list_cubes

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

With no annotations provided, the description carries full burden. It discloses the envelope return format, total_matches vs complete flag, scope specifics, locale effects, retry with underscores, and empty query preview. This is richly transparent.

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 front-loaded with the main purpose and then detailed. Though somewhat lengthy, every sentence contributes essential information. Minor room for tightening, but overall efficient.

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 complexity (4 parameters, output schema exists), the description covers return envelope, pagination, scope variants, locale, retry logic, and empty query behavior. It is highly complete and leaves no critical gaps.

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 input schema has no descriptions (0% coverage), but the description adds meaning for all four parameters—query, scope, locale, offset—by explaining their values and behavior in context. It does not list each parameter separately but effectively conveys semantics.

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 tool searches the DataSaudi catalog of 277 statistical cubes, establishing a specific verb and resource. It distinguishes itself from sibling tools (describe_cube, query_cube) by focusing on listing/searching.

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 provides clear context on when to use the tool, including scope options (catalog, measures, levels), locale behavior, pagination via offset, and retry logic. While it does not explicitly exclude alternative tools, the use cases are well-defined.

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