Server Quality Checklist

Tool Scores

• query_data_extensionA
  3.9/5.0
  Behavior3/5

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

  With no annotations, the description partially compensates by mentioning pagination (max 50 rows), filter operators, and ordering. However, it lacks details on side effects (e.g., read-only guarantee), error conditions, or authorization requirements.

  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 main purpose, and covers all essential features without waste. Each sentence contributes meaning.

  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 no output schema, the description could better explain the response structure or field selection. It is adequate for a simple query tool but lacks details on error handling or data format.

  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 value by explaining the filter format with examples, pagination limits, and ordering syntax, going beyond the schema's parameter 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 it queries records from a Data Extension by external key, supporting filter, ordering, and pagination. It distinguishes from sibling tools list_data_extensions and validate_sql by specifying this tool is for querying specific records.

  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?

  No explicit guidance on when to use this tool versus alternatives. It does not mention that list_data_extensions should be used for listing Data Extensions or validate_sql for SQL validation. Usage context is only implied.

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

• list_data_extensionsA
  4/5.0
  Behavior3/5

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

  The description discloses features like pagination, name filter, and optional fields, but does not mention permission requirements, rate limits, or confirm read-only behavior. Since no annotations are provided, the description carries the full burden, and it is adequate but not exhaustive.

  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, well-structured sentence that efficiently conveys the tool's purpose, optional features, and filtering support. No unnecessary words.

  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 mentions the returned fields (name, external key, and optionally fields). The tool is simple and the description covers essential information for invocation. Could mention sorting or ordering, but not critical.

  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 baseline is 3. The description adds that default returns include name and external key, but the parameter descriptions in the schema already cover the details. No significant value beyond schema.

  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 lists Data Extensions from the connected Business Unit, with name and external key, and optionally fields. This distinguishes it from sibling tools query_data_extension and validate_sql, which serve 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 Guidelines4/5

  Does the description explain when to use this tool, when not to, or what alternatives exist?

  The description implies use for listing Data Extensions with filtering and pagination, but does not explicitly state when not to use it versus alternatives. Since the siblings are distinct, the context is clear but lacks explicit exclusion guidance.

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

• validate_sqlA
  4.2/5.0
  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 what the tool checks (ORDER BY, CTE, MERGE, variables, temp tables, unsupported functions) and that it optionally validates Data Extensions and target schema. It states it returns blocking errors, warnings, and suggestions. However, it doesn't mention read-only behavior or rate limits, but for a validation tool the transparency is good.

  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 purpose. Every sentence adds value without redundancy. The structure is efficient 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?

  No output schema exists, but the description explains what the tool returns (errors, warnings, suggestions). Given the tool's complexity (3 parameters, validation focus), the description covers the essential behavioral aspects. Could mention if it modifies anything, but likely not needed.

  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% (all three parameters have descriptions). The tool's description adds value by setting context (e.g., highlighting that checkSchema controls DE validation), but it doesn't add meaning beyond what the schema already provides for each parameter. 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 uses specific verbs ('Valida', 'Checa', 'confere') and specifies the resource ('Query Activity do SFMC Automation Studio'). It clearly lists what is checked (unsupported constructs, existence of DEs and columns) and what is returned (errors, warnings, suggestions), distinguishing it from siblings like list_data_extensions and query_data_extension.

  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 clearly states when to use this tool ('antes de executá-la' - before executing a query). It does not explicitly mention when not to use it or name alternatives, but the context is clear enough for an agent to infer appropriate usage.

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