Server Quality Checklist

Tool Scores

• fetch_parsedA
  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 responsibility for behavioral disclosure. It mentions the ScrapeUnblocker mechanism and that output is AI-parsed structured JSON, providing some transparency about the process. However, it does not disclose potential non-determinism of AI parsing, possible errors, or side effects of scraping (e.g., rate limits, target site load).

  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 function, and every sentence adds value. It avoids unnecessary elaboration and is highly scannable.

  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?

  With no output schema and no annotations, the description is somewhat incomplete: it doesn't describe the expected JSON structure or mention that AI-parsed output may vary in shape. It covers the main purpose and use cases, but for a tool with unstructured AI output, a note about variability or potential failure 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 100%, so all parameters are already documented in the schema. The description adds context about typical extraction targets (product details, article content), which implicitly informs rules_hint, but does not add significant new meaning 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 function: fetching a web page through ScrapeUnblocker and returning AI-parsed structured JSON instead of raw HTML. It specifies use cases (product details, article content), distinguishing it from the sibling fetch_html which presumably returns raw HTML.

  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 usage context: 'Best for extracting fields from product, listing or article pages without writing your own HTML parsing.' It implicitly contrasts with raw HTML retrieval, suggesting when not to use it, but does not explicitly name the alternate tool or exclusions beyond that.

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

• google_searchA
  4/5.0
  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 adds useful context by mentioning ScrapeUnblocker as the execution path and 'organic results' as an output filter. However, it omits potential behavioral details like rate limits, pagination behavior, error responses, or any caveats about scraping Google.

  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: the first states the action and output, the second states the use case. Every clause contributes value, and it is front-loaded with the core purpose. No redundancy or fluff.

  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 covers what the tool does, how it does it, and when to use it. Since there is no output schema, it would benefit from specifying more about the returned JSON structure, but 'discover URLs' implies the key output. Given the simple parameter set and clear sibling relationship, this is largely complete but could be more detailed.

  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?

  All three parameters (keyword, proxy_country, pages_to_check) have complete schema descriptions (100% coverage), so the baseline is 3. The tool description adds no parameter-specific nuance, but it doesn't need to because the schema already explains them 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 states a specific action and resource: 'Run a Google search through ScrapeUnblocker and return the organic results as structured JSON.' It clearly distinguishes this from sibling tools (fetch_html, fetch_parsed) by emphasizing search results rather than page content.

  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 line 'Use this to discover URLs before fetching them' gives clear usage context and positions this tool as a discovery step relative to fetch tools. It does not explicitly name alternatives or state when not to use, but the guidance is clear enough.

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

• list_elementsA
  4.4/5.0
  Behavior4/5

  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 the read-only nature, that it does not interact with the page, and that it loads the page through ScrapeUnblocker. It does not mention rate limits or how 'notable' elements are selected, but for a read-only discovery tool this is reasonable coverage.

  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 with no filler: the first states core purpose and output, the second emphasizes read-only behavior, and the third gives the workflow context. All information earns its place and the most important details are 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?

  Since there is no output schema, the description explains the return value (JSON list with selector, tag, text, attributes) sufficiently. It also connects the tool to the broader fetch_html workflow. Minor gaps such as empty results or blocked pages are not covered, but they are not essential for correct selection and invocation.

  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%: url is described as 'The absolute URL whose elements you want to list' and proxy_country as 'Optional ISO country code to route through'. The tool description adds no extra parameter context, but with full schema coverage the baseline of 3 is appropriate.

  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 states a specific verb and resource: loads a page and returns a JSON list of notable elements with ready-to-use selectors and attributes. It also distinguishes itself from the sibling fetch_html by positioning itself as the 'discovery half of interactive scraping' and explicitly noting it is read-only.

  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?

  The description gives a direct usage workflow: 'call list_elements to find the selectors you need, then pass matching steps to fetch_html'. It also clarifies that the tool does not interact with the page, implying that fetch_html is for interaction, which serves as an alternative and exclusion.

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

• fetch_htmlA
  4.5/5.0
  Behavior4/5

  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 important behaviors: bypasses anti-bot protection, steps are not idempotent and run once per call, and failed steps return the failing step, reason, and page HTML at that moment. This is strong behavioral disclosure, though it omits potential costs, rate limits, or output size caveats.

  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 dense but every sentence serves a purpose: the main behavior, the bypass value, the step workflow, the selector discovery guidance, and the failure semantics. It front-loads the core purpose and keeps related operational details together. No filler or repetition.

  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 tool with no annotations and no output schema, the description is remarkably complete. It covers the main use case, the fallback trigger, step semantics, failure behavior, return format, and the recommended workflow with list_elements. The 100% schema coverage for parameters fills the remaining gaps, so nothing critical is missing.

  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 semantics beyond the schema by explaining that `steps` are an ordered list run after page load, that selectors should be discovered via list_elements, and that steps are non-idempotent. Other parameters like `wait_method` and `proxy_country` are adequately covered by the schema itself.

  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?

  States a specific verb and resource ('Fetch the fully rendered HTML of any web page') and immediately distinguishes itself by naming the anti-bot bypass use case. The scope is unambiguous and clearly separates it from the sibling tools like fetch_parsed and google_search.

  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 tells the agent when to use it: when a normal fetch is blocked (403/429, captcha, 'access denied') or when a real browser is needed for rendering. It also gives a workflow for interactive pages (use list_elements first, then build steps). It doesn't explicitly name the alternative tool for parsed content or state when not to use it, but the usage context is clear.

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