Server Quality Checklist

Tool Scores

• lookupA
  3.5/5.0
  Behavior3/5

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

  The description discloses the use of LIKE for fuzzy search and a 100-record limit. However, it does not mention that if no field is specified, all text fields are searched (only in schema), nor does it indicate case sensitivity or potential performance implications on large tables.

  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, clear sentence that efficiently conveys the tool's purpose and key constraint. It is front-loaded with the verb and resource, with no unnecessary information.

  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?

  Given the absence of an output schema, the description could explain the return format or fields. It only mentions 'up to 100 records,' leaving details like column names or ordering unspecified. It is adequate but not comprehensive.

  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?

  All parameters are described in the input schema (100% coverage). The tool description adds no additional meaning beyond the schema's parameter descriptions, meeting the baseline for a tool with comprehensive schema documentation.

  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 purpose: fuzzy search (LIKE) by keyword in a specified TABLE or VIEW, with a maximum return of 100 records. It distinguishes from sibling tools like list_databases and list_tables which are listing tools, and query_sql which allows arbitrary SQL queries.

  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?

  No explicit guidance on when to use this tool versus alternatives, especially query_sql. There is no mention of conditions where query_sql would be more appropriate, such as for exact matches or complex queries.

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

• list_databasesA
  4.1/5.0
  Behavior3/5

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

  No annotations provided, so description carries full burden. '列出' implies a read-only operation, which is accurate. However, it does not disclose any potential side effects, required permissions, or rate limits, though for a simple list tool these are less critical.

  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?

  Single clear sentence that fully describes the tool's function without any unnecessary words. Front-loaded with the action and resource.

  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 list operation with no parameters and no output schema, the description is complete. It states exactly what the tool returns: a list of database connection names configured in the MCP service.

  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?

  Tool has zero parameters, so description naturally adds no parameter details. Schema coverage is 100% (empty properties). Baseline for 0 params is 4; no further elaboration 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?

  Description uses specific verb '列出' (list) and resource '所有資料庫連線名稱' (all database connection names). It clearly distinguishes from siblings like list_tables (which lists tables within a database) and query_sql (which runs queries).

  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?

  No explicit guidance on when to use this tool versus alternatives. However, its simplicity makes the usage context clear: use to enumerate available databases before querying tables or running SQL. Sibling names imply differentiation but no direct comparison.

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

• list_tablesA
  4.3/5.0
  Behavior4/5

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

  No annotations are provided, so the description carries the full burden. It clearly indicates a read-only listing operation with no destructive side effects, but does not discuss rate limits, performance, or other potential behaviors. The description is accurate and non-contradictory.

  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 conveys all essential information without wasted words.

  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 (one optional parameter, no output schema), the description covers the core functionality: what it lists and the details included. It could optionally mention that results are returned as a list but is sufficient for the agent to understand the output.

  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 100% for the single parameter, and the description adds valuable context: it explains that 'database' is a connection name, suggests using list_databases to get options, and notes it can be omitted if only one connection exists.

  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 it lists all TABLEs and VIEWs in a specified database, including column details, differentiating it from siblings like list_databases (lists databases) and query_sql (executes queries).

  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 use for schema exploration but does not explicitly state when to use it versus alternatives or provide exclusion criteria. Context from sibling tools suggests using list_databases first, but this is not mentioned.

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

• query_sqlA
  4.4/5.0
  Behavior4/5

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

  With no annotations, the description clearly states the tool is read-only (SELECT only) and enforces mutation prohibition. It could be improved by mentioning potential performance impacts or result set size, but the core safety behavior is well disclosed.

  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 efficiently conveys the core purpose and restrictions. Every word 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?

  The description covers allowed operations, the need for a database connection, and how to obtain it via list_databases. While it doesn't explicitly state the return format, it's implied for SELECT queries. A warning about potential long-running queries would improve completeness.

  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 coverage is 100%, with both parameters described in the schema. The description adds little beyond the schema, mainly reinforcing the SELECT-only constraint already present in the schema description. Baseline 3 is appropriate.

  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: executing free SELECT statements on a specified database. It explicitly restricts usage to SELECT only and prohibits mutation syntax, distinguishing it from sibling tools that list databases or tables.

  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?

  The description explicitly states when to use the tool (for arbitrary SELECT queries) and when not (only SELECT allowed, no INSERT/UPDATE/DELETE). It also references using list_databases to get available database connections, providing clear context for tool selection.

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