Server Quality Checklist

Tool Scores

• fetch_urlA
  4/5.0
  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 behavioral disclosure. It adds non-obvious information about rotating across multiple extraction providers and failover behavior, which helps an agent anticipate reliability and latency characteristics. It does not mention error handling or rate limits, but those are less critical for a simple fetch operation.

  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 a single sentence that states the primary purpose first and then adds the key behavioral detail about provider rotation and failover. There is no filler or redundant repetition of the tool name.

  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 tool with one required parameter and no nested structures, the description is largely complete: it explains the input (URL), the output (markdown content), and the notable internal behavior (provider failover). It could mention what happens on fetch failures, but this is a minor gap given the tool's simplicity.

  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 fully documents the only parameter, 'url', with a description ('URL to fetch'). The tool description adds no additional parameter-level meaning, so the baseline score of 3 applies.

  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 ('Fetch a web page') and a resource (a URL), and clarifies the return format ('content as markdown'). This clearly separates it from sibling tools like web_search, which searches rather than fetches a specific page.

  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 when to use the tool: when you have a specific URL and want its content as markdown. However, it does not explicitly state when not to use it or mention alternatives such as web_search for discovery or engine_status for checking provider health.

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

• engine_statusA
  4.5/5.0
  Behavior4/5

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

  Annotations already declare this as read-only and non-destructive. The description adds meaningful behavioral caveats: historical errors do not prove current failure, and disabled engines do not necessarily mean missing credentials. This helps an agent interpret results correctly.

  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 primary purpose is front-loaded, followed by two high-value caveats that prevent misinterpretation. Every sentence earns its place.

  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 zero-parameter read-only tool with no siblings in the same domain, the description fully covers what the tool accesses and how to interpret the data. No output schema exists, but the description gives enough behavioral context for correct use.

  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 tool has zero parameters, so there is nothing for the description to explain. The baseline for zero-parameter tools is 4, and the description does not introduce any conflicting or confusing parameter-related claims.

  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 uses a specific verb ('Read') and names the exact resources: engine configuration, authentication requirements, usage and quota sources. It also clearly distinguishes this from a health check, which sets it apart from any sibling that might be mistaken for it.

  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 gives clear context about what the tool is for and explicitly warns that it is not a live health check. It does not name alternative tools, but the siblings are unrelated enough that the guidance is still useful and sufficient.

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

• open_dashboardA
  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 behavioral burden. It discloses the main side effect—opening a web browser—and clarifies what the dashboard contains. It does not mention prerequisites like whether a local server must already be running, but for a benign, no-parameter action this is acceptable.

  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 no filler: the first states the action and resource, the second states when to use it. The most important information is front-loaded, and every sentence earns its place.

  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 simple no-parameter tool with no output schema, the description is complete. It explains what the tool does, what the dashboard contains, and when to invoke it. Nothing essential is missing for an agent to select and call it correctly.

  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 tool has zero parameters, and the schema coverage is 100%, so there are no parameter semantics to explain. The baseline for zero-parameter tools is 4, and the description adds useful context about what the dashboard shows.

  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 a specific verb and resource: 'Open the local dashboard ... in a web browser.' It also enumerates the dashboard contents, making the tool's function unambiguous. This distinguishes it from sibling tools like engine_status, which is about status rather than opening a UI.

  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 gives an explicit use condition: 'Use when the user wants to configure engines or check quota.' It does not discuss when not to use it or name alternative tools, but the intended context is clear and sufficient for this no-parameter action.

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

• web_searchA
  4.6/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full transparency burden. It discloses significant behavioral traits: automatic round-robin across providers, transparent failover, and the guarantee that time filters are never silently dropped. It also specifies the result shape, which is especially valuable because no output schema exists.

  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 compact and front-loaded, using only two sentences. It conveys core behavior, provider list, failover semantics, returned fields, and the time-filter guarantee without filler or repetition.

  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 six parameters and no output schema, the description covers the essential result format and important behavioral constraints. It does not discuss error handling beyond failover, rate limits, or provider-specific edge cases, so it is thorough but not exhaustive.

  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 input schema already describes all six parameters with 100% coverage, so the baseline is 3. The description adds extra semantic value by explaining that time filters restrict rotation and failover to compatible providers, a nuance not present in the schema. This justifies a score above baseline.

  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 a specific action and resource: web search performed through multiple named APIs. It clearly differentiates this tool from siblings like fetch_url and engine_status by emphasizing search results, round-robin rotation, and failover.

  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 for when the tool is appropriate: general web searching with automatic provider rotation and date filtering. It does not explicitly state when to prefer fetch_url or engine_status, so it falls short of a perfect 5, but the use case is evident.

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