test(routing-eval): add 6 data_science cases (PR #10/#11 regression line)#13
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…ine) routing_eval golden dataset를 12 → 18 cases로 확장. data_science 카테고리에 신규 6 cases 추가하여 본 세션의 시각화/분기 회귀를 정량 측정으로 차단. 신규 cases: - data-002 trend line CSV → data_science_team - data-003 JSON category bar chart - data-004 xlsx multi-sheet 비교 - data-005 multi-file 비교 - data-006 CJK 라벨 차트 - data-007 corrupt PDF 우아한 실패 plan §4.0 P5 (회귀는 evaluation harness로) 강화. CODEBASE_WIDE_REFACTORING_PLAN §2.8 항목에 18 cases + 카테고리 10종 + data_science 확장 메모 반영. 검증: pytest 316/316 + routing_eval 6/6 PASS, 회귀 0. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Summary
routing_eval golden dataset를 12 → 18 cases로 확장. data_science 카테고리에 6 cases 신규 추가하여 본 세션의 시각화/분기 회귀(PR #10, #11)를 정량 측정으로 차단.
New cases (S-A~S-F 그대로 라벨)
Plan §4.0 P5 강화
회귀는 evaluation harness로 측정. scorer가 신규 cases도 top-1 평가.
Verification
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