restore_dataset

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

With no annotations, the description carries full disclosure burden. It only states the action without detailing side effects, required permissions, behavior on invalid state (e.g., already active dataset), or any irreversible consequences. This is insufficient for a mutation tool.

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 a single concise sentence, front-loaded with the key action. It avoids wasted words, though it could include more context without losing conciseness.

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 tool's mutating nature, lack of annotations, and existence of an output schema (not shown), the description is incomplete. It omits preconditions, error handling, and behavioral details that would help an agent use it correctly.

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 100% (parameter description: 'Dataset identifier to restore.'). The tool description adds no extra meaning beyond the schema, so baseline 3 is appropriate. No additional value provided.

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 action ('Restore') and the resource ('soft-deleted dataset record'). It directly distinguishes from siblings like delete_dataset (opposite action) and create_dataset (new record), providing unambiguous purpose.

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?

No explicit guidance on when to use this tool versus alternatives (e.g., restore_category for categories). It implies usage for soft-deleted datasets but doesn't mention prerequisites, error scenarios (e.g., dataset not in soft-deleted state), or when not to use.

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