fca_trade_stats

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true, and destructiveHint=false, so the safety profile is fully covered. The description adds genuinely useful context — that results are implicitly constrained to a single organization — but says nothing about result volume limits, pagination, or how an empty query behaves. Comparable to the calibration case where safety is annotated and only scoping context is added.

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 front-loaded in the first sentence, and the wrapper relationship follows immediately. It is tight overall with no filler, though the domain-scope sentence could be folded in more economically.

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?

The presence of an output schema and rich annotations means the definition doesn't need to explain return shape or safety. However, with zero schema coverage on parameters, the description should say more about how `query` and `rows` behave; that gap is the main impediment to a correct first call.

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 0%, so both parameters (`rows`, `query`) are undocumented anywhere. The description does not explain what `query` matches (dataset names? descriptions? HS chapter terms?) or whether the empty-string default returns everything, nor what `rows` bounds. The schema does supply defaults, but the semantics an agent needs to form a good call are absent.

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?

States a specific verb and resource ('Search Federal Customs Authority trade statistics datasets') and immediately clarifies it is a filtered wrapper over `fcsc_search_dataset` scoped to the `federal-customs-authority` organization. The domain content (UAE non-oil trade by HS chapter, imports, exports, re-exports) further pins down what an agent will get, distinguishing it clearly from the generic sibling.

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 explicitly names the underlying alternative (`fcsc_search_dataset`) and explains the selection rule implicitly: use this when you want the FCA organization's data without specifying an organization yourself. It lacks an explicit 'do not use this for other organizations / use fcsc_search_dataset instead' exclusion, so it stops short of full routing guidance.

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