Server Quality Checklist

Tool Scores

• fetch_multipleA
  4.3/5.0
  Behavior3/5

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

  Describes concurrency and per-result token cap, but no annotations present. Lacks details on error handling, rate limits, or caching behavior beyond defaults.

  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?

  Well-structured into purpose, when-to-use, args, and returns. No redundant sentences, every line contributes.

  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?

  Covers purpose, usage, parameters, return shape, and concurrency limit. Could include error behavior or more details on caching, but overall sufficient for a fetch tool.

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

  Parameters5/5

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

  Provides clear explanations for all three parameters: url limit and splitting, max_tokens_each token budget guidance, and use_cache caching behavior. Adds significant value over schema-only info.

  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?

  Clearly states 'Fetch up to 20 URLs concurrently' with a specific verb and resource. Distinguishes from sibling tools by highlighting concurrency and batch limit.

  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?

  Includes 'WHEN TO USE' section explicitly describing scenarios. Mentions splitting large batches but does not explicitly state when not to use or name alternatives like fetch_url.

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

• search_and_fetchA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description effectively discloses the combined search-and-fetch behavior and the return format. However, it lacks details on error handling or failure scenarios for individual result fetches.

  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 with a header and 'WHEN TO USE' section, making it easy to parse. It is concise yet informative, though the parameter descriptions could be integrated more succinctly.

  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 adequately covers the tool's purpose, usage, parameters, and return format. Given no output schema, the return shape is documented. Missing details on partial failures or edge cases, but overall sufficient for this combined tool.

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

  Parameters5/5

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

  Despite zero schema coverage, the description fully compensates by specifying constraints (query 2-500 chars, num_results 1-10, max_tokens_each default 2000) and explaining each parameter's role, adding substantial 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 'Web search + fetch top results in one call,' which precisely defines the tool's combined action. It distinguishes itself from siblings like fetch_url and fetch_multiple by highlighting the aggregation of search and fetch into one step.

  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 includes a 'WHEN TO USE' section that explicitly recommends the tool for research questions rather than specific URLs. It contrasts with the alternative of using separate search and fetch tools, providing clear guidance on when to prefer this tool.

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

• estimate_tokensA
  4.9/5.0
  Behavior5/5

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

  No annotations exist, but the description fully discloses behavior: no body fetch, 10x cheaper, fallback when Content-Length missing, and return structure with confident flag.

  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?

  Well-structured with sections, but includes a full return example that is slightly verbose yet informative.

  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 one-parameter tool, the description covers purpose, usage, fallback, and return format completely, compensating for lack of output schema.

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

  Parameters5/5

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

  Schema has 0% coverage, but the description includes an 'Args' section explaining the url parameter, adding 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 estimates token count without fetching the body, and distinguishes from sibling tools like fetch_url by emphasizing it does not fetch the body.

  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?

  Explicitly provides when-to-use (unsure about context window, triaging URLs) and when-not-to-use (if confident=false, use fetch_url with max_tokens).

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

• fetch_urlA
  4.9/5.0
  Behavior5/5

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

  No annotations exist, so the description fully bears the transparency burden. It discloses caching (6h), auto-routing to multiple fetchers, cost estimates, and return structure including error handling. This far exceeds minimal requirements.

  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 with sections, bullet points, and a return format sample. While fairly long, every sentence adds value—usage guidance, parameter details, and return schema. Minor conciseness loss from repetition of 'WHEN TO USE' structure.

  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?

  Despite no output schema and no annotations, the description compensates fully: explains return structure in detail, caching behavior, fetcher selection logic, cost implications, and context window management (max_tokens). An agent has everything needed to invoke correctly.

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

  Parameters5/5

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

  Schema description coverage is 0%, so the description must add context for all parameters. It explains url (implicit), max_tokens (hard cap, default unlimited, context budget advice), format (default markdown, recommended), and use_cache (default true, when to pass false). Each parameter gets meaningful guidance 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 opens with 'Fetch any URL and return clean, LLM-ready Markdown' clearly stating the verb+resource+output quality. It explicitly distinguishes from siblings 'search_and_fetch' and 'fetch_multiple' in the WHEN NOT TO USE section.

  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 WHEN TO USE and WHEN NOT TO USE sections provide explicit scenarios (e.g., specific URL, JS-rendered, PDF, paywall) and name alternative tools. This gives clear guidance on when to invoke this tool versus its siblings.

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