behavioral context but lacks depth for a tool with no annotation coverage.

  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 with zero waste: the first states the purpose, and the second provides usage guidelines. It is front-loaded with the core action and efficiently conveys all necessary information 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 low complexity (0 parameters, no output schema, no annotations), the description is mostly complete. It covers purpose and usage well, but lacks details on return format or behavioral traits like error handling. For a simple list tool, this is sufficient but not exhaustive.

  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 input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, focusing instead on the tool's purpose and usage. A baseline of 4 is applied as it compensates well for the lack of parameters by providing clear context.

  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 ('Get a list') and resource ('all available QR code style presets with their color schemes'), distinguishing it from sibling tools like generate_qr_code which creates codes, generate_qr_urls_batch which batches generation, and preview_qr_url which previews URLs. It explicitly identifies what is being retrieved and why.

  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 explicitly states when to use this tool: 'Use this to discover styling options before generating QR codes.' This provides clear context for usage (pre-generation discovery) and implies an alternative (use other tools for actual generation), guiding the agent effectively.

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