Server Quality Checklist

Tool Scores

• list_tablesA
  3.6/5.0
  Behavior3/5

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

  No annotations are provided, but the description discloses that the tool reads from INFORMATION_SCHEMA, which implies a read-only metadata operation and scopes to the current database. However, it does not describe output format, ordering, or the impact of the schema filter beyond what the schema says.

  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 one concise sentence that directly states the tool's function without filler, earning a top score.

  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 simple listing tool with one optional parameter and no output schema, the description is mostly adequate but lacks explicit return value information (e.g., whether it returns schema names, table types, or ordering). For a simple tool, this is acceptable, but it could be more complete.

  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 describes the optional 'schema' parameter with an example, and the description does not add further parameter semantics. Since schema coverage is 100%, the schema carries the burden, so a baseline score of 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 the specific verb 'List' with the resource 'tables and views' and scoping to the current database, clearly differentiating from sibling tools like describe_table (which targets a single table).

  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 explicit guidance on when to use this tool versus alternatives; the description simply states its function without mentioning query, analyze_query, or describe_table. Usage is implied but not stated.

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

• describe_tableA
  3.8/5.0
  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 tool's output (columns, types, nullability, defaults), which is the core behavior. However, it does not mention error handling, permissions, or what happens if the table does not exist, leaving some gaps.

  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 nine words, front-loaded with the verb and resource. Every word earns its place, making it extremely concise without losing clarity.

  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 simple describe operation with only two parameters and no output schema, the description provides the essential information about the return value. It does not specify output format or edge cases, but the tool's simplicity means this is minimally sufficient.

  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 covers 100% of the parameters with descriptions, so the baseline is 3. The description does not add any extra parameter-specific semantics, but the schema already defines the table and schema parameters adequately.

  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 'Return' and identifies the resource as a table, listing the exact metadata fields (columns, types, nullability, defaults). This clearly differentiates it from siblings like query or list_tables, which have 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 Guidelines3/5

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

  The description implies the tool is used to retrieve table structure, which is an implied usage context. However, it does not explicitly state when to use it versus alternatives like list_tables or analyze_query, nor does it provide exclusions or prerequisites.

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

• queryA
  4.2/5.0
  Behavior4/5

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

  With no annotations, the description carries the full burden. It discloses read-only behavior, permitted statement types, rate limits, concurrency limits, and error/retry behavior. This is strong coverage, though it omits details like handling of non-SELECT statements or maxRows defaults, leaving a small gap.

  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, no fluff. The first sentence front-loads purpose and output format; the second adds rate limit and read-only constraints. Every word earns its place.

  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 simple 2-parameter tool with no output schema or annotations, the description covers the essential operational context: purpose, output format, safety (read-only), and rate limits. It lacks explicit error scenarios, but the description is reasonably complete for its complexity.

  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% for both parameters, so the schema already documents 'sql' and 'maxRows'. The description does not add extra parameter semantics beyond the schema, meeting the baseline but not exceeding it.

  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 specific verb+resource: 'Execute a single SELECT query against SQL Server and return rows as JSON.' This distinguishes it from siblings like list_tables and describe_table, which have 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 provides clear context for use (querying data with SELECT/WITH) and explicitly notes the read-only constraint. It does not mention alternatives or when not to use, so it falls short of a 5, but the intended usage is unmistakable.

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

• analyze_queryA
  4.5/5.0
  Behavior5/5

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

  With no annotations, the description carries full burden. It discloses rate limits (30 per 60s, 4 concurrent), the error behavior on exceeding them, and the nature of returned data (plan warnings, missing indexes, I/O stats). It implies read-only behavior via SELECT, which is sufficient for this tool.

  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 core function and followed by a concise use case and rate-limit warning. Every sentence earns its place with no unnecessary detail.

  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?

  Despite no output schema, the description enumerates the key return data (estimated vs actual rows, logical/physical reads, timing, missing-index suggestions, plan warnings). It also covers rate limits and execution scope, making it complete for an agent to select and invoke 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?

  The input schema provides full descriptions for all three parameters (sql, maxRows, includePlanXml) with 100% coverage. The description adds no additional parameter semantics beyond what the schema already states, so the baseline score of 3 applies.

  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 executes a SELECT with SET STATISTICS and returns structured performance data including per-operator rows, reads, timing, missing-index suggestions, and plan warnings. This specific focus on performance diagnostics distinguishes it from the sibling query tool, making its purpose unambiguous.

  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 explicitly says 'Use this to explain why a query is slow,' which provides a clear use case. It does not explicitly contrast with the query sibling, but the performance-analysis angle implies it is for diagnostics rather than general execution. The SELECT-only constraint is also mentioned.

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