Server Quality Checklist

Tool Scores

• list_tablesA
  4.3/5.0
  Behavior3/5

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

  No annotations are provided, so the description carries the burden of behavioral disclosure. It specifies the output (list of tables with description and row count) and notes 'No SQL is required,' implying a read-only metadata operation. However, it does not explicitly state that the operation is read-only or side-effect-free, nor does it mention any authentication or performance considerations, which are minor for a simple listing 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?

  The description is two concise sentences. The first sentence states the action and output, and the second provides usage context. No filler words or redundancies exist, and the most important information (what it does) is front-loaded.

  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 the tool has no parameters, no output schema, and a simple, self-contained purpose, the description is complete. It tells the agent exactly what it will receive (tables, descriptions, row counts) and when to call it. Nothing critical is missing for effective use.

  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, and the schema coverage is trivially 100%. Per the baseline rule for 0-parameter tools, a score of 4 is appropriate. The description adds value by explaining what the tool outputs, which fully compensates for the absence of parameters.

  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 lists all tables with a short description and row counts. It also differentiates itself from siblings by saying 'Use this first when you do not know the schema, before writing any SQL,' which implies it is a schema-discovery tool distinct from describe_table (specific table details) and read_query (SQL execution).

  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 states when to use it ('when you do not know the schema' and 'before writing any SQL'), providing clear contextual guidance. It does not name alternative tools explicitly, but the context strongly implies that after gaining schema knowledge, one would use read_query or describe_table, which is sufficient for minimal guidance.

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

• describe_tableA
  4.8/5.0
  Behavior4/5

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

  Since annotations are absent, the description carries full burden. It discloses the return content (columns, flags, foreign keys) and error behavior for invalid input. While it doesn't explicitly state it is read-only, the non-destructive nature is strongly implied by 'describe' and the absence of any mutating language. It could have been 5 if it explicitly said 'performs no data modification', but the current disclosure is sufficient for safe invocation.

  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 three concise sentences with zero filler: the first states the purpose and output, the second gives usage context, and the third constrains input and defines error behavior. It is front-loaded with the most critical information and every sentence earns its place.

  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 simple tool with one parameter and no output schema, the description is complete: it covers what it does, when to use it, how to choose the parameter, and error handling. An agent has everything needed to call it correctly without additional inference. No behavioral annotations exist, but the description compensates fully for their absence.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters5/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema coverage is 0% and the only parameter has no description beyond its title, so the description adds significant value by explaining that the table_name must come from list_tables and that unknown names cause an error. This goes beyond the schema and directly helps the agent select a valid value, making the parameter's semantics fully clear.

  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 explicitly states the verb 'describe' and the resource 'structure of one table', then lists the exact components (columns with flags, foreign keys). It clearly distinguishes itself from siblings by positioning it as the follow-up to list_tables and a prerequisite for writing SQL, while read_query is for actual data retrieval.

  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?

  It gives explicit when-to-use context ('Use this after list_tables to understand the schema before writing SQL') and even instructs that the table name must come from list_tables. It also preempts misuse by stating unknown names produce a clear error, leaving no ambiguity about prerequisites or error handling.

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

• read_queryA
  4.9/5.0
  Behavior5/5

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

  No annotations provided, so description carries full burden. It discloses that the database is opened read-only (writes impossible), rejects multi-statement SQL and all DML/DDL/PRAGMA, and details the output structure with truncation semantics. This is a model of behavioral transparency 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 dense but perfectly organized: operation definition, supported features, prerequisite guidance, server rules, result format, and truncation handling. Every sentence adds critical information with no redundancy. Front-loads the core purpose and essential constraints, making it easy 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?

  Covers everything an agent needs to call this tool correctly: allowed SQL types, supported clauses, schema discovery prerequisite, server-side restrictions, read-only guarantee, output format, truncation behavior, max_rows default, and remediation advice. With no output schema, the description provides a complete picture, making it highly complete for a complex 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?

  Schema description coverage is 0%, so the description must add meaning. It explains the sql parameter implicitly (the SQL statement to execute) and mentions max_rows with its default and effect on truncation. While not a dedicated parameter-by-parameter breakdown, it effectively conveys the purpose and impact of both parameters, going well beyond the bare 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?

  The description states a specific verb (Execute), resource (read-only SQL statement against the shop database), and explicitly enumerates allowed SQL constructs (SELECT, WITH ... SELECT, JOIN, GROUP BY, etc.). This clearly distinguishes it from sibling tools list_tables and describe_table, which are schema introspection rather than data querying.

  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?

  Provides explicit when-to-use vs. alternatives: 'If you do not know the schema yet, call list_tables and describe_table first.' Also states constraints (one statement per call, no modification statements) and practical advice on handling truncation (refine query with LIMIT/WHERE/aggregation). This leaves no ambiguity about when and how to use the tool.

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