Server Quality Checklist

Tool Scores

• maps_searchB
  3.2/5.0
  Behavior2/5

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

  With no annotations, the description should disclose behavioral traits, but it only mentions output features (Lead Quality Score, outreach hints) and not side effects, rate limits, or authentication requirements beyond what is in the schema.

  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, direct sentence with no fluff. However, it could be slightly more structured by separating the action from the output description.

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

  Completeness3/5

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

  The description covers the basic purpose and output, but lacks details on pagination, errors, or the full structure of returned data. Given no output schema, more context on the response format would be helpful.

  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 parameters are documented. The description adds value by explaining the output, which aids understanding of why parameters matter, but does not add new parameter-level 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 searches Google Maps businesses by type and location and returns a Lead Quality Score and outreach hints, making the purpose very specific and distinguishable from siblings like maps_leads.

  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 alternatives (e.g., maps_leads) is provided. The description lacks any context about appropriate use cases or when not to use it.

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

• shopify_analyzeB
  3.2/5.0
  Behavior2/5

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

  No annotations provided; description only implies analysis without stating read-only nature, data freshness, rate limits, or side effects. The term 'analyze' suggests non-destructive but is not explicit.

  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 with clear enumeration of outputs. No unnecessary words; front-loaded with action and scope.

  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?

  Lists key outputs (products, pricing, etc.) compensating for lack of output schema. However, missing behavioral details (e.g., read-only, prerequisites) given no annotations.

  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?

  Parameter 'url' has adequate schema description with example. Schema coverage is 100%, so description adds no extra meaning beyond schema. Baseline 3 applies.

  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?

  Description clearly states the tool analyzes a Shopify store with specific outputs (products, pricing, vendors, apps, theme, collections). However, it does not distinguish from sibling tool 'shopify_products' which may have overlapping purpose.

  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 alternatives like 'shopify_products'. The description only says 'Analyze any Shopify store', lacking usage context.

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

• shopify_productsB
  3.2/5.0
  Behavior2/5

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

  With no annotations, the description must provide behavioral details. It only mentions pagination and the 250-product limit, but omits traits like rate limits, whether the tool is read-only, or error handling.

  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, no filler. First sentence states purpose, second adds a key constraint. Every word earns its place.

  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 simple parameters, description lacks details on return format, error conditions, authentication needs, or sorting/filtering. Fails to fully exploit the no-annotation 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?

  Input schema already describes all 3 parameters (100% coverage). The description adds minimal value: 'any Shopify store' for url and 'up to 250' for limit, which overlaps with schema's 'max 250'. 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 'Fetch a paginated product catalog from any Shopify store', indicating a specific verb and resource. It distinguishes from siblings like amazon_product or maps_search which target different platforms.

  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 alternatives like shopify_analyze. Doesn't mention prerequisites or exclusions. The 'any Shopify store' hint is broad but lacks explicit when-to-use context.

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

• maps_leadsB
  3.4/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It does not disclose whether the operation is read-only, any authentication requirements beyond the API key, or behavior when no leads are found. The description is minimal on behavioral 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, no filler, front-loaded purpose. Every word adds value.

  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?

  No output schema and no annotations. The description does not explain the concept of Lead Quality Score, output format, or what happens if no leads match. For a tool with 4 parameters and no structured metadata, more context is needed.

  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?

  Input schema has 100% coverage, so baseline is 3. The description mentions 'Lead Quality Score' but does not add details beyond schema (e.g., what min_score represents or how it's calculated). No additional parameter meaning given.

  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?

  Description clearly states the tool finds qualified sales leads on Google Maps filtered by Lead Quality Score, distinguishing it from the sibling 'maps_search' which is likely a general search. The purpose is specific and actionable.

  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?

  Says 'Best for building targeted outreach lists,' which implies a use case but does not explicitly state when to use or avoid this tool, nor compare to sibling tools like 'maps_search'.

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

• amazon_searchA
  3.7/5.0
  Behavior3/5

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

  No annotations are provided, so the description must cover behavioral traits. It discloses the return of an Opportunity Score with factors, but omits details like read-only nature, pagination, rate limits, or authentication needs.

  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, front-loaded with the core function, and includes a key output feature in the second sentence. Every word earns its place.

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

  Completeness3/5

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

  For a simple search tool with 2 params and no output schema, the description adequately states purpose and return score, but lacks details about full return structure (e.g., other product fields). Without output schema, more completeness would be beneficial.

  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%, with both parameters having clear descriptions in the schema (keyword and marketplace with enum). The tool description adds no additional semantic value 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 tool searches Amazon products by keyword and returns an Opportunity Score. It distinguishes from siblings like amazon_product (for product details) and Shopif/ maps tools.

  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 searching Amazon products but provides no explicit guidance on when to use this tool versus siblings. No 'when not to use' or alternative recommendations.

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

• amazon_productA
  4/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries full burden for behavioral traits. It discloses the output contents (FBA fee, profit margin, opportunity tier) but does not mention any side effects, rate limits, data freshness, or external calls. Additional context would improve 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?

  A single sentence that front-loads the core purpose and lists key outputs. No wasted words, highly efficient.

  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 there is no output schema, the description gives a good sense of what the tool returns (FBA fee, profit margin, opportunity tier). It covers the single-product analysis scope adequately. Could mention that the output is a detailed report, but overall complete enough.

  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 baseline is 3. The description does not add significant meaning beyond the schema; it mentions 'by ASIN' which matches the asin parameter, but does not elaborate on the marketplace parameter or provide formatting hints.

  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 it performs 'deep analysis of a single Amazon product by ASIN' and lists specific outputs (FBA fee estimate, profit margin, opportunity tier). This distinguishes it from siblings like amazon_search, which is for searching products.

  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 implies the tool is for analyzing a single product in depth, but does not explicitly state when to use it versus alternatives (e.g., amazon_search for broader queries). It provides context for use but lacks explicit guidance.

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