update_dataset

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

The description only states the action without disclosing side effects, error conditions, or return behavior. No annotations are provided to complement.

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 succinct and to the point, with no unnecessary words.

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 simple schema and no output schema, the description is adequate but could benefit from specifying requirements like at least one field or error handling.

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 description adds minimal additional meaning beyond the schema's parameter descriptions; it clarifies that at least one of name or description should be supplied, but otherwise relies on the schema.

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 that the tool updates a dataset's name and/or description, which is specific and distinguishes it from create/list operations.

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 does not provide explicit guidance on when to use it versus alternatives, such as when creating or listing datasets, nor does it mention prerequisites like dataset existence or permissions.

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