KOSPI, KOSDAQ 등 주요 시장 지수를 조회합니다.
Args:
index_name: 지수명 (예: "코스피", "코스닥"). 빈 문자열이면 주요 지수 전체.
date: 조회일 (YYYY-MM-DD). 빈 문자열이면 최근 영업일.
num_results: 조회 건수 (기본 20, 최대 100)
Returns:
지수 종가, 등락률, 거래량, 거래대금, 상장시가총액
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | ||
| index_name | No | ||
| num_results | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the behavioral burden. It discloses empty-string defaults (all indices, latest business day), the num_results default and max, and the return fields. It does not mention caveats such as historical date limits or how num_results applies across multiple indices.
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?
A front-loaded one-sentence summary followed by a compact Args/Returns block. Every line adds useful information, with no repetition of schema titles or empty filler.
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 simple read-only lookup with three optional parameters and an output schema, the description covers all parameter semantics and the main return fields. Nothing essential is missing for correct invocation.
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 the description fully compensates: each parameter gets a purpose, format examples (코스피/코스닥, YYYY-MM-DD), default, and maximum. An agent can fill all arguments correctly from the description alone.
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 '조회' (retrieve) and a specific resource '주요 시장 지수' (major market indices), naming KOSPI/KOSDAQ. This clearly differentiates it from sibling stock-level tools like get_stock_price and search_stock.
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?
Provides clear context that this tool is for market-index data, not individual stocks, which is enough to route an agent correctly. However, it does not explicitly name alternatives or state when not to use the tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.