Server Quality Checklist

Tool Scores

• healthA
  4.3/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden of behavioral disclosure. It explicitly lists the checks performed, which implies a read-only health check. It does not detail return format or permission requirements, but given the nature of a health check, this is reasonably transparent.

  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 sentence long, front-loaded with the primary action, and provides specific details without any wasted words. Every sentence contributes to the understanding of the tool's purpose.

  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?

  For a simple health check with zero parameters and an output schema, this description adequately covers the purpose and the specific checks. It is complete enough for an agent to select and invoke the tool correctly, and the output schema handles return-value details.

  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 tool has zero parameters, so the schema is trivially complete. The description does not need to explain parameters, and it doesn't. Baseline score of 4 for parameter-less tools 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's function with a specific verb ('Check') and resource ('server configuration and inputs'). It lists concrete checks (target directory, artifacts, warehouse connectivity), which distinguishes it from sibling tools like run_summary, list_failing_tests, and sample_failing_rows that deal with test outputs rather than system health.

  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 use for verifying system readiness but provides no explicit guidance on when to choose this tool over alternatives, nor does it mention exclusions or prerequisites. The context is clear but lacks direct 'use this when' statements.

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

• list_failing_testsA
  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 the scope and the kind of output, but it does not mention that this is a read-only operation, what happens if no run exists or no tests fail, or any permissions/dependencies. Since an output schema exists, the description's enumeration of return fields is partly redundant, but the 'generic vs hand-written' distinction adds useful semantic context.

  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 and well-structured: the first sentence states the primary purpose, and the second elaborates on the output. It is front-loaded with the core action and contains no filler or redundant wording.

  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?

  For a simple, zero-parameter tool with an output schema, the description is complete enough. It captures the essential purpose, scope, and distinguishing return information. No key context appears missing.

  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 tool has zero parameters, so the empty schema has 100% coverage. According to rubric, 0 params gives a baseline of 4. The description does not need to explain parameters, and it doesn't introduce confusion.

  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 uses a specific verb ('List') and resource ('failing tests') with clear scope ('in the last dbt run'). It also enumerates returned fields (test name, model/column, rows failed, generic vs hand-written), making it unambiguous and distinct from siblings like sample_failing_rows and run_summary.

  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 gives clear context for when this tool applies ('last dbt run' and listing all failures), but it does not explicitly mention alternatives or scenarios where a sibling tool like sample_failing_rows would be preferable. Thus it has clear context but no exclusions.

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

• sample_failing_rowsA
  4.3/5.0
  Behavior3/5

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

  With no annotations, the description must convey behavioral traits. It discloses that the tool fetches rows and that the limit is intentionally small. It also implies the operation is read-only via the verb 'Fetch'. However, it does not describe error behavior for invalid test_name, response format, or what happens when no rows exist. This leaves some transparency gaps, but the provided details are meaningful.

  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 succinct and well-structured. It opens with a one-sentence purpose, followed by a clear Args list. Every sentence earns its place, with no fluff or repetition. The format is front-loaded and easy to parse.

  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 the output schema is present, the description does not need to detail return values. It covers the tool's purpose, parameter semantics, and usage sequence, which is sufficient for a simple read operation. It could mention edge cases (e.g., no failing rows) but these are likely covered by the output schema. Overall, it is complete for its complexity.

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

  Parameters5/5

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

  Even though schema descriptions are absent (0% coverage), the description's Args section compensates fully. It explains test_name as 'the test's name or unique_id' from list_failing_tests, and limit as 'maximum rows to return (kept small on purpose)'. This adds meaning beyond the bare schema and clarifies how to supply each parameter correctly.

  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's function: 'Fetch the actual rows that caused a test to fail.' This is a specific verb+resource combination that distinguishes it from sibling tools like list_failing_tests (which lists tests) and run_summary (which provides summaries). The purpose is unambiguous and immediately recognizable.

  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 explicit usage context by stating test_name is 'as returned by list_failing_tests', indicating the workflow of calling list_failing_tests first. It also adds the caution that limit is 'kept small on purpose', setting expectations for output size. However, it does not explicitly state when not to use this tool or mention alternative tools for other scenarios, so it falls short of a perfect score.

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

• run_summaryA
  4.7/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It discloses the core behavior (summarising recent run, test failure count and names) and the 'most recent' scope. It doesn't detail side effects, but for a read-only summary, this is adequate.

  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, front-loaded with the action and key output. The second sentence adds actionable usage context without unnecessary detail. Very concise and well-structured.

  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?

  The tool is simple and zero-parameter. The description covers purpose, scope, and usage order. An output schema exists, so return details are not needed in the description. The guidance to use first provides necessary context for a health-check step.

  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 tool has zero parameters, so schema coverage is 100% vacuously. Per guidelines, 0 params earns a baseline 4. The description adds no parameter information, which is appropriate since none exist.

  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 summarises the most recent dbt run, specifically how many tests failed and their names. This is a specific verb+resource combination that distinguishes it from sibling tools like list_failing_tests and sample_failing_rows.

  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 instructs to use this tool first to judge overall health before drilling into any one failure, providing clear when-to-use guidance and implying it precedes more detailed tools.

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