Server Quality Checklist

Tool Scores

• get_table_structureC
  2.9/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves metadata, implying a read-only operation, but fails to mention critical details like whether it requires specific database permissions, if it works on views or only tables, error handling for non-existent tables, or the format of the returned structure. This is inadequate for a tool with no annotation coverage.

  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, efficient sentence that front-loads the core purpose ('Get the structure/schema of a SQL Server table') and adds specific details without waste. Every word earns its place, making it easy for an agent to parse quickly.

  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 complexity of database operations and the lack of annotations and output schema, the description is incomplete. It doesn't explain the return format (e.g., JSON, table-like structure), error conditions, or behavioral nuances like permissions. For a tool with no structured data to rely on, this leaves significant gaps for an agent to invoke it correctly.

  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 100% description coverage, fully documenting the single 'table' parameter. The description adds no additional parameter semantics beyond what the schema provides (e.g., it doesn't clarify syntax beyond 'can include schema' or mention case sensitivity). With high schema coverage, the baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

  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 verb ('Get') and resource ('structure/schema of a SQL Server table') with specific details about what is retrieved ('column names, data types, and constraints'). It distinguishes from siblings like 'get_table_count' and 'get_table_data' by focusing on metadata rather than row counts or content. However, it doesn't explicitly differentiate from 'query_data', which could also return schema information, preventing a perfect score.

  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 like 'get_table_data' or 'query_data'. It lacks context about prerequisites (e.g., database connection, permissions) or exclusions (e.g., not for querying actual data). This leaves the agent with minimal direction for tool selection.

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

• get_table_countB
  3.1/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool counts records, implying a read-only operation, but does not cover aspects like performance impact, error handling, or whether it requires specific permissions. This leaves gaps in understanding the tool's behavior beyond its basic function.

  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, clear sentence that directly states the tool's function without unnecessary words. It is front-loaded and efficiently conveys the essential information, making it highly concise and well-structured.

  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, no output schema, no annotations), the description adequately covers the basic purpose. However, it lacks details on usage context, behavioral traits, and output format, which could be important for an AI agent to invoke it correctly in more complex scenarios.

  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 100% description coverage, fully documenting the single 'table' parameter. The description does not add any extra meaning beyond the schema, such as format examples or constraints, so it meets the baseline score when the schema handles parameter documentation effectively.

  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 action ('Get the total count') and resource ('records in a SQL Server table'), making the purpose immediately understandable. It does not explicitly differentiate from sibling tools like 'get_table_data' or 'query_data', which might also involve table operations, so it misses the highest score for sibling distinction.

  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 such as 'get_table_data' or 'query_data'. It lacks context about prerequisites, exclusions, or specific scenarios where counting records is preferred over other table-related operations.

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

• get_table_dataB
  3.2/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries full burden. It mentions pagination enforcement and returns a page of records, but lacks details on permissions required, rate limits, error handling, or what happens with invalid inputs (e.g., non-existent table). For a read operation with zero annotation coverage, this is insufficient.

  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 concise (two sentences) and front-loaded with the core purpose. Every sentence earns its place by specifying pagination and return type, though it could be slightly more structured (e.g., separating key behaviors).

  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 annotations and no output schema, the description is moderately complete for a read tool with full schema coverage. It covers the basic operation but lacks details on behavioral aspects like error cases or response format, which are important for a tool with 4 parameters and pagination 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%, so the schema fully documents all 4 parameters. The description adds no additional meaning beyond what's in the schema (e.g., it doesn't explain pagination logic or default behaviors further). Baseline 3 is appropriate when schema does the heavy lifting.

  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 verb ('Get paginated data') and resource ('from a SQL Server table'), specifying it returns a page of records with pagination. It distinguishes from siblings like 'get_table_count' (counts records) and 'get_table_structure' (schema info), but doesn't explicitly mention 'query_data' as an alternative for filtered 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?

  The description implies usage for retrieving paginated table data, but doesn't explicitly state when to use this vs. alternatives like 'query_data' (which might allow filtering) or 'get_table_count' (for counts only). No guidance on prerequisites or exclusions is provided.

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

• query_dataA
  4.3/5.0
  Behavior4/5

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

  With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes key behavioral traits: the tool enforces pagination, restricts to SELECT queries only, and rejects DDL/DML operations. However, it doesn't mention other potential behaviors like error handling, timeout limits, or authentication requirements, 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 extremely concise and front-loaded with essential information in just two sentences. Every word earns its place: the first sentence states purpose and key constraint, the second clarifies allowed/rejected operations. No wasted words or redundancy.

  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 annotations and no output schema, the description does well on purpose and usage but has gaps. It doesn't describe the return format (e.g., result set structure), error responses, or other behavioral aspects like rate limits. For a query execution tool with 3 parameters, this is adequate but incomplete.

  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%, so the schema already fully documents all three parameters (query, page, pageSize). The description adds some context by mentioning 'enforced pagination' and the SELECT-only restriction, but doesn't provide additional parameter semantics beyond what's in the schema. This meets the baseline for high schema 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 specific action ('Execute a SELECT query') and resource ('SQL Server database') with explicit constraints ('with enforced pagination', 'Only SELECT queries are allowed'). It distinguishes from potential siblings by emphasizing the query execution nature versus table-specific operations like get_table_count, get_table_data, and get_table_structure.

  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?

  The description provides explicit usage guidelines: use for SELECT queries only, with enforced pagination, and explicitly states when not to use it (DDL and DML operations like CREATE, ALTER, DROP, INSERT, UPDATE, DELETE are rejected). This gives clear alternatives (avoid this tool for non-SELECT operations) and context for when it's appropriate.

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