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브레인(lax)의 판례 큐레이션 페이지를 precedents DB 최신 상태로 재생성하라. 대상: 판례-조문클러스터(참조조문 클러스터 인덱스), 판례-리딩케이스(피인용 상위 15건 카드+인용 cross-link), 판례-키워드축. 기준 스펙은 브레인의 판례-지식층 페이지(2층 구조, L1 큐레이션+L2 코퍼스)를 따르고 기존 페이지 구조·slug를 유지하라. 소장 판례(source=변호사 소장, workspace_id 있음)는 통계에 포함하되 개별 카드로 노출할 때 워크스페이스 식별 정보를 쓰지 마라. 변경 요약을 보고로 남겨라.

💭 사고 과정

The user wants the three precedent curation pages regenerated, and I already have the relevant skill and memory entries to guide this. I should load the skill first and check the existing brain pages before proceeding.

🔧 Skill

⚡ 명령 · ls C:/Users/user/lax-brain/company/wiki/ | head -80

💭 사고 과정

Let me follow the skill procedure, starting with reading the four page types and querying the corpus snapshot in parallel.

⚡ 명령 · cd C:/Users/user/lax-brain/company/wiki && wc -l 판례-지식층.md 판례-조문클러스터.md 판례-리딩케이스.md 판례-키워드…

cd C:/Users/user/lax-brain/company/wiki && wc -l 판례-지식층.md 판례-조문클러스터.md 판례-리딩케이스.md 판례-키워드축.md && echo "=== INDEX ===" && grep -n "판례" ../index.md

⚡ 명령 · node C:/Users/user/LAX-site/daemon/tools/d1q.mjs "SELECT query_tag, COUNT(*) n, SUM(CASE W…

node C:/Users/user/LAX-site/daemon/tools/d1q.mjs "SELECT query_tag, COUNT(*) n, SUM(CASE WHEN body IS NOT NULL AND length(body)>0 THEN 1 ELSE 0 END) body_n FROM precedents GROUP BY query_tag ORDER BY n DESC; SELECT COUNT(*) total, SUM(CASE WHEN body IS NOT NULL AND length(body)>0 THEN 1 ELSE 0 END) body_total FROM precedents; SELECT source, CASE WHEN workspace_id IS NULL THEN 'NULL' ELSE 'HAS_WS' END ws, COUNT(*) n FROM precedents GROUP BY source, ws; SELECT (SELECT COUNT(*) FROM precedent_statutes) statutes_rows, (SELECT COUNT(*) FROM precedent_citations) citations_rows, (SELECT COUNT(*) FROM precedent_citations WHERE internal_serial IS NOT NULL) internal_edges"

💭 사고 과정

The corpus hasn't changed — there are still zero cases sourced from the legal brief itself, with everything coming from national legal information and no workspace_id. Since that count is zero, it doesn't affect the statistics rule, but I should state this explicitly. Now I need to read through the four page types and check the numeric figures in the prose.

⚡ 명령 · cd C:/Users/user/lax-brain/company/wiki && for f in 판례-지식층.md 판례-키워드축.md 판례-리딩케이스.md; do e…

cd C:/Users/user/lax-brain/company/wiki && for f in 판례-지식층.md 판례-키워드축.md 판례-리딩케이스.md; do echo "=========== $f"; cat -n "$f"; done

⚡ 명령 · cd C:/Users/user/lax-brain/company/wiki && grep -n "1,382\|1,339\|3,169\|1,818\|1,844\|51,…

cd C:/Users/user/lax-brain/company/wiki && grep -n "1,382\|1,339\|3,169\|1,818\|1,844\|51,481\|80,567\|44,120\|28,893\|37,773\|49,637" 판례-지식층.md 판례-조문클러스터.md 판례-리딩케이스.md 판례-키워드축.md

💭 사고 과정

Since the corpus is unchanged, I need to actually recompute things now: E1 (top20 articles with domain filter), E2 (top15 cluster members with domain lens), E3 (top15 leading cases against the full 51k indegree), E4 (ego-net), and the keyword axis for top articles overall and by domain. I should check the existing page content carefully first so I can compare against what's persisted.

For E1 specifically, I need to confirm the schema before querying — I recall precedent_statutes likely has columns like prec_serial, statute_name, article, but I should verify rather than assume. Let me run a schema check query first.

⚡ 명령 · node C:/Users/user/LAX-site/daemon/tools/d1q.mjs "SELECT sql FROM sqlite_master WHERE name…

node C:/Users/user/LAX-site/daemon/tools/d1q.mjs "SELECT sql FROM sqlite_master WHERE name IN ('precedents','precedent_statutes','precedent_citations') AND type='table'"

⚡ 명령 · cd C:/Users/user/lax-brain/company/wiki && sed -n '1,120p' 판례-조문클러스터.md

[[THINK]]Now I need to recompute the actual figures. I should check how the top-20 article counts for the domain's four keywords were originally derived, since the skill requires deduplication by case_no (using MAX), and the article counts likely need COUNT(DISTINCT case_no) to be accurate.

I'm also planning queries for the representative cases per article cluster (top 3 by overall indegree among domain precedents), cluster member rankings (top 15 by internal indegree), leading case rankings (top 15 by overall indegree), and the ego-net cross-link analysis. The keyword axis is included too, while the knowledge layer stays fixed per spec.

I'm writing a query that joins domain precedents (filtered by query tags) with their cited statutes, counting distinct case numbers per statute-article combination to get the top 20 — but I need to verify whether the original counts like 153 used DISTINCT case_no or plain COUNT(*), so I'll pull both versions to compare.

For the top 3 representative cases per cluster, I'm checking whether SQLite's window functions (ROW_NUMBER) are usable here — they are, so I'll combine everything into one larger query rather than running separate ones, since scanning the ~44,120-row citation table should be cheap enough. I'm building a combined query with CTEs for the domain set, indegree counts, and cluster rankings, then deduplicating representative cases by case number and taking the maximum indegree within each cluster.

Finishing the query...