Server Quality Checklist

Tool Scores

• check_availabilityA
  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. It states a read operation (lookup) and limits to 20 items, but does not disclose error handling, response format, or authentication requirements. This is adequate for a simple lookup but lacks depth.

  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 with no extraneous words. It efficiently conveys the function and usage guidance, earning its place without redundancy.

  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?

  No output schema exists, so the description omits return value details. For a bulk lookup, mentioning what the response contains (e.g., mapping of identifiers to price/stock) would improve completeness. Still, the description is largely sufficient for simple usage.

  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%, and the parameter description is clear. The tool description adds no additional semantic information beyond what is already in the schema, so a 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 specifies a clear verb ('lookup') and resource ('price/stock for up to 20 products'), with explicit identifiers (id, SKU, or name). It distinguishes from siblings like search_products and get_product by focusing on bulk lookup of specific items.

  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 includes guidance 'Use when tracking specific items rather than browsing', providing clear context on when to use this tool. It indirectly contrasts with browsing tools, but does not explicitly mention alternatives or exclusions.

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

• get_productA
  4.2/5.0
  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. It describes the return fields but does not mention behavior on missing products, authorization, or side effects. For a read-only tool, this is adequate but could be improved.

  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 that is front-loaded with the main purpose, followed by a list of return fields. No unnecessary 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 lists the returned information (description, attributes, brand, stock, rating, image). It lacks mention of error handling or that only one identifier should be provided, but covers the essentials.

  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?

  Schema coverage is 100%, but the description adds value by explaining that id, slug, or SKU are alternative identifiers for the product, which is not explicit in 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 it provides full detail for a product by id, slug, or SKU, listing specific fields. It distinguishes from sibling tools like search_products which return lists.

  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?

  It specifies how to identify the product (by id, slug, or SKU), implying the agent should use exactly one. While it doesn't explicitly state when not to use this tool, the context of sibling tools makes it clear this is for single product detail.

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

• list_categoriesA
  4.2/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It discloses the number of categories (376), tree structure, and argument effects. Missing details like read-only nature, auth needs, or pagination, but covers core behavior adequately.

  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 concise sentences. First sentence sets scope (376-category tree), second explains argument usage. No redundancy, front-loaded with key info. Every word earns its place.

  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?

  No output schema exists, but description doesn't explain return format. However, for a category browser, the return is likely intuitive. Given the tool's simplicity and good annotations coverage (though absent), it is complete enough for typical 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?

  Schema coverage is 100%, so baseline is 3. The description adds value beyond schema by explaining parent 'descends' and search 'finds one anywhere', and mentions default limit of 40 (schema also says default 40). This context aids agent in understanding parameter purpose.

  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 browses a category tree and specifies behavior with no arguments (top-level) vs parent or search arguments. It distinguishes from sibling tools like search_products which target products, not categories.

  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 explains how to use the tool: no arguments for top-level, parent to descend, search to find. It implicitly covers when to use it (for categories) but lacks explicit exclusions or alternatives. However, sibling tools provide enough context.

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

• list_filter_valuesA
  4.2/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden. It discloses that the output includes 'product counts' when passing an attribute, which adds behavioral detail beyond a simple list. However, it doesn't mention rate limits, authentication requirements, or error behavior.

  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 long, front-loading the purpose and then detailing behavior. Every sentence earns its place with no fluff.

  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 3 optional parameters and no output schema, the description adequately explains both modes of operation and mentions product counts in the output. It doesn't cover pagination or sorting, but given the tool's discovery nature, it is reasonably complete.

  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?

  Schema coverage is 100%, with each parameter described. The description adds value by explaining the dual-mode behavior (no args vs. with attribute) and the inclusion of product counts, which is not evident from the schema alone. The enumeration of example attributes ('Caliber, Action, Barrel Length…') provides context.

  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 'Discover filterable attributes and their valid values', specifying both the verb (discover) and resource (filterable attributes/values). It distinguishes itself from sibling tools like search_products and get_product by focusing on the filtering infrastructure.

  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 usage context: 'Use this to ground a filter before searching'. It explains the behavior with no arguments (list all attributes) and with an attribute argument (list values with product counts). It doesn't explicitly state when not to use it, but the guidance is sufficient.

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

• search_productsA
  4.9/5.0
  Behavior5/5

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

  With no annotations, the description discloses key behaviors: spelling expansion for caliber and brand, compact record return, stock percentage, and hidden test products. This provides full transparency beyond what the schema offers.

  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?

  Four sentences, no wasted words, front-loaded purpose, logical flow from main function to details to a practical note about stock. Ideal conciseness.

  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?

  Given 13 parameters, no output schema, and nested objects, the description covers scope, filtering capability, special behaviors, stock context, and directs to sibling tools for more detail. Everything an agent needs to know is present.

  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?

  Schema coverage is 100%, but description adds value by explaining that caliber and brand accept everyday spellings and are expanded to matching catalog terms, which is not in the schema. Baseline 3, extra context raises to 4.

  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 searches the Rangeview Sports catalog (~5,600 products), combines free-text with multiple filters, and distinguishes from siblings by mentioning get_product for full detail and list_categories for browsing categories.

  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?

  Explicitly tells when to use this tool vs alternatives: 'Returns compact records; call get_product for full detail' and suggests using in_stock_only for buyable items due to low stock percentage.

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