Server Quality Checklist

Tool Scores

• execute_queryC
  2.9/5.0
  Behavior2/5

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

  No annotations provided, so the description must disclose behavioral traits. It only mentions execution against Azure SQL but does not address potential side effects (data modification, schema changes), performance impact, required permissions, or error states. This is insufficient for a tool that can alter data.

  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?

  Extremely concise (two sentences) with front-loaded purpose. Every word earns its place given the single parameter. However, the brevity sacrifices important behavioral context, making it feel under-specified rather than efficiently concise.

  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's complexity (arbitrary SQL execution) and lack of annotations, the description is incomplete. It does not cover allowed operations, query safety, or connections to sibling tools. The existence of an output schema justifies no return-value explanations, but other gaps remain 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?

  With 0% schema description coverage, the description must add meaning. It provides an example query and states the parameter is a SQL query. This clarifies the parameter's intent beyond the raw schema, but lacks details on syntax rules, limits, or escape characters. Barely meets minimal expectations.

  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 clearly states the tool's action ('Execute a SQL query') and target resource ('Azure SQL database'). It distinguishes from sibling tools (check_database_config, get_tables, etc.) by its verb and scope. However, it doesn't specify allowed query types (e.g., SELECT only, DDL, DML), which could cause agent confusion.

  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 versus alternatives like get_sample_data or get_table_schema. Missing exclusions such as 'do not use for schema inspection' or warnings about destructive queries. The example suggests a SELECT, but the description does not restrict usage.

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

• get_table_schemaB
  3.4/5.0
  Behavior2/5

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

  With no annotations provided, the description carries full burden for behavioral disclosure. It only mentions 'schema information' without specifying what that includes (e.g., columns, types, constraints) or whether it is read-only. This is a significant gap for a tool that retrieves database metadata.

  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 short and front-loaded with the main purpose. The structure with 'Args' is clear, but it could be more concise by removing the 'Args' header if not needed. Overall, every sentence earns its place.

  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 (one parameter) and presence of an output schema, the description is adequate but not complete. It does not clarify what the output schema contains, which is important for an AI agent to interpret results. More detail 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?

  The input schema has no description (0% coverage), so the description adds value by explaining the 'table_name' parameter with an example. However, it could provide more detail on valid formats or restrictions beyond the example.

  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 schema information') and the resource ('a specific table'), making the purpose unambiguous. It naturally distinguishes from sibling tools like 'get_tables' which likely lists table names, while this tool retrieves schema details.

  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 provide explicit guidance on when to use this tool versus alternatives. While the purpose is clear, there is no mention of when to prefer this over 'execute_query' or 'get_tables', or under what conditions it should be used.

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

• get_sample_dataA
  3.5/5.0
  Behavior2/5

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

  No annotations exist, and the description does not disclose read-only nature, error handling for missing tables, or any side effects. It only describes parameters.

  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?

  Minimal and well-structured: purpose in first sentence, parameter docs follow. Every sentence adds value.

  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?

  Adequate for a simple tool with output schema, but lacks usage guidelines and behavioral details that would make it fully self-contained.

  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 description adds concrete examples and constraints for both parameters (e.g., table_name format, limit defaults and max), compensating for the schema's 0% description coverage.

  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 verb 'Get' and resource 'sample data from a table', which distinguishes it from sibling tools like execute_query or get_table_schema.

  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 explicit guidance on when to use this tool versus alternatives, nor any context about when not to use it.

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

• check_database_configA
  3.8/5.0
  Behavior2/5

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

  No annotations are provided, so the description must fully cover behavioral traits. It only states that it returns configuration status and errors, but does not mention whether it is read-only, modifies state, or requires any permissions. This is insufficient for a tool with no 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?

  The description is two sentences, front-loaded, and contains no unnecessary information. Every sentence serves a purpose.

  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 tool's simplicity (no parameters, output schema exists), the description is mostly complete. It mentions the return type (status and errors). However, it could explicitly state that it does not modify any state, which would improve completeness for an agent.

  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, so schema coverage is 100%. The description adds no parameter info, but with zero parameters, baseline 4 is appropriate as there is nothing to add.

  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 checks database configuration, which is a specific verb+resource combination. It is distinctly different from sibling tools like execute_query and get_tables, which focus on data operations rather than configuration.

  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 versus siblings. The context implies it might be used prior to queries to ensure configuration, but no clear when-not or alternative recommendations are provided.

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

• get_tablesA
  4.1/5.0
  Behavior3/5

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

  No annotations provided, so the description bears the full burden. It implies a read-only listing but does not explicitly state safety, performance, or side effects. Adequate for a simple list operation.

  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?

  Single sentence with no extraneous words. Front-loaded and to the point.

  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 parameter-free list tool with an output schema (not shown), the description sufficiently covers functionality. No gaps given simplicity.

  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?

  No parameters, so schema coverage is 100%. The description adds no parameter info, which is acceptable. Baseline score of 4 for zero-parameter tools.

  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 verb 'Get list of all tables' and the resource 'Azure SQL database', which is distinct from sibling tools that focus on specific tables, schemas, data, or queries.

  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 vs alternatives, but the scope is obvious (listing all tables). No exclusions or context provided.

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