superset_dataset_refresh_schema

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

No annotations are provided, so the description must carry the transparency burden. It discloses the action (rescan columns and types) and the return type (JSON string). However, it does not mention side effects, permission requirements, or potential failure modes. This is minimal but not misleading.

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 concise and well-structured: a clear one-sentence purpose, a usage note, and a simple args/returns section. Every sentence adds useful information without unnecessary fluff.

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 tool with a single integer parameter and an output schema, the description covers the purpose, when to use it, and the return type. It lacks details on errors or prerequisites, but it is sufficiently complete for the tool's low complexity.

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%, and the description only says 'dataset_id: Dataset ID,' which adds no meaning beyond the parameter name and schema type. Since there is only one parameter, the gap is small, but the description does not compensate for the missing schema descriptions.

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 function: 'Refresh the dataset schema from the source (rescan columns and types).' This uses a specific verb and resource, and it is distinct from sibling tools like superset_dataset_get or superset_dataset_update.

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?

Provides explicit usage context: 'Useful after ALTER TABLE or any structural change to the underlying table.' This tells the agent when to invoke this tool, though it does not explicitly mention alternatives or exclusions. The context is clear enough to guide selection.

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