delete_dataset

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly states that deletion is permanent, irreversible, and cascades to all logs, which is critical for a destructive operation. It could add permission requirements or downstream impact, but the core destructive behavior is well disclosed.

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 short sentences with no filler. It front-loads the action and immediately communicates the most important consequence (permanence).

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 single-parameter destructive tool, the description is sufficiently complete: it states what is deleted, the scope of deletion, and irreversibility. No output schema exists, but return values are not critical for a delete operation. Sibling tool names further clarify its role.

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 schema already provides 100% coverage for the single parameter dataset_id with a clear description. The tool description adds no additional parameter semantics, so the baseline of 3 is appropriate.

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 ('delete') and clearly identifies the resource ('a dataset and all its logs'). It also distinguishes this tool from sibling tools like remove_dataset_logs by explicitly stating the cascading scope.

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 implies when to use this tool—when you want to permanently remove an entire dataset and its logs—but it does not explicitly contrast it with alternatives such as remove_dataset_logs or delete_experiment. The usage context is clear but not fully articulated.

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