Server Quality Checklist

Tool Scores

• describe_tableA
  3.6/5.0
  Behavior2/5

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

  No annotations are provided, so the description must bear the entire burden of disclosing behavioral traits. It does not mention whether the operation is read-only, whether it can fail on non-existent tables, or any side effects. While the tool name and wording imply a harmless read, the description offers no explicit transparency about error handling or assumptions, leaving an agent potentially uninformed.

  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, direct sentence that immediately communicates the core function and output fields. There is no filler or redundancy, and it is appropriately sized for a one-parameter utility tool.

  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 presence of an output schema and the simplicity of the tool, the description covers the essential information: it states the input (table) and the output (column details). It lacks explicit notes on error cases or prerequisites, but for a straightforward metadata query, this is largely sufficient. The existence of an output schema reduces the need to describe return values in detail.

  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 schema provides only a parameter name 'table' with type string, and schema description coverage is 0%. The description adds the semantic that the parameter refers to the table whose columns are to be described, which is valuable. However, it does not specify format constraints (e.g., whether it must match an existing table exactly, case sensitivity, or quoting rules). It partially compensates for the schema gap but could be more explicit.

  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 states a specific verb (describe) and resource (table columns), and clearly specifies the returned attributes: name, type, and required status. This distinguishes it from sibling tools like list_tables (which lists table names) and run_query (which executes queries). An agent can accurately select this tool for schema inspection without ambiguity.

  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 should be used when needing column-level metadata for a specific table, but it does not explicitly state when to prefer it over alternatives or mention exclusions. For example, it does not say 'use run_query for filtering data' or 'use list_tables to see available tables.' The context is clear from the purpose, but explicit routing guidance is missing.

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

• pingA
  3.8/5.0
  Behavior3/5

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

  Annotations are absent, so the description must carry the burden of behavioral disclosure. 'Check that the server is alive' conveys the intent but does not mention whether it performs a network call, what it returns (though output schema exists), or that it is a read-only operation. The description is not misleading, but it adds minimal behavioral detail beyond the 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 concise clause, front-loading the core purpose with no extraneous words. Every word earns its place, making it highly efficient for an agent to parse.

  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 zero-parameter health check with an output schema present, the description is complete. An agent knows that calling the tool requires no inputs and will return a result defined by the schema. No additional context is needed to invoke it correctly.

  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 tool has zero parameters, so the schema carries no parameter information to describe. The baseline is 4, and the description need not add any parameter documentation. It correctly implies no arguments are required.

  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 'check' and the resource 'server is alive', making the tool's purpose unambiguous. It naturally distinguishes itself from sibling tools (list_tables, describe_table, run_query) which handle database operations, though it does not explicitly name them as alternatives.

  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 provides no explicit guidance on when to use this tool versus the siblings. While it is evident that it is a health check and the siblings are for table/query operations, the description does not state 'use this to verify connectivity before running queries' or any other usage context. It relies on the agent to infer from the tool name and description.

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

• run_queryA
  3.8/5.0
  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 discloses that the operation is read-only, caps results at 500 rows, sets the 'truncated' flag when exceeded, and aborts queries longer than 5 seconds. This covers safety, limits, and timeout behavior, which is substantial. It does not describe the exact response structure, but an output schema is present to handle that.

  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 concise and front-loaded: the core action is stated first, followed by two constraint sentences that are directly actionable. Every sentence adds value (payload limit, truncation handling, timeout), with no fluff or repetition. It is well-structured and easy to scan.

  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 a single parameter, and the description covers key operational aspects: read-only nature, row limit, truncation flag, and timeout. Given an output schema exists (for return format) and the tools is simple, the description is nearly complete. It lacks error-handling details, but those are often covered by the runtime rather than the description. Overall, it adequately equips 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?

  Schema description coverage is 0%, so the description must compensate. It implies that the 'sql' parameter is the SELECT query to run, but does not explicitly state 'sql contains the query'. For a single parameter named 'sql', this is reasonably inferred. The description adds minimal further semantics beyond the parameter name, but the connection is clear.

  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 'Run' and the resource ('read-only SELECT query'), specifying exactly what the tool does. It differentiates itself from siblings like list_tables and describe_table by focusing on arbitrary SELECT queries, though it doesn't explicitly contrast with them. The action and scope are unambiguous.

  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 mention when to use this tool versus alternatives. It does provide practical guidance on handling truncation ('add a LIMIT or aggregate instead') and timeout, which helps the agent use the tool correctly. However, it assumes the agent understands the difference from ping/list_tables/describe_table, providing no explicit selection criteria.

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

• list_tablesA
  3.9/5.0
  Behavior3/5

  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 states the core function but adds no extra context such as whether the operation is read-only, requires any permissions, or has side effects. While the purpose is clear and it is evidently a passive listing operation, the description does not explicitly guarantee that nothing is mutated or that it is safe to call repeatedly.

  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, front-loaded sentence that states exactly what the tool does with no superfluous content. Every word earns its place, and it is immediately scannable. It achieves maximum conciseness while preserving clarity.

  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?

  Given that the tool has no parameters and an output schema exists (providing the return format), the description is complete for its purpose. It tells the agent what the tool does (lists table names) and nothing more is required for a successful invocation. There are no configuration details, prerequisites, or edge cases that need to be disclosed.

  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 tool takes zero parameters, and the schema shows an empty properties object, so there is no parameter information to add. The baseline for 0 parameters is 4, and the description correctly reflects that no arguments are needed. It does not add anything about parameters because there are none, but it also does not create any confusion.

  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 ('list') and a precise resource ('names of every table in the database'). It clearly distinguishes itself from siblings: 'ping' (health check), 'describe_table' (specific table schema), and 'run_query' (executes queries). An agent can immediately understand what this tool does and why it differs from the others.

  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 gives no explicit guidance on when to use this tool versus alternatives. It does not mention that this should be used to discover tables before querying or describing them, nor does it note any limitations or exclusions. The usage context is only implied by the sibling names, not stated.

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