superset_database_validate_sql

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 explicitly states that SQL is not executed, and it discloses the engine-support limitation. However, it does not describe error behavior for unsupported engines, authentication needs, or other potential side effects, so the transparency is good but not exhaustive.

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

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

The description is appropriately concise: a one-sentence purpose, a brief IMPORTANT caution, and a compact Args list. Every sentence earns its place, and the most critical information is front-loaded.

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

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

For a validation tool with three parameters and an existing output schema, the description covers the core purpose, parameter semantics, and a key compatibility caveat. It does not explain the exact return format or error handling, but the output schema likely covers the return value, making this adequate for the tool's complexity.

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

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

The input schema provides only types and no descriptions for database_id, sql, or schema. The description compensates fully by listing each parameter with a clear meaning (e.g., 'Database connection ID', 'SQL query to validate', 'Schema for validation context') and even includes an example value for schema. This adds critical meaning beyond the schema.

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

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

The description opens with a specific action: 'Validate SQL query syntax without executing it (EXPLAIN-like check).' This clearly identifies what the tool does and distinguishes it from sibling tools like superset_sqllab_execute (which executes) and superset_database_validate_parameters (which validates connection parameters).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear usage context by stating the tool validates without executing and explicitly warns that not all database engines support SQL validation (with PostgreSQL cited as supporting). This implies when to use it, but it does not explicitly name alternative tools or provide concrete when-not-to-use exclusions beyond the engine caveat.

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