Server Quality Checklist

Tool Scores

• share_of_voiceB
  3.2/5.0
  Behavior2/5

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

  Annotations include readOnlyHint=true and openWorldHint=true, but the description adds minimal behavioral context beyond the purpose. It does not disclose output format, accuracy limitations, or data scope (e.g., how 'share of voice' is computed), which would help the agent anticipate results.

  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, front-loaded sentence with no superfluous words. It efficiently communicates the core purpose without redundancy.

  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?

  Despite low complexity (2 parameters, no output schema), the description lacks essential context. It does not explain what 'share of voice' means, how it is calculated, or what the output structure is, leaving important gaps for agent understanding.

  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, with clear parameter descriptions (e.g., example for 'keyword', default/enum for 'marketplace'). The tool description does not add additional meaning beyond what the schema provides, meeting the baseline without enhancement.

  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's purpose: 'Analyze brand share of voice for a given Amazon search keyword.' It uses a specific verb ('Analyze') and distinct resource ('brand share of voice'), differentiating it from sibling tools like 'keyword_search_volume' and 'sales_estimates'.

  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 does not suggest when to avoid using it or mention any prerequisites, leaving the agent to infer usage from the purpose alone.

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

• keywords_by_asinA
  3.5/5.0
  Behavior3/5

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

  Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is clear. The description adds that keywords 'drive traffic' which is behavioral context, but does not explain other traits like pagination, rate limits, or response format. Bar is lowered by annotations, so a 3 is appropriate.

  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?

  A single, front-loaded sentence that is concise and immediately conveys the tool's purpose. Every word earns its place, but it could be slightly more informative without being verbose.

  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 absence of an output schema, the description should explain what the tool returns (e.g., list of keywords with metrics, format, array objects). It only says 'discover which keywords drive traffic' without specifying the output structure, leaving the agent with incomplete context about the response.

  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 coverage is 100%, so the schema already documents all three parameters with descriptions for asin, page_size, and marketplace. The description adds no additional meaning beyond the schema, meeting the baseline for high coverage.

  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 discovers keywords that drive traffic to a specific Amazon listing via ASIN. It uses a specific verb ('discover') and resource ('keywords') and implies non-overlap with siblings like 'keyword_search_volume' which focuses on volume rather than traffic drivers.

  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 use for analyzing which keywords bring traffic to an ASIN but provides no explicit guidance on when to use versus alternatives like 'product_database_query' or 'sales_estimates'. The context signal of sibling tools is present but the description itself lacks differentiation.

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

• product_database_queryA
  3.6/5.0
  Behavior3/5

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

  Annotations already include readOnlyHint=true and openWorldHint=true. The description adds no behavioral context beyond confirming a read operation, but it does not contradict annotations.

  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?

  A single sentence front-loads the core purpose with zero wasted words.

  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?

  With 8 optional parameters and no output schema, the description fails to explain the return format, result structure, or how 'product opportunities' are defined, leaving key usage information missing.

  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?

  All 8 parameters have descriptions in the input schema (100% coverage), so the tool description does not need to add parameter details. It adds no additional meaning beyond the schema, earning a baseline 3.

  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 verb 'Search' and the specific resource 'Jungle Scout product database' for finding 'Amazon product opportunities', which effectively distinguishes it from sibling tools focused on keywords or sales estimates.

  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 for product opportunity discovery but provides no explicit guidance on when to use or avoid this tool compared to siblings like keyword_search_volume or sales_estimates.

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

• sales_estimatesA
  3.8/5.0
  Behavior3/5

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

  Annotations declare readOnlyHint true and openWorldHint true, which are consistent. The description adds minimal behavioral context beyond the purpose, but does not contradict annotations.

  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?

  Single sentence of 13 words that is front-loaded with the action and object. No wasted words.

  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?

  With no output schema, the description adequately states what is returned (estimated monthly sales units and revenue). Parameters are well-described in the schema, so overall the tool is sufficiently documented for its 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?

  Schema description coverage is 100%, so the description adds little value over the schema. It mentions 'a specific ASIN' which is already in the schema, but does not further clarify parameter behavior.

  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 specifies the exact verb 'Get' and the resource 'Jungle Scout estimated monthly sales units and revenue for a specific ASIN', clearly distinguishing it from sibling tools like keyword_search_volume or product_database_query.

  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 use when sales estimates for an ASIN are needed, but provides no explicit when-to-use or when-not-to-use guidance, nor any mention of alternatives.

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

• keyword_search_volumeA
  4.1/5.0
  Behavior4/5

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

  Annotations already declare readOnlyHint=true and openWorldHint=true, indicating a safe read operation. The description adds value by specifying exact-match and broad-match volume, and the schema description notes that up to 10 keywords per call are processed. No contradictions.

  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 is both concise and front-loaded with the purpose. Every word contributes meaning with no redundancy. It is appropriately sized for the tool's simplicity.

  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 lookup tool with complete annotations and schema coverage, the description adequately covers what the tool does, what it returns (exact and broad volume), and the input constraints (keywords, marketplace). No output schema is needed as the return values are implied.

  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 burden on the description is low. The description only says 'one or more Amazon keywords,' while the schema already explains each parameter in detail (e.g., keyword array with examples, marketplace enum). The description adds minimal extra 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's purpose: looking up exact-match and broad-match search volume for Amazon keywords. The verb 'look up' and the resource 'search volume' are specific, and the tool is distinct from siblings like keywords_by_asin and sales_estimates.

  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 provides no explicit guidance on when to use this tool versus alternatives. Siblings are listed but not compared. The description mentions match types but does not address when not to use or prerequisites. Basic context is implied but lacks exclusionary criteria.

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