get_us_chart

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

No annotations are provided, so the description carries the full burden. It explains that prepost only works for intraday intervals, that limit protects token consumption, and that larger data should be obtained via export. It does not mention any side effects or authorization needs, but the read-only nature is implied.

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 well-structured with an English title, Korean usage context, and an Args section. It is front-loaded with purpose and usage. Although it is relatively long, every sentence adds value, and it is not redundant.

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?

Considering the tool has an output schema (not shown but present), the description adequately covers the what, when, and how. It mentions token consumption and limits. Minor omission: it doesn't explicitly state the return type (OHLCV fields), but the output schema likely fills that gap.

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%, but the description adds significant meaning to all five parameters: ticker (example), period/interval (lists valid values), prepost (notes intraday only), and limit (explains default, max, and use cases). This fully compensates for lack of schema descriptions.

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 stock OHLCV data (historical price data) and explicitly distinguishes it from get_chart for Korean stocks. It also provides specific example queries like 'AAPL 차트' and 'Tesla 1년 주가', making the purpose very clear.

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 explicitly says to use this tool for US stock chart questions and advises using get_chart for Korean stocks. It also mentions when to use export_us_to_excel for larger data. However, it does not differentiate from get_us_price, which could be used for simpler price data.

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