Server Quality Checklist

Tool Scores

• dompruner_analyzeA
  3.6/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the burden of behavioral disclosure. It states what is returned (report, counts, anchors) but does not disclose whether the tool fetches the URL, side effects, rate limits, or error behaviors. It is non-misleading 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?

  A single, front-loaded sentence that conveys the primary action and key output metrics. No filler words; every element contributes to understanding the tool's 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?

  The tool is simple (one param, no output schema), and the description adequately covers the return content (render type, token counts, anchors). It lacks context about error handling or prerequisites (e.g., valid URL), but is sufficiently complete for a basic analysis tool.

  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 100% (single 'url' parameter described as 'URL to analyze'). The description adds no further param semantics beyond the schema, so baseline 3 applies per the rubric.

  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 it returns a token-reduction analysis report for a URL, listing specific output elements (render type, token counts, Semantic Anchors). This clearly distinguishes it from a generic fetch tool, though it does not explicitly name the sibling.

  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?

  Usage is implied: use this to get a token-reduction analysis report for a URL. No explicit alternatives or exclusions are mentioned, but the sibling name 'dompruner_fetch' strongly suggests a different purpose. There is no guidance on when to choose one over the other.

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

• dompruner_sitemapA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden of disclosing behavior. It explains automatic sitemap index handling, DOM-pruned Markdown output, and a stated 90%+ token reduction. It does not detail failure modes or side effects (e.g., network load), but for a read-only crawler, the provided transparency is reasonably good.

  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 and well-structured: the first sentence states the core action, the second frames the ideal use case, and the third gives a parameter tip. No unnecessary words or repetition, making it appropriately sized and front-loaded.

  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?

  The description gives a good overall picture of the tool's purpose, capabilities, and typical use case. It covers the return type ('DOM-pruned Markdown'), automatic handling of sitemap indexes, and a filtering example. Lacking an output schema, it does not detail the exact response structure, but for a six-parameter tool with no annotations, this is reasonably 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?

  The input schema already provides 100% coverage with descriptions for all six parameters, so the baseline is 3. The description adds value by giving a concrete example for filter_urls ('/docs/', '/tutorial/'), but this is more of a usage guideline than new semantic meaning. Overall, the description does not significantly enhance parameter understanding beyond the schema.

  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 core function: 'Fetches all pages listed in a sitemap.xml and returns DOM-pruned Markdown for each.' It also specifies the scope (entire documentation sites) and a unique capability ('Handles sitemap indexes automatically'), which distinguishes it from sibling tools like dompruner_fetch.

  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 a clear use case: 'Ideal for ingesting entire documentation sites into an LLM context.' It also offers a practical tip: 'Use filter_urls to limit to a path prefix (e.g. /docs/, /tutorial/).' However, it does not explicitly mention when not to use this tool or name alternative sibling tools, so it falls slightly short of a 5.

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

• dompruner_fetchA
  4.8/5.0
  Behavior5/5

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

  With no annotations, the description carries the full burden and does so excellently. It discloses key behaviors: DOM pruning with 90%+ token reduction, preservation of original text (no summarization), BM25 section filtering, and the unusual URL-sampling behavior when url is omitted. This goes beyond basic expectations and covers potential surprises.

  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 well-structured, starting with a strong directive, then behavior, workflow, and filtering capability. It is slightly lengthy but every sentence contributes value; no filler or tautology.

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

  Completeness5/5

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

  For a 2-parameter tool with no output schema and no annotations, the description is impressively complete. It covers alternatives, usage scenarios, special behaviors, and expected output format (Markdown). The workflow guidance leaves little room for agent confusion.

  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 coverage is 100%, so the baseline is 3. The description adds meaningful context beyond schema: it explains how query enables BM25 filtering and can trigger URL sampling from the host LLM when url is absent. This enriches the parameter definitions without redundancy.

  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 it fetches a URL and returns DOM-pruned Markdown, with a specific verb, resource, and outcome. It explicitly differentiates itself from WebFetch and aligns with sibling tools by name (fetch vs. sitemap/analyze), leaving no ambiguity about its function.

  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?

  It gives an explicit directive to use this instead of WebFetch, and provides a step-by-step workflow for both known and unknown URLs. It also explains when to use the query parameter for BM25 filtering, offering clear context for appropriate usage.

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