Server Quality Checklist

Tool Scores

• query_mssqlA
  3.5/5.0
  Behavior3/5

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

  Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=false, and idempotentHint=false. The description adds the read-only mode context ('只读模式'), which reinforces but doesn't significantly expand beyond annotations. It doesn't disclose additional behavioral traits like rate limits, authentication needs beyond parameters, or error handling.

  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 in Chinese that directly states the tool's purpose and key constraint ('只读模式'). It's front-loaded with no unnecessary words, making it highly concise and well-structured.

  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 tool's complexity (database querying with 6 required parameters), annotations cover safety aspects (read-only, non-destructive), but there's no output schema. The description is minimal and doesn't explain return values, error cases, or connection behavior. It's adequate but lacks depth for a tool with significant operational context.

  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 all parameters well-documented in the input schema. The description doesn't add meaningful parameter semantics beyond what's already in the schema, such as format examples or constraints. Baseline 3 is appropriate since the schema carries the full burden.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the action ('执行MSSQL数据库查询') and resource ('MSSQL数据库'), specifying it's for read-only operations. It distinguishes from siblings by mentioning MSSQL specifically, though it doesn't explicitly contrast with other database query tools like query_mysql or query_oracle.

  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 usage for MSSQL database queries in read-only mode, but doesn't provide explicit guidance on when to use this tool versus alternatives like query_mysql or query_oracle. No exclusions or prerequisites are mentioned beyond the read-only constraint.

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

• query_mysqlA
  3.5/5.0
  Behavior3/5

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

  The description adds value beyond annotations by specifying '只读模式' (read-only mode), which aligns with the readOnlyHint=true annotation. However, it doesn't provide additional behavioral context such as connection handling, timeout behavior, result format, or error conditions. With annotations covering safety (readOnlyHint=true, destructiveHint=false), the description meets the lower bar but doesn't enrich understanding significantly.

  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 extremely concise with a single sentence that efficiently communicates the core purpose and constraint. It's front-loaded with no wasted words, making it easy for an AI agent to parse quickly. Every part of the sentence earns its place by specifying the action, target, and operational mode.

  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 tool's complexity (6 required parameters for database connection and query execution), the description is minimal. While annotations provide safety information (readOnlyHint=true, destructiveHint=false) and the schema fully documents parameters, there's no output schema and the description doesn't explain what the tool returns (e.g., result sets, error formats). For a database query tool, this leaves gaps in understanding the complete behavior.

  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 description doesn't add any parameter-specific information beyond what's already in the input schema, which has 100% description coverage. It mentions 'MySQL数据库查询' (MySQL database query) but doesn't explain individual parameters like host, port, or querySql. With high schema coverage, the baseline score of 3 is appropriate as the schema carries the full burden of parameter documentation.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the verb ('执行' - execute) and resource ('MySQL数据库查询' - MySQL database query), and specifies the operational mode ('只读模式' - read-only mode). It distinguishes from siblings by mentioning MySQL specifically, though it doesn't explicitly contrast with other database types like MSSQL, Oracle, or PostgreSQL.

  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 usage context by specifying '只读模式' (read-only mode) and the input schema further clarifies that SQL queries should be '仅支持SELECT等只读操作' (only support SELECT and other read-only operations). However, it doesn't explicitly state when to use this tool versus the sibling database tools (query_mssql, query_oracle, query_postgresql), nor does it provide any exclusion criteria beyond the read-only constraint.

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

• query_postgresqlA
  3.5/5.0
  Behavior3/5

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

  Annotations already declare readOnlyHint=true, destructiveHint=false, etc., covering safety aspects. The description adds the read-only mode context ('只读模式') and specifies SQL query constraints ('仅支持SELECT等只读操作'), which provides useful behavioral context beyond annotations, though it doesn't detail rate limits, error handling, or output format.

  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 in Chinese that directly states the tool's purpose and key constraint ('只读模式'). It's front-loaded with no unnecessary words, making it highly concise and well-structured.

  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 tool's complexity (6 required parameters for database queries) and lack of output schema, the description is adequate but minimal. It covers the read-only nature and PostgreSQL focus, but doesn't explain return values, error cases, or connection handling, leaving gaps for an AI agent to infer.

  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 fully documents all 6 parameters. The description doesn't add any parameter-specific semantics beyond what's in the schema, such as format details or examples. Baseline score of 3 is appropriate as the schema handles the heavy lifting.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the action ('执行PostgreSQL数据库查询') and resource ('PostgreSQL数据库'), specifying it's for read-only operations. It distinguishes from siblings by mentioning PostgreSQL specifically, though it doesn't explicitly contrast with other database types like MySQL or Oracle.

  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 usage for PostgreSQL read-only queries but doesn't provide explicit guidance on when to use this tool versus the sibling tools (query_mssql, query_mysql, query_oracle). No alternative tools or exclusions are mentioned beyond the read-only constraint.

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

• query_oracleA
  3.8/5.0
  Behavior4/5

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

  Annotations already provide readOnlyHint=true, destructiveHint=false, openWorldHint=false, and idempotentHint=false. The description adds valuable context by specifying '只读模式' (read-only mode) and implying Oracle-specific behavior. While it doesn't detail rate limits, authentication needs beyond parameters, or result formats, it usefully reinforces the read-only constraint beyond what annotations alone convey.

  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 in Chinese: '执行Oracle数据库查询（只读模式）'. It's front-loaded with the core purpose and includes the critical 'read-only mode' qualification. There's zero wasted verbiage or redundant information.

  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 database query tool with 6 parameters, 100% schema coverage, and annotations covering safety (readOnlyHint=true, destructiveHint=false), the description is reasonably complete. It specifies the database type (Oracle) and read-only mode. The main gap is lack of output schema, but the description doesn't need to explain return values. It could better differentiate from sibling tools but covers essential context.

  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 all 6 parameters well-documented in the input schema (e.g., host, port, user, pwd, db, querySql). The description adds no additional parameter information beyond what's in the schema. With complete schema coverage, the baseline score of 3 is appropriate as the description doesn't need to compensate for gaps.

  Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

  Purpose4/5

  Does the description clearly state what the tool does and how it differs from similar tools?

  The description clearly states the tool's purpose as '执行Oracle数据库查询（只读模式）' which translates to 'Execute Oracle database query (read-only mode)'. This specifies both the verb (execute query) and resource (Oracle database), and distinguishes it from non-database tools. However, it doesn't explicitly differentiate from sibling database query tools (query_mssql, query_mysql, query_postgresql) beyond specifying Oracle.

  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 usage context through '只读模式' (read-only mode) and the input schema's querySql description specifies '仅支持SELECT等只读操作' (only supports SELECT and other read-only operations). However, there's no explicit guidance on when to use this tool versus the sibling database tools, nor any mention of prerequisites or alternative scenarios.

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