delete_dataset

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

No annotations exist, so the description fully discloses destructive behavior, the confirm-gate mechanism, preview vs. actual deletion, and exact return formats. It highlights the irreversible nature and requires explicit confirmation, which is comprehensive for an agent.

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 logically structured: purpose, safety warning, parameters, returns, and example. Every section serves a purpose and is front-loaded with the critical safety note. No fluff or redundancy.

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?

Despite the lack of annotations and rich schema, the description covers all necessary context: safety, usage workflow, parameter semantics, return values, and a concrete example. An agent can call the tool correctly with only this description.

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 provides zero descriptions (0% coverage), but the description fully explains both parameters: 'name' as the exact dataset name and 'confirm' with its default and behavioral effect. An example ties it together, far exceeding what the schema alone offers.

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 opens with a specific verb ('Delete') and resource ('an entire dataset and all of its rows'), which clearly distinguishes it from sibling tools like delete_rows. The intent is unambiguous and directly actionable.

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 an explicit two-step workflow: first invoke with confirm=false to preview, then with confirm=true after user agreement. This tells the agent exactly when and how to use the tool, though it does not compare directly to delete_rows, the workflow is complete and self-contained.

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