Server Quality Checklist

Tool Scores

• describe_tableA
  4.1/5.0
  Behavior3/5

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

  The description discloses the core behavior (what metadata it returns) but goes little beyond that. No annotations are provided, and it does not mention error handling, schema-qualified name resolution, or whether it accesses system catalogs. Adequate but minimal for a simple read-only 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 sentences, front-loaded with the purpose and followed by a usage directive. Every word earns its place; there is no redundancy or filler.

  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 tool with one parameter, no annotations, and no output schema, the description is complete. It states exactly what the tool returns (columns, types, nullability, comments) and when to use it, which is sufficient 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 already describes the 'table' param fully with an example. The description adds only that it applies to 'table or view', which is a minor clarification. Since schema coverage is 100%, the description does not need to compensate, but it also does not add significant semantic value.

  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's purpose with a specific verb ('Show') and resource ('columns, types, nullability and column comments for one table or view'). This distinguishes it from siblings like list_tables and run_query, which serve different functions.

  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 explicit when-to-use guidance: 'Call this before writing a query against a relation you have not queried before.' It does not mention alternatives or exclusions, but the context is clear enough for an agent to decide when to invoke it.

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

• list_tablesA
  4.2/5.0
  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 adds that the tool is 'cheap' and 'tells you what exists,' which are useful traits. However, it does not mention potential limits (e.g., pagination, schema coverage), auth requirements, or any side effects. For a read-only listing tool, the disclosed behavior is adequate but not comprehensive.

  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 included objects, and the second provides a clear usage directive. Every word contributes value, and the structure is front-loaded with the primary function.

  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 tool's simplicity (no parameters, no output schema), the description is sufficiently complete. It explains what the tool returns (tables with descriptions), when to use it (first), and why (cheap). It does not describe the return format in detail, but that is less critical for a discovery tool whose primary purpose is inventorying available data assets.

  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 baseline is 4. The description does not need to explain parameters, and it correctly focuses on the tool's purpose and output scope. No additional parameter detail is needed.

  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's function: listing every table, view, and materialized view in the mart schema(s) along with descriptions. The phrase 'Call this first' distinguishes it from siblings by positioning it as an initial discovery step, contrasting with describe_table (for specific tables) and run_query (for arbitrary queries).

  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 advises to call this tool first because it is cheap and reveals what exists. This provides clear usage context, though it does not explicitly mention alternatives or when not to use it. The sibling tool names imply that describe_table is for deeper details and run_query for specific queries, but this is not stated.

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

• run_queryA
  4.9/5.0
  Behavior5/5

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

  With no annotations provided, the description carries the full burden. It discloses read-only behavior, allowed statement types, single-statement restriction, default and maximum row caps, and advises against pulling rows for counting. This is rich behavioral disclosure far beyond simple 'runs a query'.

  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?

  Three sentences, front-loaded with the core purpose, followed by constraints and best-practice advice. No filler or redundancy; every sentence adds necessary information.

  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's complexity (SQL query execution), the description covers return format (JSON), allowed syntax, single-statement rule, and row limits. Sibling tools are metadata-oriented, so this is complete for selecting and invoking the tool. No output schema or annotations exist, but the description sufficiently covers what the agent needs to know.

  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 coverage is 100%, so baseline is 3. The description adds value by explaining the default row cap (200), the absolute max (5000), and the rationale for using SQL-side aggregation, which complements the schema's limit parameter and sql description.

  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 clearly states a specific verb ('Run') and resource ('a read-only SQL SELECT against the warehouse') with a concrete outcome ('return rows as JSON'). It distinguishes itself from siblings (list_tables/describe_table) by being the data-query tool rather than a metadata tool.

  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 constraints: only SELECT/WITH...SELECT, single statement, row caps, and guidance to aggregate in SQL instead of pulling raw rows. This clearly tells the agent when to use the tool and what to avoid, effectively differentiating from metadata-only sibling tools.

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