get_us_etf_info

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the description does not need to restate safety. It adds value by specifying the returned data categories (top holdings, sector weights, asset allocation). It does not discuss pagination, error handling, or other behaviors, but given the annotations cover the main traits, a 3 is appropriate.

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 compact and front-loaded with the main purpose, followed by example queries and a brief parameter note. It avoids unnecessary detail. The bilingual format (Korean/English) is slightly redundant but not harmful. Overall, it is efficient and well-structured.

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 single-parameter read-only tool with an output schema, the description is fairly complete. It states the type of data returned and gives usage examples. It does not mention that it is specifically for US ETFs, but the tool name already conveys that. It could note that the ticker must be a US-listed ETF, but this is minor given the examples and schema availability.

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 has no description for the ticker parameter (0% coverage), so the description must compensate. It does so by explaining the ticker is an ETF ticker and providing concrete examples (SPY, QQQ, VOO, SCHD). This adds meaningful guidance beyond the raw schema, though it could also specify format or uppercase requirement.

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 it provides US ETF details including top holdings, sector weights, and asset allocation. It distinguishes itself from siblings like get_us_info (general stock info) and get_etf_info (potentially non-US ETF) by specifying 'US ETF' and the exact content types. Example queries further clarify its scope.

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 concrete example queries ('SPY 구성종목', 'QQQ holdings', 'VOO 섹터', 'ETF 보수') that indicate when to use the tool. However, it does not explicitly mention alternatives or state when not to use it, such as for non-US ETFs or price data. The context is clear but lacks explicit exclusions.

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