superset_dataset_get

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

No annotations are provided, so the description carries the burden. It clarifies the operation is a read-only 'get' and specifies that it returns a JSON string with dataset details. It does not disclose error behavior or permissions, but for a simple getter with this verb, the transparency is reasonable.

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 compact and well-structured: one-sentence purpose, an important note about prerequisites, and clearly labeled Args/Returns sections. Each line adds value without verbosity.

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 get-by-ID operation, the description provides the return format, the prerequisite, and parameter semantics. With an output schema present (though not detailed here) and no complex nested objects, this is sufficient context for correct invocation.

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?

Input schema has one required integer 'dataset_id' with no description. The description adds meaning by specifying it's an integer from the dataset_list result, explaining where to obtain the value. This compensates for the 0% schema description coverage.

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 uses a specific verb ('Get') and resource ('dataset'), explicitly listing what detailed information includes (columns, metrics, SQL). It distinguishes from sibling tool superset_dataset_list by stating 'detailed' and providing the prerequisite of using list first to obtain the ID.

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 explicitly instructs when to use this tool: if the ID is unknown, call superset_dataset_list first. This provides a clear prerequisite and implies using this tool only when the ID is known, effectively guiding tool selection.

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