Server Quality Checklist

Tool Scores

• time_series_analysisC
  2.7/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden. It does not disclose whether the tool is read-only, what data freshness assumptions exist, or if side effects occur. The output format is not mentioned, leaving the agent uncertain about what to expect.

  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 sentence, which is efficient and front-loaded with the core purpose. However, it is too concise at the expense of necessary detail, bordering on under-specification.

  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 no output schema and 6 parameters, the description fails to explain return values, default behaviors (e.g., start_date not required), or what happens if dates are omitted. The tool lacks sufficient context for an agent to invoke it correctly without additional knowledge.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is only 33%, and the description adds no additional meaning beyond the schema's parameter names. For example, 'metric' and 'geography' lack elaboration, and the description does not clarify valid metric values or date range implications.

  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?

  The description states 'Analyze trends over time for specific health metrics,' which clearly indicates the tool's purpose of time series analysis on health metrics. However, it lacks specificity about the type of analysis (e.g., modeling, forecasting) and does not differentiate from sibling tools like compare_states or filter_data.

  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 usage guidelines are provided. The description does not specify when to use this tool versus alternatives like compare_states or search_health_data. There is no guidance on prerequisites, data context, or limitations.

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

• compare_statesC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description must carry the full burden. It only states that it compares metrics, implying a read operation, but does not disclose what the output looks like, any limitations, or side effects. For a tool with required parameters and no output schema, this is insufficient.

  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 concise sentence with no unnecessary words. It effectively communicates the core purpose without redundancy. It could be slightly expanded to include usage guidance without losing conciseness, but given its current length, it 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?

  Given the tool has 4 parameters (3 required), no output schema, and no annotations, the 6-word description is too minimal. It does not explain what the comparison output is, any constraints beyond schema, or how results are structured. The description leaves significant gaps for an agent trying to invoke the tool correctly.

  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 for its 4 parameters. The description adds no additional meaning beyond the schema; it simply echoes the tool's purpose. According to the rubric, with coverage >80%, baseline is 3, and the description does not improve it.

  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?

  The description 'Compare health metrics across multiple states' clearly states the verb (compare) and resource (health metrics across states). While it distinguishes from siblings like filter_data and time_series_analysis, it does not explicitly differentiate from search_health_data which could also compare across states. Still, the purpose is well communicated.

  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 siblings like filter_data, get_available_datasets, search_health_data, or time_series_analysis. There is no mention of prerequisites or context that would help an agent choose this tool over others.

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

• get_available_datasetsB
  3/5.0
  Behavior2/5

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

  With no annotations, the description carries full burden. It mentions 'comprehensive information' but does not specify what that includes (e.g., dataset names, descriptions, metadata). The include_sample parameter hints at sample data but behavior is not fully disclosed (e.g., data volume, pagination, response format).

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness3/5

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

  The description is a single short sentence, which is functional but could be more informative. It is not excessively verbose but lacks some useful context. It is adequately concise but not exemplary.

  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 simplicity (1 optional param, no output schema), the description is minimal. It does not explain what datasets are, what information is returned, or how it fits with sibling tools. More context about data discovery workflow would improve completeness.

  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 the boolean parameter already well-described. The description does not add significant extra meaning beyond the schema's 'Include sample data for each dataset'. The baseline is 3, and no additional value is provided.

  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 'Get comprehensive information about all available PopHIVE datasets', specifying the verb (Get), resource (available datasets), and scope (all). It distinguishes well from sibling tools like compare_states and filter_data, which are more specific operations.

  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 is provided on when to use this tool versus alternatives. It does not mention that this tool should be used first to discover available datasets before applying filters or analyses. The description lacks any usage context or exclusion conditions.

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

• search_health_dataB
  3.1/5.0
  Behavior2/5

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

  Without annotations, the description should disclose behavioral traits like output format, pagination, or data sources. It only says 'search' and does not explain what the result looks like or any constraints, leaving the agent blind to key behaviors.

  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 concise sentence that front-loads the main purpose. It could be slightly expanded without losing conciseness, but it is efficient and to the point.

  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 tool has no output schema and no annotations, the description is too minimal. It does not explain return format, result structure, or how to further refine searches, leaving significant gaps for a search 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 description does not need to add meaning for parameters. The description does not provide additional semantics beyond what is already in the schema's property descriptions.

  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 action ('Search across all datasets') and the target ('health conditions, metrics, or keywords'). It differentiates from siblings like 'compare_states' or 'time_series_analysis' by focusing on generic search across all datasets.

  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. Sibling tools are listed but there is no explicit differentiation or recommendation on which to choose for specific tasks.

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

• filter_dataB
  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 must cover behavioral traits. It states the tool filters data, but does not mention whether it is read-only, pagination, limits, or side effects. For a filter tool, read-only nature should be 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?

  The description is a single sentence, front-loaded with the main action, and contains no unnecessary words. It is concise and to the point.

  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 tool has 6 parameters (1 required) and no output schema or annotations, the description is minimal. It lacks details on return format, empty results, sorting, or limits. For a filter tool with many optional filters, more context would improve completeness.

  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 all parameters are documented there. The description adds a summary of criteria categories but no additional meaning beyond the schema. 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 action ('filter'), the resource ('PopHIVE datasets'), and examples of criteria ('state, date range, demographics'). It distinguishes from sibling tools like 'compare_states' or 'time_series_analysis' which have different purposes.

  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 when to use this tool (for filtering datasets), but does not explicitly compare to siblings like 'search_health_data' or 'get_available_datasets'. No when-not-to-use or alternative guidance is provided.

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