feat: 분석 결과 전문성·신뢰도 보강 — 방법론·맥락·면책 (#23)#27
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- 방법론 블록(접이식): 데이터 출처(쿠팡 공개 리뷰) + 표본 수(총 리뷰/상품 수) + AI 분류 안내 - 섹션별 맥락 카피: TOP3/경쟁사 약점/구매 결정 요인/불만·긍정/평점 분포 각 "왜 중요한가" 설명 - 면책 고지: "참고용 인사이트, 원문 리뷰 병행 확인" 정직한 한계 고지 - 기존 테스트 유지 + 보강(8 tests), 76개 전체 통과 Refs #23 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
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Closes #23
작업 요약
분석 결과가 전문적이고 근거 있어 보이도록 보강해, 소상공인이 결과를 믿고 실행에 옮길 수 있게 한다.
변경 내용 (InsightReport)
<details>): 데이터 출처(쿠팡 공개 리뷰) + 표본 수(총 리뷰 수·상품 수) + "AI가 한국어 문맥으로 분류·집계" 안내 + "표본 많을수록 신뢰도↑".검증
npm run type-check통과npm test -- --run— 76/76 통과 (InsightReport 기존 5 + 보강 3, analysis-result-page 유지)작업 방식
이슈 #23 → /task-with-harness → 이 PR. 이번 주 4개 이슈(#20~#23) 중 마지막.
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