set_dataset_description

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

With no annotations provided, the description carries the full burden. It discloses that the operation updates/mutates the dataset catalog and describes the return format. However, it does not mention permissions, reversibility, or edge cases such as empty description strings.

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 with a summary line, an optional benefit note, an Args section, a Returns section, and a concrete example. It is compact, readable, and every part adds value.

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 low complexity (two simple string parameters) and the presence of an output schema, the description is complete. It explains purpose, parameters, return value, and demonstrates usage with an example.

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 input schema provides only field names with no descriptions (0% schema coverage). The tool description compensates fully by explaining that dataset_rid is the RID of the dataset to update and description is the new description text. This is sufficient and accurate for both parameters.

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 ('Set or update') and an explicit resource ('the description for a dataset'), clearly distinguishing it from sibling tools like set_table_description or set_column_description. It also states the effect ('Updates the dataset's description in the catalog').

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 on when to use the tool: when you need to set or update a dataset's description. It does not explicitly mention alternatives or exclusions, but the resource is unambiguous and the example reinforces the intended usage.

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