Server Quality Checklist

Tool Scores

• dental_cost_by_cityA
  4/5.0
  Behavior4/5

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

  No annotations are provided, so the description must disclose behavior. It explains that city data is a single observed average per procedure (no min/max), includes state low/high range for context, and notes the data is market research not advice. This adds useful limitations beyond 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is only 3 sentences, front-loaded with the purpose, and includes an example, data limitation note, and disclaimer. Every sentence earns its place with no waste.

  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 output schema, the description adequately explains what is returned (average prices, state range, clinic counts) and the data limitation. It could be more explicit about the output structure, but the example and context are sufficient for a simple tool.

  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% for all 3 parameters. The description adds marginal value with an example and mention of state disambiguation, but the schema already describes parameters well. Baseline 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 the verb 'Get' and resource 'average dental costs and clinic counts for a specific US city', specifying procedures (implants, veneers, braces). It distinguishes from siblings like dental_cost_by_state and dental_national_average by noting it returns city data plus parent state range.

  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 an example and mentions using the 'state' parameter to disambiguate, but does not explicitly state when to use this tool versus alternatives (e.g., state-level or national tools). Usage context is implied but lacks direct guidance on exclusions.

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

• dental_national_averageA
  4.3/5.0
  Behavior4/5

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

  No annotations are provided, so the description must fully convey behavior. It states the output includes low/avg/high cash prices and cheapest/prisest state, plus the disclaimer that it's market research data, not advice. This adequately discloses the read-only, non-destructive nature and the data source. No hidden side effects are mentioned, but none are expected for a read operation.

  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 extremely concise: two sentences plus an example. It starts with the core action ('Get the US national average...') and front-loads the most important information. Every sentence adds value, and there is no redundancy or filler.

  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 the tool's simplicity and the absence of an output schema, the description sufficiently explains what the tool returns: low/avg/high cash prices and cheapest/priciest state. It also provides a disclaimer about the nature of the data. No critical details appear missing for an agent to correctly invoke and interpret the tool.

  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 baseline is 3. The description does not add significant parameter-level detail beyond the schema; it only gives an example ('procedure="veneer"'). The schema already has comprehensive enum descriptions for procedure and lang. Thus, the description adds minimal value to parameter understanding.

  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 explicitly states it retrieves the US national average cost for a dental procedure, including low/avg/high prices and cheapest/priciest states. The verb 'Get' and resource 'national average dental cost' are clear, and the example 'procedure="veneer"' reinforces the purpose. It distinguishes well from sibling tools that focus on city or state averages.

  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?

  While no explicit 'use this when' or direct comparison to siblings, the description clearly defines the scope as 'US national average' and 'mean across all 51 states + DC'. The sibling names (dental_cost_by_city, dental_cost_by_state, out_of_pocket_estimate) themselves indicate alternative scopes, so an agent can infer that this tool is for nationwide averages. The disclaimer about market research data provides a usage note.

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

• out_of_pocket_estimateA
  4.3/5.0
  Behavior4/5

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

  With no annotations, the description fully discloses the tool's behavior: it explains each payment mode's coverage (e.g., insurance caps, exclusions) and notes that data is market research, not advice. This adds significant behavioral context beyond 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.

  Conciseness5/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  Extremely concise: first sentence states purpose, then defines modes with key details, followed by an illustrative example and a disclaimer. No wasted words.

  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 the tool's complexity (4 enum parameters, no output schema), the description covers all necessary aspects: what it does, how modes work, what procedures are, and limitations. It leaves no critical gaps for agent understanding.

  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?

  Although the schema covers 100% of parameters, the description enriches them by explaining payment modes in detail, providing an example, and clarifying procedure IDs implicitly, adding value beyond the enum lists.

  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?

  Clearly states the tool estimates out-of-pocket costs for a dental procedure under a specific payment mode, distinguishing it from sibling tools that likely provide average costs without payment mode consideration.

  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?

  Implied usage from the description is clear (when you need an out-of-pocket estimate with a payment mode), but there is no explicit guidance on when to use alternative siblings or when not to use this tool.

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

• dental_cost_by_stateA
  4.4/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries full burden. It discloses that the tool returns market research pricing data, not medical/financial advice, and hints at the comparison metric. It does not mention data freshness or error handling, but the enums in schema prevent invalid inputs. Overall, it is fairly transparent about 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, front-loaded with the core purpose, followed by an example and a disclaimer. Every sentence adds value, and there is no extraneous information. It is concise and well-structured.

  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 3 parameters (all described in schema with enums), no output schema, and no annotations, the description is complete enough. It covers what the tool returns (price range, national comparison, cost index) and includes a disclaimer. Some minor details (like pagination or exact format) are missing, but it adequately informs an agent.

  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 meaning beyond the schema by illustrating how parameters work in context (e.g., 'procedure="implant", state="CA" returns...'). It reinforces that state is a two-letter code and procedure uses specific IDs. This extra context justifies a 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 the verb 'get' and the resource 'dental cost by state', specifies it returns low/average/high cash price compared to national average, and includes an example. It effectively distinguishes from sibling tools like dental_cost_by_city (city scope) and dental_national_average (national scope).

  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 an explicit example (implant in CA) and explains the output. While it doesn't explicitly state when to use vs. alternatives, the sibling context (e.g., by_city for city-level, national_average for national only) implies appropriate use cases. No exclusions are given, but the guidance is clear.

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