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toss-invest

by nangchang

캔들 차트 조회

toss_get_candles
Read-onlyIdempotent

Get historical OHLCV candlestick data for any stock symbol. Choose between 1-minute or daily intervals, adjust for splits/dividends, and paginate through older candles.

Instructions

특정 종목의 캔들 차트 데이터를 조회합니다.

Args:

  • symbol (string, 필수): 종목 심볼. KRX: 6자리 숫자, US: 영문 티커

  • interval (string, 필수): 캔들 간격. "1m" (1분봉) 또는 "1d" (일봉)

  • count (number, 선택): 조회 건수. 기본값 100, 최대 200

  • before (string, 선택): 페이지네이션 상한 (ISO 8601). 이 시간 이전 캔들을 반환

  • adjusted (boolean, 선택): 수정주가 적용 여부. 기본값 true

Returns:

  • candles[]: 캔들 목록 (timestamp, openPrice, highPrice, lowPrice, closePrice, volume, currency)

  • nextBefore: 다음 페이지 조회용 cursor (더 이전 데이터가 없으면 null)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo조회 건수. 기본값 100, 최대 200
beforeNo페이지네이션 상한 (ISO 8601). 이 시간 이전의 캔들을 반환. 이전 응답의 nextBefore 값 사용
symbolYes종목 심볼. KRX: 6자리 숫자 (예: 005930), US: 영문 티커 (예: AAPL)
adjustedNo수정주가 적용 여부. 기본값 true
intervalYes캔들 간격. "1m" (1분봉) 또는 "1d" (일봉)
Behavior4/5

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

Annotations already identify this as a read-only, open-world, idempotent, non-destructive operation. The description adds behavioral context beyond this, including pagination via 'before'/'nextBefore', default values for 'count' and 'adjusted', and the return structure (candles[] with fields). This provides useful operational detail without contradicting the annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and well-structured: a one-line purpose statement followed by a clearly labeled 'Args' list and 'Returns' section. Every element is necessary, and the format is easy to scan. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description fully documents the return shape (candles[] with timestamp, openPrice, etc., and nextBefore). It also covers all 5 parameters, including optional ones with defaults and constraints. For a read-oriented tool with moderate complexity, this is complete and self-sufficient.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description repeats the parameter descriptions already present in the schema (e.g., interval, count, before) without adding new meaning. The 'Returns' section is valuable but does not contribute to parameter semantics. Thus, no additional value over the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: '특정 종목의 캔들 차트 데이터를 조회합니다.' This specifies the verb (retrieve), resource (candle chart data for a specific stock), and scope (specific symbol). It distinctly differs from sibling tools like toss_get_prices or toss_get_trades, which focus on current prices or trade history.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description does not explicitly mention when to use this tool versus alternatives, nor does it provide exclusions or alternative tool recommendations. Usage is implied by the tool's name and description (needing candle chart data), but there is no direct guidance on when not to use it or which sibling would be better for different scenarios.

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

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