Server Quality Checklist

Tool Scores

• analyze_tableC
  2.6/5.0
  Behavior2/5

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

  No annotations are provided, so the description carries the full burden of behavioral disclosure. The description mentions 'collect statistics information' but doesn't specify what statistics are collected (e.g., row count, column distributions, indexes), whether this is a read-only operation, performance implications, or output format. For a tool with no annotation coverage, this leaves critical behavioral traits undocumented, though it doesn't contradict any annotations.

  Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

  Conciseness4/5

  Is the description appropriately sized, front-loaded, and free of redundancy?

  The description is a single, efficient sentence: 'Analyze table to collect statistics information'. It's front-loaded with the core action and outcome, with no wasted words. While it could be more detailed for better tool selection, it's appropriately concise for its length, earning a high score for structure and brevity.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given the tool's complexity (analysis operation with 2 parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain what 'statistics information' entails, how results are returned, or behavioral aspects like performance. With no structured fields to compensate, the description should provide more context to ensure the agent can use the tool effectively, but it falls short.

  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 has 100% description coverage, with clear documentation for 'schema' and 'table' parameters. The description doesn't add any parameter-specific semantics beyond what the schema provides, such as examples or constraints. However, with high schema coverage, the baseline score is 3, as the schema adequately documents parameters without needing extra description details.

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

  Purpose3/5

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

  The description states the tool's purpose as 'Analyze table to collect statistics information', which provides a clear verb ('analyze') and resource ('table') with a general outcome ('collect statistics information'). However, it doesn't differentiate from sibling tools like 'execute_sql' or 'get_execution_plan', leaving ambiguity about when to use this specific analysis tool versus executing SQL queries directly. The purpose is understandable but lacks specificity for tool selection.

  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 provides no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'execute_sql' or 'get_execution_plan', nor does it specify contexts where table analysis is preferred over direct SQL execution or plan retrieval. Without any usage context or exclusions, the agent must infer when this tool is appropriate, which could lead to incorrect tool selection.

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

• execute_sqlC
  2.9/5.0
  Behavior2/5

  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 but offers minimal information. It doesn't address critical aspects such as whether the query is read-only or mutating data, authentication needs, rate limits, error handling, or the format of results. The description merely states what the tool does without revealing operational traits.

  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 directly conveys the tool's function without unnecessary words. It is front-loaded with the core action and resource, making it easy to understand at a glance. Every part of the sentence earns its place by defining the tool's purpose clearly.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  For a tool that executes SQL queries with no annotations and no output schema, the description is insufficient. It lacks details on behavioral aspects like data mutation risks, result formats, error conditions, and usage constraints. Given the complexity of SQL execution and the absence of structured data to compensate, the description does not provide enough context for safe and effective use.

  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 has 100% description coverage, with the 'sql' parameter documented as 'The SQL to Execute'. The description adds no additional meaning beyond this, such as SQL dialect specifics, query length limits, or supported operations. Given the high schema coverage, a baseline score of 3 is appropriate as the schema handles parameter documentation adequately.

  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 ('Execute a SQL Query') and target resource ('on the Redshift cluster'), making the purpose unambiguous. It distinguishes from siblings like 'analyze_table' and 'get_execution_plan' by focusing on direct query execution rather than analysis or planning operations.

  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 is provided on when to use this tool versus alternatives. While the description implies it's for executing SQL queries, it doesn't specify scenarios where 'analyze_table' or 'get_execution_plan' might be more appropriate, nor does it mention prerequisites like database permissions or connection requirements.

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

• get_execution_planC
  2.9/5.0
  Behavior2/5

  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 states the tool retrieves an execution plan with runtime statistics, which suggests a read-only, analytical operation, but doesn't clarify permissions, performance impact, data returned format, or any side effects. This is inadequate for a tool that likely interacts with a database system.

  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 core functionality ('Get actual execution plan with runtime statistics') and specifies the target ('for a SQL query'). There is zero waste, making it highly concise and well-structured for quick comprehension.

  Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

  Completeness2/5

  Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

  Given no annotations and no output schema, the description is incomplete for a tool that analyzes SQL queries. It lacks details on behavioral traits (e.g., read-only nature, performance implications), output format, and differentiation from siblings. This leaves significant gaps for an agent to understand the tool's full context and usage.

  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 the single parameter 'sql' documented as 'The SQL query to analyze'. The description adds no additional meaning beyond this, such as SQL dialect requirements, query length limits, or syntax specifics. Baseline 3 is appropriate as the schema handles parameter documentation adequately.

  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 with a specific verb ('Get') and resource ('execution plan with runtime statistics'), and specifies the target ('for a SQL query'). It doesn't explicitly differentiate from sibling tools like 'execute_sql' or 'analyze_table', but the focus on 'actual execution plan with runtime statistics' implies analytical rather than execution functionality.

  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 like 'execute_sql' or 'analyze_table' is provided. The description implies usage for SQL query analysis but doesn't specify contexts, prerequisites, or exclusions, leaving the agent to infer appropriate scenarios.

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