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

Annotations already mark the call as read-only, idempotent, and non-destructive. The description adds the useful behavioral detail that it returns only locally loaded datasets with record counts, which goes beyond the annotations and is not contradicted.

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 core statement is one short sentence and is front-loaded in English. The Korean translation repeats the same content, adding a little length, but the overall description is compact and every clause contributes meaning.

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 zero-required-parameter tool with strong annotations, the description covers what it returns, its scope, and why to call it. It does not spell out the exact output shape, but the list-with-counts description is sufficient for correct invocation.

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 single optional query parameter is already fully described in the schema, including that empty means the full list. The description adds no additional parameter-level meaning, so the schema-coverage baseline of 3 applies.

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 states a specific action and resource: listing the loaded datasets and their record counts. It also differentiates from siblings like search_catalog and search_data by emphasizing that only actually loaded data is included, so an agent can tell this tool apart from the search-oriented tools.

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 gives a clear use context: use this when checking what data is available to answer from. It does not explicitly name alternatives or say when not to use it, but the 'actually loaded' framing provides enough context to route an agent appropriately.

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