Server Quality Checklist

Tool Scores

• describe_tableA
  4/5.0
  Behavior3/5

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

  No annotations are present, so the description carries the full burden. It clearly discloses what the tool returns (column names, data types, nullability), but it does not explicitly state that it is a read-only operation or mention any side-effect-free behavior. This is adequate but not rich.

  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 filler. The key return information is front-loaded, and the usage instruction is placed immediately after. Every sentence 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 two-parameter tool, the description covers what the tool returns, its single-table scope, and when to use it. The input schema covers parameter semantics. Slightly more explicit differentiation from sibling tools would make it fully 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?

  Schema description coverage is 100%, with both owner and tableName already documented in the input schema. The description adds no parameter-level detail beyond what the schema provides, 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 states a specific verb ('Returns') and a specific resource ('column names, data types, and nullability for exactly one table'). The 'exactly one table' qualifier differentiates it from list_tables, and the metadata focus differentiates it from run_sql.

  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 to call this only for tables relevant to the question, giving clear usage context. It does not explicitly mention alternatives like list_tables or run_sql, but the scope is reasonably clear.

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

• list_tablesA
  4/5.0
  Behavior3/5

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

  With no annotations, the description carries the full burden. It clarifies that only table names are returned and not columns, and hints at read-only behavior, but it doesn't describe output format, sorting, pagination, or error/limits behavior.

  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 short sentences front-load the core purpose and then provide a targeted usage note. There is no wasted wording; every sentence 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, optional-parameter enumeration tool with no output schema, this description covers the what, the scope, the filter mechanism, and the key distinction from describe_table. It could add return-format details or permission context, but the core invocation is adequately 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?

  Schema description coverage is 100% and both parameters are already documented clearly in the schema. The description paraphrases those meanings ('explicit OWNER', 'optionally filtered by a SQL LIKE pattern') without adding new details beyond the 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?

  Description states a specific verb and resource: 'Lists table names for the connected schema or an explicit OWNER'. It also differentiates itself from describe_table by noting 'it does not return columns'.

  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?

  Gives explicit usage direction: 'Call this before describe_table', making the workflow intentions clear. It does not address when to prefer list_tables over run_sql, but does provide useful context for the primary sibling.

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

• run_sqlA
  4.1/5.0
  Behavior3/5

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

  Discloses the key safety trait—read-only execution with DML/DDL disabled—which is important since no annotations are provided. However, it is silent on return shape, large-result behavior, error handling, and what happens if allowWrite=true is passed, leaving meaningful behavioral 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?

  Two tight sentences with no filler; the first front-loads the core purpose and the second provides essential environment context about write support.

  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?

  Covers the core operation and read-only constraint, and the schema handles parameter details. But with no output schema and no annotations, the lack of any return/result description or allowWrite-behavior note leaves the definition somewhat incomplete for a SQL execution tool.

  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 schema already fully describes the sql, binds, and allowWrite parameters at 100% coverage. The description adds value by restricting sql to SELECT/WITH statements, which the schema does not explicitly state.

  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?

  States a specific action ('Executes') and resource ('read-only SELECT/WITH SQL'), immediately ruling out DML/DDL. This makes it easy to distinguish from sibling metadata tools like list_tables and describe_table.

  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?

  Clearly frames the tool as read-only and explains that the server was not started with --allow-write, so write attempts are not valid. It doesn't explicitly name the sibling tools as alternatives, but the intended context for running ad hoc read queries is clear.

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