Server Quality Checklist

Tool Scores

• get-dataflowB
  3.4/5.0
  Behavior3/5

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

  The description is accurate but does not disclose any behavioral traits beyond being a read operation. With minimal annotations (title only), the description carries the burden but omits details like idempotency, caching, or error behavior. No contradiction with annotations.

  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 very concise (one sentence) with no wasted words. However, it lacks additional details that could be included without bloat.

  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 (1 parameter, output schema exists), the description is minimally adequate. It misses usage guidelines and any prerequisites, but the output schema compensates for return value documentation.

  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%, and the schema already provides a description for the only parameter (dataflowId). The tool description adds no additional meaning beyond the schema, so 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 (Get) and the resource (a Coupler.io data flow by ID). It distinguishes from siblings like 'list-dataflows' (list) and 'get-data'/'get-schema' (different entities).

  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 (e.g., when to use 'list-dataflows' or 'get-data'). No explicit 'when to use' or 'when not to use' context.

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

• get-dataA
  3.6/5.0
  Behavior3/5

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

  The annotations include idempotentHint: true, which already indicates that the tool is safe to repeat. The description adds no behavioral details beyond that, such as side effects, authentication needs, or rate limits. It does not contradict the annotations, but it also does not provide extra disclosure beyond the purpose (getting data). Given the annotations cover the main behavioral trait, a score of 3 is appropriate.

  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 front-loaded with the main purpose in the first sentence. It includes necessary workflow instructions but could be more concise by separating usage guidelines from the core purpose. The length is reasonable and does not contain fluff, though the sample query and get-schema instructions could be part of a separate section.

  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?

  The tool has an output schema (per context signals), so the description does not need to explain return values. The description gives enough context to use the tool in combination with the sibling tools (get-schema, list-dataflows). It covers the prerequisite steps and important caveats (no file/URL fetching). Overall, combined with the structured information, the description is sufficiently complete for an agent to use the tool effectively.

  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%, with each parameter (dataflowId, executionId, query) having a clear description in the input schema. The tool description does not add any semantic information beyond what the schema already provides. The example query in the description ('SELECT * from data LIMIT 5') is a usage hint, not parameter semantics. Therefore, no added value beyond the schema baseline.

  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 tool name 'get-data' and title 'Get and query data from a Coupler.io data flow' clearly indicate that the tool retrieves data. The description starts with 'Get data from a Coupler.io data flow run', which aligns with the purpose. However, it does not explicitly distinguish itself from sibling tools like get-schema or list-dataflows, though the name and context imply the distinction.

  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 workflow guidance: first query a sample of 5 rows using a SELECT statement, then run get-schema to understand the structure. It also instructs on visualization behavior ('do not try to read any files or fetch any URLs'). While it gives clear context on when to use this tool, it does not mention when not to use it or explicitly name alternatives, though get-schema is referenced as a prerequisite.

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

• get-schemaA
  4/5.0
  Behavior4/5

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

  Annotations set idempotentHint=true, confirming safe reuse. The description adds behavioral context by explaining how to interpret the response (columnName properties) and providing a concrete example. No contradictions with annotations.

  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?

  Three sentences, no filler. First sentence defines the action, second explains how to extract column names, third provides an illustrative example. Every sentence 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.

  Completeness4/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool with 2 required parameters, existing output schema, and idempotent annotation, the description adequately covers purpose and response interpretation. Lacks explicit error scenarios or prerequisites beyond parameter descriptions, but overall complete enough.

  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?

  Both parameters (dataflowId, executionId) have clear descriptions in the input schema, achieving 100% schema coverage. The description does not add additional meaning to these parameters, focusing instead on the output format. 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 'Get data table schema from a Coupler.io data flow' with a specific verb and resource. It distinguishes from siblings by focusing on schema retrieval, differentiating from get-data (data), get-dataflow (metadata), and list-dataflows (enumeration).

  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 does not explicitly state when to use this tool versus alternatives. It implies usage for obtaining column names before fetching data, but lacks explicit when-to-use or when-not-to-use guidance. The example helps but does not clarify selection criteria.

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

• list-dataflowsA
  4.5/5.0
  Behavior4/5

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

  Annotations include idempotentHint=true, indicating no side effects. Description adds that it lists 'my' data flows (scope) and returns IDs, which is consistent and adds value.

  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 short, informative sentences with no extraneous information. Purpose and specific usage are front-loaded.

  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 parameterless list tool with an output schema, the description covers the essential: it lists flows and can be used to find an ID by name. No further guidance is needed.

  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?

  Tool has zero parameters, baseline is 4. Description does not add parameter info, but schema coverage is 100% since there are no parameters.

  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 it lists Coupler.io data flows and specifies the use case: to get a data flow's UUID by name. Distinguishes from sibling tools like get-dataflow (which likely returns a single flow) by its listing nature.

  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 advises using it to retrieve a data flow ID by name, providing a clear context. Does not mention when not to use or alternatives, but for a simple list tool this is sufficient.

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