Server Quality Checklist

Tool Scores

• fetch-textC
  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 'various HTTP methods' and 'defaults to converting HTML to Markdown format,' which adds some context about functionality. However, it doesn't cover critical aspects like error handling, rate limits, authentication needs, or what happens with non-HTML content, leaving significant gaps for a tool that interacts with external URLs.

  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 a single, efficient sentence that front-loads the core purpose. It avoids unnecessary details, though it could be slightly more structured by explicitly separating key points. Overall, it's concise with minimal waste.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (5 parameters, no annotations, no output schema), the description is incomplete. It lacks details on behavioral traits, error handling, and output specifics, which are crucial for a tool fetching content from URLs. The schema covers parameters well, but the description doesn't compensate for missing annotations or output schema, leaving the agent with insufficient 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?

  Schema description coverage is 100%, so the schema already documents all parameters thoroughly. The description adds minimal value beyond the schema, mentioning 'various HTTP methods' and 'defaults to converting HTML to Markdown format,' which loosely relates to 'method' and 'output_format' parameters but doesn't provide additional semantics. Baseline 3 is appropriate as the 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 text content from a URL using various HTTP methods.' It specifies the resource (URL) and action (fetch text content), but doesn't explicitly differentiate from sibling tools like 'fetch-json' or 'batch-fetch-text' beyond mentioning 'text content' and 'Markdown format.' This makes it clear but not fully sibling-distinctive.

  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 like 'fetch-json' or 'batch-fetch-text.' It mentions 'various HTTP methods' and 'defaults to converting HTML to Markdown format,' which implies some context, but lacks explicit when-to-use or when-not-to-use statements, leaving the agent to infer usage scenarios.

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

• batch-fetch-textA
  3.7/5.0
  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: concurrent execution for performance and support for various HTTP methods beyond GET. However, it lacks details on error handling, rate limits, authentication needs, timeout behavior, or what 'raw text content' specifically entails (e.g., encoding, size limits).

  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 extremely concise with two sentences that are front-loaded and waste-free. The first sentence covers purpose and scope, while the second adds performance context, with every word earning its place.

  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 (batch HTTP operations with multiple methods and output formats), no annotations, and no output schema, the description is incomplete. It doesn't explain return values, error formats, or important behavioral constraints like concurrency limits or timeouts, leaving significant gaps for an AI agent to use it correctly.

  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%, providing detailed documentation for the single parameter 'requests' and its nested properties. The description adds minimal value beyond the schema, only implying that requests are executed concurrently. No additional parameter semantics are explained in the description.

  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 ('batch fetch raw text content'), target resource ('from multiple URLs'), and method ('using various HTTP methods'). It distinguishes from sibling tools by specifying 'raw text content' rather than JSON, and mentions concurrent execution for performance.

  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 'batch fetch' and 'multiple URLs,' suggesting this is for bulk operations rather than single requests. However, it doesn't explicitly state when to use this tool versus alternatives like 'batch-fetch-json' or 'fetch-text,' nor does it mention any prerequisites or exclusions.

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

• batch-fetch-jsonA
  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 effectively describes key behaviors: concurrent execution for performance, deduplication optimization, and support for multiple HTTP methods with request bodies. However, it lacks important details like error handling, timeout behavior, authentication requirements, or rate limits that would be needed for a complete behavioral picture.

  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 efficiently structured with four focused sentences that each add value: states the core purpose, describes JSONPath support, explains performance optimizations, and notes HTTP method flexibility. There's zero wasted text, and the most important information (batch JSON extraction with JSONPath) appears first.

  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 good coverage of the core functionality but has significant gaps. It explains what the tool does and some behavioral aspects, but doesn't describe the return format, error responses, or important operational constraints. Given the complexity of batch HTTP operations with JSON processing, more completeness would be expected.

  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 schema already documents all parameters thoroughly. The description adds some context about JSONPath extensions and concurrent execution, but doesn't provide significant additional parameter semantics beyond what's in the schema. The baseline of 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 ('batch extract JSON content'), resource ('from multiple URLs'), and mechanism ('with different extended JSONPath patterns'). It distinguishes from sibling tools by specifying JSON extraction (vs. text extraction in batch-fetch-text) and batch processing (vs. single URL in fetch-json).

  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 (batch JSON extraction with JSONPath patterns) and implicitly distinguishes from batch-fetch-text (JSON vs. text) and fetch-json (batch vs. single). However, it doesn't explicitly state when NOT to use it or name specific alternatives, missing the highest score criteria.

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

• fetch-jsonA
  3.9/5.0
  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 behavioral traits like default HTTP method (GET), handling of omitted patterns, and support for extended JSONPath features. However, it lacks details on error handling, rate limits, authentication needs, or response formats, which are important for a tool making HTTP requests.

  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 appropriately sized and front-loaded: the first sentence states the core purpose, followed by key features and defaults. Every sentence adds value, such as explaining pattern behavior and HTTP method support, with no redundant or wasted 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?

  Given the complexity (5 parameters, HTTP operations, JSONPath features) and no annotations or output schema, the description is partially complete. It covers basic usage and features but lacks details on error cases, authentication, rate limits, or return value structure, which are crucial for an HTTP-based tool with extended functionality.

  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 some context, such as the effect of omitting 'pattern' and default HTTP method, but does not provide significant additional meaning beyond the schema. Baseline 3 is appropriate as 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 tool's purpose: 'Extract JSON content from a URL using JSONPath with extended features.' It specifies the verb ('extract'), resource ('JSON content'), and method ('JSONPath'), and distinguishes itself from sibling tools like fetch-text (which handles text) and batch-fetch-json (which handles multiple 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 usage: 'If 'pattern' is omitted or empty, the entire JSON document is returned' and 'Supports different HTTP methods (default: GET).' It implies when to use this tool (for JSON extraction with JSONPath) versus fetch-text (for text extraction), but does not explicitly name alternatives or state exclusions, such as when to prefer batch-fetch-json for multiple URLs.

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