Server Quality Checklist

Tool Scores

• analyze_database_schemaC
  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 mentions 'optional sample data' and 'max 5 rows per table' which provides some behavioral context, but doesn't cover important aspects like whether this is a read-only operation, performance implications, authentication requirements, rate limits, or what the analysis output format looks like.

  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 purpose and includes the optional sample data feature. Every word serves a purpose with no wasted text or redundancy.

  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 database analysis tool with no annotations and no output schema, the description is insufficient. It doesn't explain what the analysis output contains, how relationships are determined, what 'analyze' actually means operationally, or how this differs from the sibling tools. The context signals show this is a 3-parameter tool with 100% schema coverage, but the description doesn't compensate for the lack of behavioral and output information.

  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 documents all three parameters thoroughly. The description adds minimal value beyond the schema - it mentions 'optional sample data' which relates to 'includeSamples' parameter, but doesn't provide additional semantic context beyond what's in the parameter descriptions.

  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: analyzing database schema structure including tables, columns, indexes, and relationships, with optional sample data. It uses specific verbs ('analyze') and resources ('D1 database schema structure'), but doesn't explicitly differentiate from sibling tools like 'get_table_relationships' or 'validate_database_schema'.

  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 the sibling tools. It mentions 'optional sample data' but doesn't explain when to include samples versus when to use alternatives like 'suggest_schema_optimizations' or 'validate_database_schema' for different analysis needs.

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

• suggest_schema_optimizationsC
  2.9/5.0
  Behavior2/5

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

  With no annotations, the description carries full burden but provides minimal behavioral details. It mentions analysis and suggestions but doesn't disclose critical traits like whether it's read-only, requires specific permissions, has side effects, or how suggestions are formatted. This is inadequate for a tool with potential operational impact.

  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 concise and front-loaded in a single sentence, with no wasted words. It efficiently conveys the core purpose, though it could be slightly more structured by separating purpose from examples.

  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 complexity of schema optimization analysis, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, output format, and usage context, leaving significant gaps for an AI agent to understand how to invoke and interpret results effectively.

  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 the single parameter (environment). The description adds no additional parameter semantics beyond what the schema provides, such as examples of optimizations or how environment choice affects analysis. Baseline 3 is appropriate given high schema coverage.

  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 ('analyze') and resource ('schema'), and indicates the outcome ('suggest performance optimizations'). It distinguishes from siblings by focusing on performance rather than relationships or validation, though it doesn't explicitly name alternatives.

  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 guidance is provided on when to use this tool versus the sibling tools (analyze_database_schema, get_table_relationships, validate_database_schema). The description implies usage for performance analysis but lacks explicit context, prerequisites, or exclusions.

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

• get_table_relationshipsB
  3.1/5.0
  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. It mentions 'extract and analyze' but doesn't clarify what analysis entails, whether it's read-only or has side effects, performance implications, or output format. For a tool with no annotations, this leaves significant behavioral gaps.

  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 with zero waste. It's front-loaded with the core purpose and uses precise language. Every word earns its place, 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 moderate complexity (analyzing database relationships), no annotations, and no output schema, the description is minimally adequate. It states the purpose clearly but lacks details on behavior, output, or usage context. It meets the bare minimum for a read-oriented tool but doesn't fully compensate for missing structured data.

  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 documents both parameters thoroughly. The description adds no additional meaning beyond what the schema provides—it doesn't explain parameter interactions or usage nuances. Baseline 3 is appropriate when the schema does 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 tool's purpose with specific verbs ('extract and analyze') and resources ('foreign key relationships between tables in the database'). It distinguishes from siblings like 'analyze_database_schema' by focusing specifically on relationships rather than general schema analysis. However, it doesn't explicitly differentiate from all siblings like 'validate_database_schema' or 'suggest_schema_optimizations'.

  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 any of the sibling tools, nor does it specify use cases, prerequisites, or exclusions. The agent must infer usage from the purpose alone without explicit direction.

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

• validate_database_schemaB
  3.1/5.0
  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. It mentions what the tool does ('validate' and 'detect') but doesn't describe behavioral traits such as whether it's read-only, if it requires specific permissions, its performance impact, or what the output looks like (e.g., a report or error list). For a validation tool with zero annotation coverage, this is a significant gap.

  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 purpose ('Validate database schema integrity') and adds clarifying examples ('missing primary keys, orphaned foreign keys, etc.') without unnecessary details. Every word earns its place, making it appropriately sized 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 moderate complexity (validation with potential issues detection), no annotations, and no output schema, the description is minimally adequate. It explains the purpose but lacks details on behavior, output format, or usage context. With no output schema, the agent doesn't know what to expect in return, which is a notable gap for a validation tool.

  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 single parameter 'environment' well-documented in the schema itself (including enum values and description). The description adds no additional meaning about parameters beyond what the schema provides, so the baseline score of 3 is appropriate as the schema does 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 tool's purpose: 'Validate database schema integrity and detect potential issues' with specific examples like 'missing primary keys, orphaned foreign keys, etc.' It uses a specific verb ('validate') and resource ('database schema'), but doesn't explicitly distinguish it from sibling tools like 'analyze_database_schema' or 'suggest_schema_optimizations' which might have overlapping 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?

  The description provides no guidance on when to use this tool versus its siblings. It doesn't mention alternatives, prerequisites, or exclusions. The agent must infer usage from the tool name and description alone, which is insufficient given the presence of similar tools like 'analyze_database_schema' and 'suggest_schema_optimizations'.

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