Server Quality Checklist

Tool Scores

• query_tableA
  3.5/5.0
  Behavior3/5

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

  With no annotations, the description carries the full behavioral burden. It usefully discloses one significant trait: all results pass through the KVKK/GDPR gateway with sensitive fields auto-masked. However, it omits other relevant behaviors such as the read-only nature of the query, permission requirements, error handling, or what happens to results when the gateway limit is reached.

  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: the first states the core purpose and the second adds the essential gateway behavior. Purpose is front-loaded, with no filler 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?

  The definition is adequate for basic invocation: required table parameter, optional filter, and limit are documented, and the masking behavior is disclosed. But there is no output schema, and the description does not explain the return shape of rows or how the gateway limit affects result truncation, leaving moderate gaps for a tool with no annotation safety net.

  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 parameters are already documented: table, filter, and limit. The main description adds little beyond the schema; it echoes 'optional filters' and provides gateway-related context, but no new per-parameter meaning.

  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 operation ('Query rows') and resource ('from a database table'), with optional filters. This verb- and resource-level detail unambiguously separates it from siblings like list_tables, describe_table, and gateway_status.

  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 implies use for row retrieval but provides no explicit guidance on when to use it versus the listed siblings, and no exclusions or alternative conditions. There is no mention of when not to use query_table, leaving the agent to infer the boundary from the sibling names.

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

• describe_tableA
  4/5.0
  Behavior3/5

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

  With no annotations provided, the description carries the full behavioral disclosure burden. 'Get' strongly implies a read-only metadata operation, and 'gateway masking policy' clarifies the nature of the returned information. However, it does not disclose permission behavior, error cases, or any side effects, leaving some ambiguity.

  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 action and resource, then adds the purpose. Every word contributes meaning, with no fluff or repetition.

  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 one-parameter metadata tool with no output schema, the description adequately conveys what is returned (column names and gateway masking policy) and why it is useful. It could be more complete by explicitly addressing permissions or differentiating from siblings, but those are minor gaps given the tool's simplicity.

  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 the single 'table' parameter as 'Table name'. The description adds little beyond restating that the operation is for a table, so it does not significantly improve parameter understanding.

  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 ('Get') and clearly identifies the resource: column names and gateway masking policy for a table. It also states the intended purpose—helping the LLM understand data access—which distinguishes it from siblings like query_table and list_tables.

  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 clear context for when to use the tool: when the LLM needs to understand what data it can access, including column names and masking policy. It does not explicitly name alternatives or state when not to use it, but the intended use case is evident.

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

• gateway_statusA
  4.2/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the behavioral burden. 'Show' clearly indicates a read-only operation, and the description discloses what content will be displayed. It does not mention authentication or output format, but those are less critical for a zero-parameter status read.

  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?

  A single, well-front-loaded sentence that contains no filler. Every phrase adds informational value.

  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 zero-parameter status tool, the description adequately covers purpose and content. It could mention whether the output is formatted as a summary or detailed report, but the core usage context is clear given the tool's simplicity.

  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?

  There are zero parameters, so parameter-level semantics are not needed. The description meaningfully explains what the tool reports, making the lack of parameters a non-issue.

  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 names a specific verb ('Show') and resource ('active gateway configuration'), and lists concrete contents (field masking rules, table policies, audit settings). It clearly stands apart from the table-oriented sibling tools.

  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 this tool is for inspecting gateway configuration rather than querying or describing tables, but it does not explicitly state when to choose this tool over siblings or mention any exclusions.

  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
  Behavior4/5

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

  With no annotations provided, the description carries the full behavioral disclosure burden. It does disclose an important behavioral trait—deny-marked tables are omitted from results—and 'List' implies a read-only operation. It stops short of detailing return format or permissions, but for a simple listing tool this is solid.

  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 that are front-loaded and contain zero filler. The main action is stated first, followed by a single relevant policy caveat.

  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 zero-parameter list tool with a simple purpose, the description is nearly complete: it states what is listed and the visibility rule. The only minor omission is an explicit statement of the return shape, though 'List' strongly implies a list of table names.

  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 input schema has zero parameters and 100% schema-description coverage by default, so there is no parameter burden for the description to carry. Baseline 4 is appropriate for a no-parameter tool.

  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 the verb 'List' and the resource 'available database tables', and adds a precise policy restriction: tables marked 'deny' are omitted. This makes it easily distinguishable from query_table, describe_table, and gateway_status.

  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 tool's intended use is implied: call it when you need an inventory of accessible database tables. However, it does not explicitly contrast with siblings like describe_table or query_table, nor does it state when this tool should not be used.

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