Server Quality Checklist

Tool Scores

• execute_queryC
  2.1/5.0
  Behavior1/5

  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. 'Run a query to database' implies a potentially mutating operation (e.g., INSERT, UPDATE, DELETE) but doesn't specify if it's read-only, destructive, requires authentication, has rate limits, or what the output format is. This is a significant gap for a tool with no annotation coverage.

  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 'Run a query to database', which is front-loaded and wastes no words. It efficiently conveys the core action, though this brevity contributes to gaps in other dimensions.

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

  Completeness1/5

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

  Given the complexity (a database query tool with potential mutations), no annotations, no output schema, and 0% schema coverage, the description is incomplete. It doesn't address key aspects like safety, return values, or parameter details, making it insufficient for effective tool use.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, meaning parameters (db_type, connection_string, query) are undocumented in the schema. The description adds no meaning beyond the schema, failing to explain what these parameters do, their formats, or examples. For a tool with 3 parameters and low coverage, this is inadequate.

  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 'Run a query to database' states the action (run/execute) and resource (database query), which clarifies the basic purpose. However, it's vague about what type of query (e.g., SELECT, INSERT, UPDATE) and lacks distinction from sibling tools like get_columns or get_tables, which might also involve database queries but for specific purposes.

  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 (get_columns, get_tables) or specify contexts like executing arbitrary SQL versus retrieving metadata, leaving the agent with no usage instructions beyond the basic action.

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

• get_columnsC
  2.1/5.0
  Behavior1/5

  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. However, it only states the action without revealing any behavioral traits such as read-only vs. destructive nature, authentication needs, rate limits, or output format. This is inadequate for a tool that interacts with databases, where such details are critical.

  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 ('Get list of column in a table') that is front-loaded and avoids unnecessary words. However, it contains a grammatical error ('column' should be 'columns'), which slightly detracts from clarity but does not significantly impact conciseness.

  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 database interactions, lack of annotations, no output schema, and 0% schema description coverage, the description is incomplete. It does not address critical aspects like return values, error handling, or behavioral constraints, leaving significant gaps for an AI agent to understand and use the tool effectively.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters1/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  The schema description coverage is 0%, meaning parameters are undocumented in the schema. The description adds no meaning beyond the schema, as it does not explain what 'db_type', 'connection_string', or 'table_name' represent, their formats, or usage. With 3 parameters and no compensation in the description, this fails to provide necessary semantic context.

  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 ('Get list of column in a table'), which is clear but vague. It specifies the verb ('Get') and resource ('column in a table'), but lacks specificity about scope or differentiation from sibling tools like 'get_tables' (which likely lists tables rather than columns). However, it avoids tautology by not merely restating the name/title.

  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 does not mention sibling tools such as 'execute_query' or 'get_tables', nor does it specify prerequisites, exclusions, or contextual cues for selection. This leaves the agent without explicit direction on tool choice.

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

• get_tablesC
  2.4/5.0
  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 a read operation ('Get list'), which implies it's non-destructive, but doesn't cover permissions, rate limits, output format, or error handling. This is a significant gap for a tool that interacts with databases, making it inadequate for safe and effective use.

  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 that gets straight to the point without unnecessary words. However, the grammatical error ('table' vs. 'tables') slightly detracts from clarity, but it remains appropriately sized and front-loaded.

  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 database interactions, no annotations, no output schema, and 0% schema description coverage, the description is incomplete. It lacks details on behavior, parameters, output, and usage context, making it insufficient for an AI agent to reliably invoke this tool without additional assumptions or errors.

  Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

  Parameters2/5

  Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

  Schema description coverage is 0%, so the schema provides no parameter descriptions. The tool description adds no information about the parameters (db_type, connection_string), their meanings, or how they affect the operation. This leaves both parameters entirely undocumented, failing to compensate for the schema's lack of coverage.

  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 'Get list of table in database' clearly states the action (get/list) and resource (tables), but it's grammatically incorrect ('table' should be 'tables') and doesn't distinguish from sibling tools like 'get_columns' or 'execute_query'. It provides a basic purpose but lacks specificity about scope or differentiation.

  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 alternatives like 'get_columns' or 'execute_query'. The description implies it's for listing tables, but there's no explicit context, exclusions, or prerequisites mentioned, leaving the agent to infer usage based on tool names alone.

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