Server Quality Checklist

Tool Scores

• ubersuggest_domain_overviewC
  2.9/5.0
  Behavior2/5

  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 mentions 'comprehensive domain analysis' but doesn't specify what that entails (e.g., data freshness, rate limits, authentication needs, or whether it's a read-only operation). This leaves critical behavioral traits undefined for the agent.

  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, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence ('Get comprehensive domain analysis including traffic and ranking data') contributes directly to understanding the tool's function, making it highly concise and well-structured.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the lack of annotations and output schema, the description is incomplete for a tool that performs 'comprehensive domain analysis'. It doesn't explain what 'comprehensive' means, what specific metrics are returned, or how the analysis is structured, leaving significant gaps for the agent to operate effectively.

  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%, with clear descriptions for both parameters ('domain' and 'country'). The description adds no additional parameter semantics beyond what's in the schema, such as format examples or constraints. Since the schema does the heavy lifting, 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.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with a specific verb ('Get') and resource ('comprehensive domain analysis including traffic and ranking data'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'ubersuggest_traffic_estimation' or 'ubersuggest_site_audit', which likely provide overlapping or related analyses.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus the sibling tools. There's no mention of alternatives, prerequisites, or specific contexts where this tool is preferred over 'ubersuggest_keyword_research' or 'ubersuggest_site_audit', leaving the agent to infer usage from tool names alone.

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

• ubersuggest_keyword_researchC
  2.9/5.0
  Behavior2/5

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

  With no annotations, the description carries full burden but only states what data is returned, not behavioral traits. It doesn't disclose whether this is a read-only operation, requires authentication, has rate limits, or how results are structured (e.g., pagination). For a tool with no annotations, this is a significant gap in transparency.

  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, efficient sentence with zero waste—it directly states the tool's function and output data. It's appropriately sized and front-loaded, making it easy for an agent to parse quickly.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  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 is incomplete. It doesn't explain return values, error conditions, or behavioral context, leaving gaps for a tool that likely involves external API calls. For a keyword research tool with three parameters, more context is needed to guide effective use.

  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 all three parameters (keyword, language, location) with clear descriptions. The description adds no additional meaning beyond implying these parameters might be used for research, which is redundant. Baseline 3 is appropriate as the schema does the heavy lifting.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the verb 'research' and the resource 'keywords', specifying the data returned (volume, difficulty, competition). It distinguishes from siblings like domain_overview or site_audit by focusing on keyword-level analysis. However, it doesn't explicitly contrast with traffic_estimation, which might also involve keywords.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  No guidance on when to use this tool versus the three sibling tools is provided. The description implies usage for keyword-level metrics, but there's no explicit mention of alternatives, prerequisites, or exclusions. This leaves the agent to infer context from tool names alone.

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

• ubersuggest_site_auditC
  2.9/5.0
  Behavior2/5

  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 mentions 'comprehensive site audit' but lacks details on what that entails (e.g., crawl behavior, time to complete, rate limits, authentication needs, or output format). For a tool that likely performs resource-intensive crawling, this is a significant gap in transparency.

  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, efficient sentence that front-loads the core action ('perform comprehensive site audit') and specifies the domain ('for technical SEO issues'). There is no wasted verbiage, making it highly concise and well-structured.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the complexity of a site audit tool with no annotations and no output schema, the description is insufficient. It doesn't cover behavioral aspects like crawl scope, performance implications, or result format, leaving the agent with incomplete context for proper tool invocation and result interpretation.

  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 both parameters ('url' and 'pages_limit') adequately. The description doesn't add any meaning beyond what the schema provides, such as explaining how 'pages_limit' affects audit depth or what constitutes a valid 'url'. Baseline 3 is appropriate when the schema does the heavy lifting.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with a specific verb ('perform') and resource ('site audit'), and specifies the domain ('technical SEO issues'). However, it doesn't explicitly differentiate from sibling tools like 'domain_overview' or 'keyword_research' which might also involve site analysis, leaving some ambiguity about when to choose this specific audit tool.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'ubersuggest_domain_overview' or 'ubersuggest_keyword_research', nor does it specify prerequisites, exclusions, or ideal scenarios for a site audit versus other SEO analyses.

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

• ubersuggest_traffic_estimationC
  2.9/5.0
  Behavior2/5

  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 but offers minimal information. It states the tool estimates traffic potential but doesn't cover aspects like data sources, accuracy, rate limits, authentication needs, or what the output might look like. This is a significant gap for a tool with no structured behavioral hints.

  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, efficient sentence that front-loads the core purpose without any wasted words. It's appropriately sized for a tool with two parameters and no complex behavioral nuances to explain.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the lack of annotations and output schema, the description is incomplete. It doesn't explain what the estimation returns, how it's calculated, or any prerequisites, making it inadequate for an agent to fully understand the tool's behavior and output in context.

  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 both parameters ('domain' and 'period') adequately. The description adds no additional meaning beyond what the schema provides, such as examples or constraints, but doesn't need to compensate for low coverage. This meets the baseline for high schema coverage.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose with a specific verb ('Estimate') and resource ('organic traffic potential for a domain'), making it immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'ubersuggest_domain_overview' or 'ubersuggest_keyword_research', which might also involve traffic analysis, preventing a perfect score.

  Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

  Usage Guidelines2/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools or contexts where this estimation is preferred over other analyses, leaving the agent to infer usage based on tool names alone.

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