superset_list_datasets

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

With no annotations, the description carries the burden. It implies a read-only listing operation but does not disclose pagination, response format, access restrictions, or ordering behavior. It adds minimal behavioral context beyond the obvious list action.

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 two crisp sentences, front-loaded with the primary purpose, and includes a clear use case. Every word earns its place with no redundancy or filler.

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 simple list tool with two optional parameters and an output schema, the description is nearly complete. It covers purpose, filters, and a concrete use case. However, it could be improved by explicitly distinguishing from superset_list_all_datasets and clarifying any response limitations.

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%, but the description adds meaning to the two parameters: 'filter by database_id or search by name.' This goes beyond the schema, but it does not explain matching behavior (case sensitivity, wildcards) or any interplay between the filters, leaving gaps.

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 verb 'List' and resource 'datasets (tables/views)' in Superset, and the optional filters differentiate it from siblings like superset_list_all_datasets and superset_get_dataset. It's specific and unambiguous.

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 context by stating 'Use to find dataset_id for creating charts,' which implies when to use this tool. However, it does not explicitly name alternatives or state when not to use it, such as when an unfiltered list or a single dataset is needed.

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