출력
기대 결과
- public call
- representative return shape
- verification result
엔진 역할
macro engine application skill for 자산: 5대 자산 심층 해석 + Cu/Au + BEI 4분면.
공개 호출 방식
import dartlab
result = dartlab.macro("assets", market="KR") 호출 동작
Reads market-level data for 제5막: 시장은 어떻게 반응하나 and computes signals, regimes, and limitations. Company-level financial interpretation belongs to analysis.
대표 반환 형태
Returns a dict or DataFrame-like result. Core fields are market, latestAsOf/date, indicator, value, unit, signal/regime, score, source/basis, assumptions, and flags.
기본 실행 순서
- target, period, and source data are fixed first.
- Run the public call exactly as documented.
- Check latestAsOf/date, missing values, flags, and assumptions.
- Bind numeric claims to tableRef/valueRef/dateRef/executionRef.
- Hand off multi-axis narrative composition to story or the parent report skill.
기본 검증
This skill is a public execution document. If this axis call, representative return keys, error behavior, or runtime limits change, update this file in the same change.
런타임
실행 환경별 호환성
| 환경 | 상태 | 비고 / 제한 |
|---|---|---|
| Local Python | supported | — |
| Server | supported | — |
| MCP | supported | — |
| Web AI | supported | — |
| Pyodide | limited | — |
실패 회피
흔한 실패 · 절대 금지
절대 금지
- Do not cite macro numbers without date/source.
- Do not use macro as a substitute for company financial analysis.
- Do not mix macro output as if it were an analysis internal calculation.