superset_database_catalogs

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

No annotations are provided, so the description carries the disclosure burden. It discloses a key behavioral trait: not all engines support catalogs, with common examples. However, it does not explicitly state that the operation is read-only or what happens on unsupported engines (error vs empty).

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?

Two short paragraphs and an Args line; every sentence is informative. The main purpose is front-loaded, and the caveat is placed early.

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?

The tool is simple with one parameter and likely a straightforward output. The description covers purpose, engine support limitation, and parameter semantics. It doesn't need to explain return values because an output schema is present.

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 schema provides no description for database_id (0% coverage), but the description compensates with an Args section explaining it as 'Database connection ID.' This adds meaning beyond the raw integer type.

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 'List catalogs in a database' with a specific verb and resource, and distinguishes itself from sibling tools by focusing on catalogs (versus schemas or tables). The engine-support caveat further narrows its scope.

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?

It provides when-to-use guidance by limiting to engines that support catalogs, and gives when-not examples (PostgreSQL and MySQL). However, it does not explicitly reference alternative tools such as superset_database_schemas or superset_database_tables, so it lacks explicit alternatives.

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