Server Quality Checklist

Tool Scores

• get_mega_menuA
  3.7/5.0
  Behavior3/5

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

  With no annotations, the description carries full burden. It notes the tool is read-only (GET) and returns data as-is, but omits details about potential errors, rate limits, or data volume. The behavioral coverage is adequate but not thorough.

  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. The first sentence immediately states the action and endpoint. Every word adds value, and the structure is front-loaded.

  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 provides the essential operation and return shape, but lacks guidance on when to prefer this over sibling tools like list_menu_items. Without an output schema, it could better describe the nesting structure or use cases.

  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 0 parameters with 100% coverage. The description does not need to add parameter information but also does not explicitly confirm the absence of parameters. Baseline 3 applies due to high schema 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 verb 'Fetches' and the resource 'mega menu payload' from a specific API endpoint. It also specifies the result is 'the full nested collections tree as-is', distinguishing it from sibling tools like list_menu_items which likely return filtered data.

  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 when the raw, unfiltered mega menu payload is needed, but does not explicitly contrast with siblings (call_ecommerce_api, list_menu_items) or provide when-not-to-use guidance. No alternatives or exclusions are stated.

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

• list_menu_itemsA
  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 must carry the full behavioral burden. It uses 'Fetches' indicating a read operation, but does not explicitly state it is non-destructive, nor does it mention authentication needs, rate limits, or potential side effects. The description adds some value by describing the output format but lacks comprehensive behavioral disclosure.

  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 concise with two sentences, front-loaded with the main purpose. Every sentence adds value without repetition or unnecessary detail.

  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 no parameters and no output schema, the description explains the output structure sufficiently (flattened, human-readable, fields). However, it does not mention whether the list is complete or limited, or if there is any ordering. Overall, it is adequate for a simple list retrieval tool.

  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 has no parameters, so schema description coverage is 100%. The description adds meaning by explaining what the returned list contains (hierarchy path, link, login requirement, sub-items), which is helpful for understanding the tool's output. With zero parameters, a baseline of 4 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 the tool fetches the mega menu and returns a flattened list with hierarchy path, link, login requirement, and sub-items. It distinguishes itself from the raw tree by stating it's easier to scan, implying a sibling tool get_mega_menu for raw tree.

  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 when to use this tool (when a human-readable flattened list is needed) versus the raw tree (get_mega_menu) by saying 'Easier to scan than the raw tree.' This provides clear context, though it doesn't explicitly mention the sibling tool name 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.

• call_ecommerce_apiA
  4.3/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the full burden. It discloses that the tool acts as a generic HTTP passthrough and lists the parameters that control behavior. However, it does not mention error handling, rate limits, authentication requirements (though headers allow auth token), or the response format. This is adequate but lacks full transparency on potential risks or failure modes.

  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, each adding essential information without redundancy. The first sentence states the purpose, the second gives usage instructions. Every word earns its place, and the most important information is front-loaded.

  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?

  Given no output schema, the description does not explain what the response will contain (e.g., JSON). It also lacks information on authentication or error handling. However, since it is a generic passthrough, the response format is inherently variable. The description is adequate but could be more complete by noting that responses are JSON and that errors may be returned.

  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 description coverage is 100%, so the baseline is 3. The description adds value by contextualizing parameters: it gives the base URL, shows a relative path example, and explains that query/body/headers are optional. This goes beyond the individual schema descriptions by tying them together into a usage 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 it is a generic passthrough tool for calling endpoints under a specific base URL, intended for endpoints not covered by dedicated tools. It specifies the verb 'call' and resource 'any Tekweld ecommerce API endpoint', distinguishing it from siblings like get_mega_menu and list_menu_items which cover specific endpoints.

  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?

  The description explicitly says 'Use this to reach endpoints not covered by a dedicated tool', providing clear when-to-use guidance and implicit when-not-to-use (when a dedicated tool exists). It also explains what to provide (path, method, query, body, headers), giving comprehensive usage instructions.

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