Server Quality Checklist

Tool Scores

• vunet_query_metricB
  3.1/5.0
  Behavior2/5

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

  No annotations provided, so description carries full burden. It mentions automatic tenant configuration but does not disclose other important behaviors like effect of conflicting time parameters, error handling, response format, or pagination. Extensive schema descriptions exist but behavioral traits beyond parameter definitions are missing.

  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?

  Single sentence is concise and front-loaded with key information. However, given the tool's complexity (12 parameters), the description could benefit from additional structure (e.g., separate paragraphs for key features) while remaining concise. No redundancy.

  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?

  For a tool with 12 parameters, no output schema, and no annotations, the description is too brief. It does not explain return values, time parameter combinations, error states, or the nature of the metric data returned. Schema covers parameters but not behavioral context needed for effective use.

  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 detailed descriptions for all 12 parameters. The description adds minimal value by summarizing 'flexible time ranges and filters' but does not explain parameter relationships, defaults, or usage patterns beyond what schema provides. 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?

  Description clearly states it queries a Vunet data model/metric, using verb 'Query' and specifying the resource. It distinguishes from siblings (vunet_fetch_datamodels, vunet_get_status, vunet_list_data_models) which are about managing models, not querying metrics.

  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 vs siblings or other alternatives. Does not mention prerequisites, contexts, or when to avoid using it. The only hint is 'automatically uses the configured tenant,' which is not a usage guideline.

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

• vunet_list_data_modelsB
  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 the full burden of behavioral disclosure. It only states the purpose and category filtering, with no mention of pagination, rate limits, or whether the list is exhaustive. This is insufficient for a list operation with no other context.

  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 that front-loads the main action. It is efficient, though the word 'common' could be more precise. Slightly more context would improve it without sacrificing conciseness.

  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 list tool with one parameter and no output schema, the description is minimally adequate. It fails to mention the response format (e.g., list of model names with descriptions) or that it returns only common models. Given no annotations, more context 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%, so the schema already documents the category parameter. The description adds little beyond restating the categories and the concept of organization. Baseline of 3 is appropriate as no additional semantic 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 specifies the verb 'List' and the resource 'common Vunet data models', and indicates organization by category. This distinguishes it from the sibling tool vunet_fetch_datamodels, which likely retrieves details of specific models.

  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?

  Usage is implied but not explicit. The description does not state when to use this over alternatives, nor does it provide exclusions. Sibling names give some context, but no direct guidance.

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

• vunet_get_statusA
  3.5/5.0
  Behavior2/5

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

  With no annotations, the description bears full responsibility for behavioral disclosure. It mentions 'Get' implying a read-only operation, but does not elaborate on any side effects, authentication requirements, rate limits, or the structure of the returned information.

  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 of 10 words, effectively conveying the tool's purpose without any extraneous information. It is concise and 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 the tool's simplicity (no parameters, no output schema), the description provides a basic understanding. However, it lacks specificity about what exactly 'connection status' and 'tenant information' entail, which would help an agent interpret the results.

  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?

  There are no parameters (0 params), so schema coverage is 100%. The description adds no parameter information because none is needed, meeting the baseline expectation for a zero-parameter tool.

  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 that the tool retrieves 'connection status and tenant information', using the specific verb 'Get'. This distinguishes it from sibling tools like vunet_fetch_datamodels or vunet_query_metric, which focus on data models and metrics respectively.

  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 or when not to use this tool versus alternatives. It simply describes the function without any context for selection among sibling tools.

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

• vunet_fetch_datamodelsA
  4/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. It describes it as a read operation that fetches live data, but doesn't cover auth needs, rate limits, or side effects. Adequate but not comprehensive.

  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 with no wasted words. First sentence gives action and endpoint; second sentence states output and usage guidance. Front-loaded and 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?

  For a tool with 5 parameters, no output schema, and no annotations, the description adequately covers purpose, output content, and usage context. Missing details on pagination or error handling, but still complete enough for basic use.

  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 schema already explains all parameters. The description adds context about discovery but no extra syntactic or behavioral details 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 it fetches actual live DataModels via a specific API endpoint, lists what it returns (signal names, types, data sources, column details), and distinguishes from sibling tools by mentioning its use before vunet_query_metric.

  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?

  Explicitly tells when to use it ('discover what data is available before querying with vunet_query_metric'). Could be improved by noting when not to use or alternatives like vunet_list_data_models.

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