Server Quality Checklist

Tool Scores

• fetch_imageC
  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 full burden. It mentions the tool fetches from 'any accessible web URL' and returns in a 'format that Claude can display,' but lacks details on error handling, authentication needs, rate limits, or what 'accessible' entails. For a network tool with zero annotation coverage, this is insufficient.

  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 concise and well-structured with two sentences that directly address purpose and usage. It avoids redundancy and is front-loaded with the core functionality. However, the second sentence could be slightly more informative.

  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 has an output schema (which handles return values) and high schema coverage, the description is minimally adequate. However, for a network-based tool with no annotations, it should provide more behavioral context like error cases or accessibility constraints to be fully complete.

  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 (url and timeout). The description adds no additional parameter semantics beyond what the schema provides, such as URL format constraints or timeout implications. Baseline 3 is appropriate when schema does the heavy lifting.

  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: 'Fetch an image from a URL and return it as an image.' It specifies the verb (fetch), resource (image), and outcome (return as image). However, it doesn't explicitly differentiate from sibling tools like fetch_json and fetch_url, which likely handle different data types.

  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 minimal usage guidance: 'This tool allows Claude to retrieve images from any accessible web URL.' It implies use for image retrieval but offers no explicit when-to-use vs. alternatives, no prerequisites, and no mention of sibling tools for comparison.

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

• fetch_urlC
  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 of behavioral disclosure. It mentions that content is returned as text and is suitable for text-based content types, but lacks details on error handling, rate limits, authentication needs, or what happens with non-text content. For a tool with no annotations, this leaves significant behavioral gaps.

  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 the core purpose stated first. It consists of three sentences that are relevant, though the second sentence ('This tool allows Claude to retrieve content...') could be considered slightly redundant with the first. Overall, it's efficient with minimal waste.

  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 that an output schema exists (as indicated in context signals), the description doesn't need to explain return values. However, with no annotations and three parameters, the description could do more to address behavioral aspects like error cases or limitations. It's adequate but has clear gaps in completeness for a tool with no annotations.

  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 (url, headers, timeout) thoroughly. The description doesn't add any parameter-specific information beyond what the schema provides. According to the rules, with high schema coverage (>80%), the baseline is 3 even with no param info in the description.

  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: 'Fetch content from a URL and return it as text.' It specifies the verb ('fetch'), resource ('content from a URL'), and outcome ('return it as text'). However, it doesn't explicitly differentiate from sibling tools like fetch_image and fetch_json, which likely handle different content types.

  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 minimal usage guidance. It mentions 'any accessible web URL' and suitability for 'HTML, plain text, and other text-based content types,' but doesn't specify when to use this tool versus fetch_image or fetch_json, nor does it provide exclusions or alternatives. No explicit when/when-not guidance is present.

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

• fetch_jsonA
  4/5.0
  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 key behaviors: fetching from URLs, parsing JSON, and formatting output. However, it doesn't mention error handling, authentication needs, rate limits, or what happens with non-JSON responses. The description adds basic context but lacks comprehensive behavioral disclosure.

  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 focused sentences that each earn their place. The first sentence states the core functionality, and the second provides additional context about accessibility and formatting. No wasted words, well-structured, and front-loaded with the main purpose.

  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 (HTTP request with JSON parsing), no annotations, but 100% schema coverage and an output schema exists, the description is reasonably complete. It covers the main purpose and formatting behavior, though additional context about error cases or authentication would improve completeness for a tool making external requests.

  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 three parameters thoroughly. The description doesn't add any parameter-specific information beyond what's in the schema. It mentions 'any accessible web URL' which reinforces the url parameter but doesn't provide additional semantic context for headers or timeout.

  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 ('fetch JSON from a URL, parse it, and return it formatted') and distinguishes it from sibling tools (fetch_image, fetch_url) by specifying JSON data retrieval and parsing. It explicitly mentions 'prettified for better readability' which adds 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 clear context about when to use this tool ('retrieve and parse JSON data from any accessible web URL'), but doesn't explicitly state when NOT to use it or mention alternatives like fetch_url for non-JSON content. It implies usage for JSON data specifically, which is helpful but not fully comparative.

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