diff --git a/CLAUDE.md b/CLAUDE.md
index ca24504..3eb2660 100644
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -1,5 +1,20 @@
 # hyungi_Document_Server — Claude Code 작업 가이드
 
+## Infrastructure Reference 📌
+
+**Always refer to** `~/.claude/projects/-Users-hyungiahn/memory/infra_inventory.md` for:
+- AI model routing (primary / fallback / embedding / rerank / vision) — **the model names below may be stale**
+- Machine info, Tailscale IPs, SSH targets
+- Docker container topology and compose projects
+- Drift log (known Desired vs Actual inconsistencies)
+- Verify commands
+
+**If this file and `infra_inventory.md` disagree, `infra_inventory.md` is authoritative.** Do not change `config.yaml` / `credentials.env` without first updating `infra_inventory.md`.
+
+**Search experiment soft lock**: During Phase 2 work (search.py refactor, QueryAnalyzer, run_eval.py execution), do **not** run `docker compose restart`, change `config.yaml`, or pull Ollama models. Violating this invalidates the experiment baseline.
+
+---
+
 ## 프로젝트 개요
 
 Self-hosted PKM(Personal Knowledge Management) 웹 애플리케이션.
diff --git a/app/services/search/fusion_service.py b/app/services/search/fusion_service.py
index 7e1e3f5..5c857bf 100644
--- a/app/services/search/fusion_service.py
+++ b/app/services/search/fusion_service.py
@@ -224,22 +224,23 @@ def get_strategy(name: str) -> FusionStrategy:
 SOFT_FILTER_MAX_BOOST = 0.05  # plan 룰 (CRITICAL)
 # ↑ RRF score는 0.01~0.05 범위 (k=60). 상한 초과 시 기존 랭킹 왜곡.
 #   기존 RRFWithBoost의 legal article boost(0.05)와 동일 최대값 → 일관성.
-SOFT_FILTER_DOMAIN_BOOST = 0.03
-SOFT_FILTER_DOCTYPE_BOOST = 0.02
+SOFT_FILTER_DOMAIN_BOOST = 0.01  # 2026-04-08 실측: 0.03은 exact_keyword -0.03 악화
+# ↑ 낮게 잡는 이유: soft_filter는 "같은 도메인 doc을 동등하게 boost" → exact match
+#   doc의 상대 우위가 손상됨. 0.01 수준이면 fusion 내부 순위 역전 확률 최소.
 
 
 def apply_soft_filter_boost(
     results: list["SearchResult"],
     soft_filters: dict | None,
 ) -> int:
-    """Phase 2.3 — QueryAnalyzer soft_filters 기반 score boost.
+    """Phase 2.3 — QueryAnalyzer soft_filters.domain 기반 약한 score boost.
 
-    ai_domain / ai_tags 매칭 시 소량 boost 적용. 총 boost는
-    SOFT_FILTER_MAX_BOOST(0.05) 상한을 넘지 않음.
+    ai_domain 정확 매칭 시 SOFT_FILTER_DOMAIN_BOOST(0.01) 1회 가산.
+    document_type 매칭은 v0.1 평가셋에서 효과 측정 불가 + false positive 많음 → 제외.
 
     Args:
         results: fusion 직후 SearchResult 리스트 (in-place 수정)
-        soft_filters: query_analysis.soft_filters = {"domain": [...], "document_type": [...]}
+        soft_filters: query_analysis.soft_filters = {"domain": [...]}
 
     Returns:
         int — boost 적용된 결과 개수 (debug/notes용)
@@ -247,35 +248,26 @@ def apply_soft_filter_boost(
     if not soft_filters:
         return 0
     domain_list = [str(d).lower() for d in soft_filters.get("domain", []) or []]
-    doctype_list = [str(t).lower() for t in soft_filters.get("document_type", []) or []]
-    if not domain_list and not doctype_list:
+    if not domain_list:
         return 0
 
     boosted_count = 0
     for r in results:
-        boost = 0.0
-
-        # domain 매칭 — ai_domain 부분 문자열 매칭 (Industrial_Safety/Legislation 같은 경로 매칭)
-        if domain_list and r.ai_domain:
-            ai_dom_lower = r.ai_domain.lower()
-            for d in domain_list:
-                if d in ai_dom_lower or ai_dom_lower in d:
-                    boost += SOFT_FILTER_DOMAIN_BOOST
-                    break  # 한 번만
-
-        # document_type 매칭 — ai_tags JSON 문자열 또는 ai_domain 내 keyword 탐지
-        # (ai_domain에 "Law_Document"는 안 들어감. ai_tags에 law/law_document 같은 태그가 있음.)
-        # 간단화: ai_domain 경로에 keyword가 포함되면 매칭
-        if doctype_list:
-            hay = (r.ai_domain or "").lower() + " " + (getattr(r, "match_reason", "") or "").lower()
-            for t in doctype_list:
-                if t in hay or any(word in hay for word in t.split("_")):
-                    boost += SOFT_FILTER_DOCTYPE_BOOST
-                    break
-
-        if boost > 0:
-            boost = min(boost, SOFT_FILTER_MAX_BOOST)
-            r.score += boost
+        if not r.ai_domain:
+            continue
+        ai_dom_lower = r.ai_domain.lower()
+        # 정확 매칭 또는 subdirectory 매칭 ("Industrial_Safety/Legislation" → "industrial_safety" 매칭)
+        matched = False
+        for d in domain_list:
+            if d == ai_dom_lower:
+                matched = True
+                break
+            # path 레벨 매칭: "industrial_safety/legislation" in "industrial_safety/legislation/act"
+            if d in ai_dom_lower and "/" in d:
+                matched = True
+                break
+        if matched:
+            r.score += min(SOFT_FILTER_DOMAIN_BOOST, SOFT_FILTER_MAX_BOOST)
             boosted_count += 1
 
     # boost 적용 후 재정렬