get_us_earnings

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

No annotations are provided, so the description bears the full burden. It does not disclose behavioral traits such as data refresh frequency, source (e.g., SEC filings, provider), whether results are cached, or any limitations. The only added context is that quarterly earnings (10-Q) are key events, but that's not a behavioral trait of the 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 very concise: three sentences plus an args line. The first sentence states the tool's purpose, the second gives example queries, and the third provides context about US earnings. Every sentence adds value with no redundancy. The structure is front-loaded with the main function.

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 that an output schema exists (not shown here but indicated), the description does not need to explain return values. It covers the main purpose, parameter usage, and contextual importance of earnings. For a simple one-parameter tool, it is adequately complete, though it could add a note about the result type (e.g., dates, numbers).

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 a single 'ticker' parameter with no description. The description adds 'ticker: US 티커 (예: 'NVDA')', which clarifies that this is a US ticker symbol. With 0% schema coverage, the description compensates well by specifying the ticker format and giving an example.

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 returns US earnings calendar including next earnings date and EPS surprise history. It provides example queries (e.g., 'AAPL 실적 언제') and distinguishes itself by focusing on earnings-specific data, which is not covered by siblings like get_us_price, get_us_financials, etc.

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 gives concrete usage examples and context (e.g., when to ask about earnings dates). While it does not explicitly list alternatives or when not to use, the examples and mention of 'US earnings date / EPS surprise' make the usage clear. Sibling tools are not contrasted, but the description is sufficient for the intended queries.

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