Server Quality Checklist

Tool Scores

• screenshot_to_markdownB
  3.1/5.0
  Behavior2/5

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

  No annotations provided; description lacks any behavioral details such as side effects, latency, or auth requirements. Merely restates functionality.

  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?

  Two concise sentences, front-loaded with core action and use case, no unnecessary words. Could include more detail without bloat.

  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?

  No output schema; description does not explain return format or structure. Lacks error scenarios and limitations, making it incomplete for complex use.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 50% but description does not add any meaning beyond schema. No mention of parameters, leaving agents to infer from schema alone.

  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?

  Description clearly states the tool takes a screenshot and converts to markdown, distinguishing from text-based alternatives like extract_article.

  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?

  Explicitly mentions use case 'when text extraction is insufficient' and implies text extraction as alternative, providing clear context.

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

• extract_articleA
  3.9/5.0
  Behavior3/5

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

  With no annotations, the description bears full burden for behavioral disclosure. It mentions 'advanced content extraction' and that output includes 'main article text, metadata, and reading stats.' However, it omits details on handling non-article URLs, rate limits, or whether the tool modifies state. This is adequate but not comprehensive.

  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 with no repetition or filler. The first sentence precisely states the action and output, the second adds context on use cases and extraction quality. Every word earns 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 5 nested options and no output schema, the description should clarify return structure more. It specifies markdown with metadata and stats but not error handling, pagination, or behavior for non-article content. This is sufficient for basic understanding but incomplete for advanced 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 coverage is 50% meaning two top-level params exist but options lacks a description. The description adds value by mentioning 'metadata and reading stats,' which relates to the include_metadata option. However, it does not explain other options like max_length or remove_nav, so compensation is partial.

  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 action ('Extract clean article content from any URL'), the resource ('any URL'), and the output format ('agent-optimized markdown'). It further specifies domains ('news, blogs, documentation'), which helps differentiate from siblings like extract_structured_data.

  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 indicates ideal usage contexts ('Perfect for agents processing news, blogs, documentation.') but does not explicitly state when to avoid the tool or mention alternatives like extract_links for non-article content. This still provides clear guidance for typical use.

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

• extract_linksA
  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 full burden. It mentions 'intelligent categorization' but does not explain specifics like deduplication, ordering, or compliance with robots.txt. More detail on behavioral traits would improve 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 concise with two sentences: the first covers purpose and output, the second provides use cases. No unnecessary words, efficiently front-loaded.

  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?

  While the description covers the tool's core functionality, it lacks details on error handling, output format, or behavior with large sets of links. Given the absence of an output schema, more completeness would aid agent 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 coverage is 50%, and the description adds some context about categorization and context but does not explicitly map to parameters like filter_options. The description provides general semantics but could better explain how parameters affect the intelligent categorization.

  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 extracts all links from a webpage, with categorization and context, returning internal/external links, link text, and destination context. It explicitly distinguishes from sibling tools like extract_article and extract_structured_data, making its purpose unambiguous.

  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 use cases (competitive analysis, site mapping, link discovery) but does not explicitly state when not to use it or compare to alternatives. However, the context is sufficient for an agent to decide.

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

• extract_structured_dataA
  3.9/5.0
  Behavior3/5

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

  Without annotations, the description must carry the full burden. It explains what the tool does (extract structured data as JSON) but does not disclose important behaviors like failure modes, dynamic content handling (though the javascript_enabled parameter hints at it), rate limits, or authentication needs. Some transparency but incomplete.

  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 action and results. Every sentence serves a purpose: first defines the tool, second adds context for when to use it. No redundant or verbose language.

  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 three parameters, nested objects, and no output schema, the description is minimal. It does not describe the structure of the returned JSON, how multiple data_types interact, or any error handling. While adequate for a simple tool, it lacks completeness for an agent to fully anticipate behavior.

  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 67%, so baseline is 3. The tool description does not add any additional meaning beyond the schema's parameter descriptions (e.g., explaining how options affect extraction or the nuances of data_types). It simply reiterates the overall purpose without enhancing parameter understanding.

  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 verb 'Extract structured data' and the resource 'any webpage', with explicit output format 'as JSON'. It lists specific data types like tables, lists, key-value pairs, and gives use cases (pricing lists, feature comparisons), distinguishing it from sibling tools that handle articles, links, or screenshots.

  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 context on when to use the tool (e.g., processing data tables, pricing lists, feature comparisons) but does not explicitly contrast with sibling tools like extract_article or extract_links. It lacks explicit when-not-to-use guidelines, but the use-case examples are sufficient to guide selection.

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

• batch_extractA
  4.2/5.0
  Behavior4/5

  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: parallel processing, rate limiting, error recovery, and configurable extraction type. It does not mention any destructive actions (likely read-only), and the error recovery ('continue_on_error' default true) is noted. Lacks details on output format but sufficient for a non-destructive 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?

  Three sentences: core function, use cases, key features. No wasted words, front-loaded with action. Every sentence adds value.

  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?

  For a batch processing tool with three top-level parameters (one nested) and no output schema, the description covers the main functionality and key behaviors. It lacks explicit details on the consolidated result format but is sufficient for an agent to infer typical usage. Additional output schema would improve completeness.

  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 high (67%+), so baseline is 3. The description adds context like 'highly efficient' and 'rate limiting' but does not significantly enhance parameter understanding beyond what the schema provides. The schema already describes each parameter's usage well.

  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 'process multiple URLs in parallel and return consolidated results', specifying the action (process multiple URLs), resource (URLs), and output (consolidated results). It distinguishes from siblings like extract_article (single URL) by emphasizing batch processing and parallel execution.

  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 usage context: 'Highly efficient for agents that need to analyze multiple pages, compare content, or do batch research.' It implies use for multi-URL tasks, implicitly contrasting with single-URL sibling tools. However, it does not explicitly state when not to use or name alternatives directly.

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