종목의 최근 N일간 주가 추이를 조회합니다.
Args:
stock_name: 종목명 (예: "삼성전자", "NAVER")
stock_code: 종목 단축코드 6자리 (예: "005930"). stock_name과 둘 중 하나.
days: 조회 기간 (기본 7일, 최대 30일)
Returns:
일별 종가, 등락률, 거래량 추이 및 기간 수익률
| Name | Required | Description | Default |
|---|---|---|---|
| days | No | ||
| stock_code | No | ||
| stock_name | 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, the description carries the behavioral burden; it does communicate a read-only lookup ('조회합니다'), the one-of identifier constraint, and the days default/max. However, it does not disclose what happens if both or neither identifier is supplied, whether one takes precedence, error behavior, or any rate/source limitations.
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 purpose line is front-loaded, followed by a compact Args list and a one-line Returns summary. There is no filler and every sentence contributes useful information.
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?
The description is nearly complete for a simple read tool: it identifies the required inputs, gives constraints, and summarizes outputs while an output schema exists to supply return typing. It falls slightly short by not clarifying precedence/behavior when both stock_name and stock_code are provided, and by not stating whether at least one is required.
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 compensates fully: it explains stock_name with examples, specifies stock_code's 6-digit format and the one-of relationship, and gives days' default (7) and maximum (30). This adds real meaning beyond the bare schema fields.
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 'queries the stock price trend over the most recent N days' and lists the daily close, change rate, volume, and period return, so an agent can tell what it does. It does not explicitly differentiate from siblings such as get_stock_price, although the phrase 'recent N-day trend' implies a historical series rather than a single snapshot.
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?
No guidance is given about when this tool should be chosen over get_stock_price, compare_stocks, or search_stock. The only usage-like information is the parameter relationship 'use either stock_name or stock_code', which concerns argument selection rather than tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.