Superset MCP Integration

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 the API endpoint and return format, but lacks details on authentication needs, rate limits, error handling, or whether it's a read-only operation. For a tool with zero annotation coverage, this is insufficient to fully inform the agent about its behavior.

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 well-structured and concise, with a clear purpose statement, endpoint details, and parameter/return explanations in separate sections. It avoids redundancy and uses minimal sentences to convey essential information, though the endpoint detail could be considered slightly verbose for a tool description.

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 the tool's low complexity (1 parameter, no output schema, no annotations), the description is moderately complete. It covers the basic purpose, parameter, and return format, but lacks behavioral details like authentication or error handling. Without annotations or output schema, it provides a baseline but misses some contextual depth needed for optimal agent use.

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 description adds meaningful context for the single parameter 'database_id' by explaining it's the 'ID of the database', which clarifies its purpose beyond the schema's basic type (integer). With 0% schema description coverage and only one parameter, this compensation is effective, though it doesn't detail format constraints (e.g., valid ID ranges).

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: 'Get a list of tables for a given database.' It specifies the verb ('Get') and resource ('tables'), and distinguishes it from siblings like 'superset_database_get_catalogs' or 'superset_database_schemas' by focusing on tables. However, it doesn't explicitly differentiate from potential similar tools beyond the name, keeping it at a 4 rather than a 5.

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 no guidance on when to use this tool versus alternatives. It mentions the endpoint but doesn't compare it to siblings like 'superset_database_list' or 'superset_database_get_by_id', nor does it specify prerequisites or exclusions. This lack of contextual advice limits its utility for an AI agent.

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