종목명 키워드로 KRX 상장종목을 검색합니다.
Args:
keyword: 검색 키워드 (예: "삼성", "바이오", "에너지")
market: 시장 구분 ("KOSPI", "KOSDAQ", "KONEX"). 빈 문자열이면 전체.
num_results: 조회 건수 (기본 20, 최대 100)
Returns:
종목코드, 종목명, 시장구분, 법인명, 법인등록번호
| Name | Required | Description | Default |
|---|---|---|---|
| market | No | ||
| keyword | Yes | ||
| 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?
With no annotations provided, the description carries the full burden. It usefully discloses KRX scope, market-filter semantics ('empty string means all'), and result-count limits. Still, it does not describe matching behavior (partial vs. exact), no-result handling, uniqueness guarantees, or error conditions.
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 well-structured: a one-line purpose followed by Args and Returns sections. Every line adds necessary information, with no filler or repetition beyond what is justified by the minimal schema.
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 the tool's moderate complexity and the presence of an output schema, the description covers the essential invocation details: keyword examples, valid markets, defaults, and returned fields. It is slightly incomplete in not explaining when to prefer this over sibling tools or what edge cases exist, but it is sufficient for correct basic 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 must fully compensate. It does: every parameter is explained with valid values, examples, defaults, and the max bound for num_results. This is strong, complete parameter documentation beyond the raw schema.
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 states a specific action ('search') and resource ('KRX listed stocks') via a stock-name keyword, which clearly conveys what the tool does. It does not explicitly name sibling tools to distinguish itself, but the keyword-search framing is clearly distinct from siblings like get_stock_price or compare_stocks.
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?
Usage context is implied: an agent would use this when it needs to find or resolve KRX stocks by a name keyword. However, there are no explicit when-to-use/when-not-to-use rules or references to alternative sibling tools, leaving routing decisions to inference.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.