Server Quality Checklist

Tool Scores

• cloudflare_ai_bot_auditA
  4/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of disclosing behavior. It explicitly states 'Read' (non-destructive), which is the most critical trait, and additionally documents required environment variables and authentication method. It does not elaborate on error cases or return format, but for a simple read operation this is sufficient.

  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?

  Two sentences, each earning its place: the first states the core purpose and scope, the second specifies authentication requirements. No filler or redundant content.

  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 simple read tool with one parameter and no output schema, the description is largely complete: it lists the settings read, the domain, and the auth prerequisites. It does not describe the return structure, but the absence of an output schema makes that less critical. Minor gaps like error handling or zone-not-found behavior keep it from a 5.

  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 covers 100% of the single parameter (domain), giving its format and example. The description adds no new parameter semantics beyond what the schema already provides, so the baseline score 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 clearly states the specific action ('Read a Cloudflare zone's Bot Management AI-bot settings') and enumerates the exact settings covered. The resource (Cloudflare zone) and the tool's focus are unambiguous, naturally distinguishing it from sibling tools despite not naming them.

  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 by stating what it reads and for which domain, but it does not provide explicit guidance on when to use this tool over alternatives, nor any exclusions. There is no mention of when not to use it or how it relates to sibling tools.

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

• check_visibilityA
  4.1/5.0
  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 explains the tool fetches a live resource and checks for specific bot names, which implies it's a read-only network operation. However, it doesn't disclose that it may make external requests, handle timeouts, or fail on invalid URLs. Given no annotations, the description does some work but misses key behavioral details.

  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 sentence, well-structured, and front-loaded with the tool's purpose. It is concise but covers the main actions without unnecessary detail. It earns its place but could be slightly more efficient in phrasing.

  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 simple tool with one parameter and no output schema, the description is reasonably complete. It explains what the tool fetches, what specific checks it performs (named bots, wildcard block, llms.txt existence), and the nuance of SPA catch-all. It doesn't explain the return format, but given the lack of an output schema, a 4 is appropriate.

  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?

  The schema covers the single parameter (url) 100%, and the description adds meaning by explaining the parameter is a site URL or bare domain (e.g., example.com). The description also provides typical usage context (robots.txt fetch and llms.txt check), which goes beyond the schema's basic 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 tool checks a site's AI-crawler visibility by fetching robots.txt and looking for Disallow rules for named AI bots and a wildcard block, and verifies llms.txt existence. It uses a specific verb (Check) and resource (site's AI-crawler visibility), distinguishing it from siblings like cloudflare_ai_bot_audit or generate_llms_txt.

  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 on what the tool does (checking robots.txt and llms.txt). It doesn't explicitly state when NOT to use it or mention alternatives, but the sibling tools (cloudflare_ai_bot_audit and generate_llms_txt) imply different use cases. The description is sufficient for an agent to decide when to invoke this tool.

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

• generate_llms_txtA
  4.2/5.0
  Behavior3/5

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

  Since no annotations are provided, the description carries the burden of behavioral transparency. It clearly states that the tool is pure text generation (no file writing, no git interaction), which is helpful. However, it doesn't disclose potential limits, response format, or whether generation is deterministic or uses external services.

  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 wasted words. It front-loads the main purpose, specifies the output components, and clarifies constraints in a concise manner.

  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?

  Given the tool has 4 parameters with 100% schema coverage, no output schema, and no annotations, the description provides a clear functional overview. However, it could be more complete by mentioning that the output includes the generated text (since no output schema exists) and whether the FAQ block is a fixed format or customizable.

  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 description coverage is 100%, so the baseline is 3. The description adds value by explaining that the 'phrase' parameter is optional and that omitting it triggers only llms.txt generation (no content pack), which is not stated in the schema. This clarifies behavior 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 generates an llms.txt line plus a content pack (ownable phrase, llms.txt sentence, meta description, FAQ block) for a product, distinguishing it from siblings like check_visibility and cloudflare_ai_bot_audit by focusing on text generation for SEO/content, not visibility checks or bot audits.

  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 specifies when to use the tool (to generate content for a landing page or file drop) and what it does not do (does not write files or touch git), providing clear context. However, it doesn't explicitly exclude alternatives or mention when not to use this tool versus other content generation tools.

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