Server Quality Checklist

Tool Scores

• typeconversionB
  3.3/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It mentions 'supports pretty printing, minification, and format-specific options' which adds some behavioral context, but doesn't cover important aspects like error handling, performance characteristics, limitations, or what happens with malformed input data.

  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 and front-loaded. The first sentence establishes the core purpose, and the second sentence efficiently lists key capabilities. Every word earns its place with zero wasted text.

  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 4 parameters (3 required), 75% schema coverage, no annotations, and no output schema, the description provides adequate but incomplete context. It covers the what and some how, but lacks information about error cases, performance, limitations, and output format details that would be needed for comprehensive 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 description coverage is 75%, so the schema already documents most parameters well. The description adds value by mentioning 'pretty printing, minification, and format-specific options like CSV delimiters and headers' which gives context for the 'options' parameter, but doesn't provide additional semantic meaning beyond what the schema already covers for other parameters.

  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 purpose with specific verbs ('convert data between different formats') and resources (JSON, XML, YAML, CSV, TOML). It distinguishes itself from sibling tools (webfetch, websearch) by focusing on data format conversion rather than web operations.

  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 on when to use this tool versus alternatives. While it's clearly different from sibling tools (webfetch, websearch), there's no mention of when to choose type conversion over other data processing methods or what scenarios it's best suited for.

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

• websearchA
  3.7/5.0
  Behavior2/5

  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 states what the tool does and returns ('Returns a list of search results with titles, URLs, and snippets'), but lacks details on rate limits, authentication needs, error handling, or performance characteristics. It mentions 'advanced filtering options' but doesn't explain behavioral implications like how filters affect results or latency.

  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 efficiently adds details in the second sentence without redundancy. Every sentence earns its place by conveying essential information about functionality and output, making it appropriately sized and well-structured.

  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 complexity (4 parameters with nested objects, no output schema, and no annotations), the description is adequate but has gaps. It covers the basic purpose and output format, but lacks details on error cases, pagination, or how the tool integrates with the search engines listed. Without annotations or output schema, more behavioral context would improve completeness for this multi-engine search tool.

  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?

  Schema description coverage is 75%, so the schema documents most parameters well. The description adds value by summarizing the purpose ('Search the web using various search engines... with advanced filtering options') and hinting at the 'filters' parameter's role, but doesn't provide additional semantic context beyond what the schema already covers for individual parameters like 'query' or 'engine'.

  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 ('Search the web') with the resource ('using various search engines') and distinguishes it from sibling tools like 'typeconversion' and 'webfetch' by focusing on search functionality rather than conversion or fetching. It explicitly mentions the verb 'Search' and the scope 'with advanced filtering options'.

  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 web searching with filtering, but provides no explicit guidance on when to use this tool versus alternatives like 'webfetch' (which might retrieve specific URLs) or other search methods. It mentions 'various search engines' but doesn't specify when to choose one over another or any exclusions.

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

• webfetchA
  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 of behavioral disclosure. It mentions 'fetch and parse HTML content' and configuration options like timeout and redirect handling, which provides some behavioral context. However, it doesn't address important aspects like error handling, rate limits, authentication requirements, or what happens with malformed URLs or network failures.

  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 and front-loaded, packing comprehensive information into two efficient sentences. Every phrase ('fetch and parse HTML content,' 'extract text...') earns its place without redundancy or unnecessary elaboration.

  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 complexity (4 parameters, nested objects, no output schema, and no annotations), the description is adequate but has gaps. It covers the core functionality and parameters well, but lacks details on return values, error conditions, and behavioral constraints that would be important for an AI agent to use this tool effectively.

  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 description adds meaningful context beyond the schema by explaining the purpose of extraction ('extract text, headings, links, metadata, images') and configuration options ('supports timeout configuration, custom user-agent, and redirect handling'). With 75% schema description coverage, the description compensates well by providing semantic understanding of what the parameters achieve, though it doesn't detail all parameter interactions.

  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 purpose with specific verbs ('fetch and parse HTML content') and resources ('from any URL'), distinguishing it from sibling tools like typeconversion and websearch. It explicitly mentions extraction capabilities and configuration options, providing comprehensive purpose definition.

  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 context through phrases like 'extract text, headings, links, metadata, images' and 'supports timeout configuration,' suggesting when to use this tool for web content extraction. However, it lacks explicit guidance on when to choose this tool versus the websearch sibling tool or any exclusion criteria.

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