Server Quality Checklist

Tool Scores

• get_public_resultA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries full burden. It discloses the return content ('scores for privacy, security, accessibility, and performance plus a summary of key findings'), which is valuable behavioral information. However, it doesn't mention error conditions, rate limits, authentication requirements, or what happens with invalid UUIDs.

  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 efficient sentences with zero waste. The first sentence states the purpose and required parameter, the second describes the return value. Every word earns its place and the information is appropriately 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?

  For a single-parameter read operation with no output schema, the description provides good coverage of purpose, parameter context, and return content. It could be more complete by mentioning error cases or authentication requirements, but given the tool's simplicity and the absence of annotations/output schema, it's 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 schema description coverage is 100%, so the schema already documents the single 'uuid' parameter completely. The description adds marginal value by specifying this is for 'publicly shared scan results', but doesn't provide additional syntax, format, or validation details beyond what the schema provides.

  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 ('Fetch'), resource ('publicly shared Polaris Audit report'), and identifier mechanism ('by its UUID'). It distinguishes from sibling tools by specifying this is for 'publicly shared' reports only, unlike 'get_scan_result' which likely retrieves private scans.

  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 about when to use this tool ('Fetch a publicly shared Polaris Audit report by its UUID'), but doesn't explicitly state when NOT to use it or name alternatives. It implies this is for public reports only, which helps differentiate from 'get_scan_result', but doesn't provide explicit exclusion guidance.

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

• audit_urlA
  4.4/5.0
  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 behavioral disclosure. It effectively describes key traits: the tool initiates an asynchronous scan (implied by the token return), specifies typical completion time ('30–60 seconds'), and indicates it's a free service. However, it doesn't mention potential limitations like rate limits, authentication needs, or error conditions, leaving some gaps.

  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 front-loaded with the core purpose, followed by essential usage and timing details in two concise sentences. Every sentence earns its place by providing critical information without redundancy, making it highly efficient and well-structured.

  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's moderate complexity (asynchronous scan initiation), no annotations, and no output schema, the description does well by explaining the process, return value (scan token), and typical timing. However, it lacks details on error handling or scan limitations, which could be important for robust agent operation.

  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 has 100% description coverage, clearly documenting the single 'url' parameter. The description adds no additional parameter details beyond what the schema provides (e.g., no extra syntax rules or examples). According to the rules, with high schema coverage, the baseline is 3 even without param info in the 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 specific action ('Submit a website URL for a free Polaris Audit scan') and resource ('website URL'), distinguishing it from sibling tools like get_scan_result (which retrieves results) and get_public_result (likely for public reports). It avoids tautology by explaining the scan process rather than just restating the name.

  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 explicitly states when to use this tool ('to submit a URL for scanning') and provides a clear alternative ('use with get_scan_result to retrieve the completed report'), directly naming the sibling tool. This gives the agent precise guidance on workflow sequencing without ambiguity.

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

• get_scan_resultA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description carries full burden and does well: it discloses the polling behavior for incomplete scans (a key behavioral trait), implies it's a read operation (retrieves results), and mentions the dependency on audit_url. It doesn't cover error cases or rate limits, but provides essential context.

  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 with zero waste: the first states purpose and prerequisites, the second provides critical behavioral guidance (polling). It's front-loaded with the core function and appropriately sized for the tool's complexity.

  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 no annotations and no output schema, the description does well: it explains the tool's purpose, usage context, and polling behavior. It could mention what the results look like or error handling, but for a simple retrieval tool with good schema coverage, it's mostly 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?

  Schema description coverage is 100%, so the schema already documents the token parameter fully. The description adds no additional parameter semantics beyond what's in the schema (e.g., no format details or examples). Baseline 3 is appropriate when schema does the heavy lifting.

  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 ('Retrieve the results') and resource ('previously submitted scan'), and distinguishes from siblings by specifying it uses the token from audit_url (vs. get_public_result which likely doesn't require a token). It explicitly mentions the polling behavior for incomplete scans.

  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 provides explicit guidance on when to use ('using the scan token returned by audit_url') and when to retry ('If the scan is still running, poll again after a few seconds'). It implicitly contrasts with audit_url (which submits scans) and get_public_result (which likely retrieves public results without a token).

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