Superset MCP Integration

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

No annotations are provided, so the description carries full burden. It states the tool 'check[s] if the provided SQL is valid' but doesn't disclose behavioral traits like whether this is a read-only operation (implied by 'validate'), potential side effects (e.g., if validation runs queries), authentication needs, rate limits, or error handling. The description is minimal and misses key operational details 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.

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

The description is appropriately sized and front-loaded: the first sentence states the core purpose clearly. The subsequent sentences add endpoint and parameter details without redundancy. It uses a structured format with 'Args:' and 'Returns:' sections, though the return description is vague ('A dictionary with validation results'). Overall efficient with minimal waste.

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?

Given no annotations, 0% schema coverage, and no output schema, the description is incomplete. It covers basic purpose and parameters but lacks behavioral context (e.g., safety, auth), detailed usage guidelines, and specifics on return values. For a validation tool with 2 parameters and no structured support, more comprehensive information is needed to guide an AI agent effectively.

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?

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds basic semantics: 'database_id: ID of the database' and 'sql: SQL query to validate', which clarifies what each parameter represents. However, it doesn't provide format details (e.g., SQL dialect, database ID source) or constraints, leaving gaps. With 2 parameters and some value added, a baseline 3 is appropriate.

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 clearly states the tool's purpose: 'Validate arbitrary SQL against a database' with specific verbs ('validate', 'check') and resources ('SQL', 'database'). It distinguishes from siblings like superset_database_test_connection (connection testing) and superset_sqllab_execute_query (actual execution), though not explicitly named. However, it doesn't fully differentiate from superset_database_validate_parameters (parameter validation), which is a minor gap.

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?

No explicit guidance on when to use this tool versus alternatives. It mentions the endpoint but doesn't specify scenarios like pre-execution validation, syntax checking, or when to choose this over other validation tools like superset_database_validate_parameters. The description lacks context about prerequisites or typical use cases.

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