G0~G8 성과·동맹 측정 OS 작업 일괄 고정

8월 7일까지 워킹트리에만 남아 있던 미커밋 작업을 커밋한다. 여러 사본
폴더(worktree·clone)에 흩어져 있던 중간 스냅샷을 정리하기 전에 원본을
git 이력으로 고정하는 것이 목적이다.

- contracts/routes/services: measurement, outcome_trajectory, rupture_repair,
  deliberate_practice, calibration_transfer, supervision_research,
  multimodal_alliance, continuous_improvement 계열 신규 모듈과 테스트
- infra/db/init: 07~16 마이그레이션(측정 기반~calibration transfer 실행)
- apps/web: 세션 리뷰 카드·관리 화면·E2E 스펙 추가
- docs/ops: G0~G8 라이브 통합·배포·롤백 증거 문서와 evidence JSON/PNG
- scripts: smoke·ledger·릴리스 에이전트·NAS 프리뷰 운영 스크립트

engine.public 로그 .bak과 apps/web/test-results 산출물은 커밋에서 제외했다.

apps/api/app/services/guardrail.py

@@ -163,6 +163,15 @@ _PII_PATTERNS: list[tuple[str, re.Pattern[str]]] = [
     ("ADDR", re.compile(r"[가-힣]{2,}(?:시|도)\s?[가-힣]{1,4}(?:시|군|구)\s?[가-힣0-9]{1,}(?:동|읍|면|로|길)")),
 ]
 
+# Source/input text keeps the broad contextless-name heuristic above for recall.
+# Generated synthetic content has no user-originated text after source validation;
+# applying that heuristic there misclassifies ordinary words such as "서운함을".
+# Keep every high-confidence label/context/honorific pattern and all non-name PII.
+_SYNTHETIC_GENERATED_PII_PATTERNS = (
+    *_PII_PATTERNS[:5],
+    *_PII_PATTERNS[6:],
+)
+
 # Presidio 지연 로드 캐시 (-1=미시도, None=미설치, 객체=설치됨)
 _PRESIDIO_ANALYZER: object = -1
 _PRESIDIO_ANONYMIZER: object = -1
@@ -216,7 +225,10 @@ class MaskResult:
     used_ko_recognizer: bool = False
 
 
-def _mask_regex_pii(text: str) -> tuple[str, list[str]]:
+def _mask_regex_pii(
+    text: str,
+    patterns: Iterable[tuple[str, re.Pattern[str]]] = _PII_PATTERNS,
+) -> tuple[str, list[str]]:
     masked = text
     found: list[str] = []
 
@@ -235,7 +247,7 @@ def _mask_regex_pii(text: str) -> tuple[str, list[str]]:
 
         return _replace
 
-    for label, pat in _PII_PATTERNS:
+    for label, pat in patterns:
         masked = pat.sub(replace_match(label), masked)
     return masked, sorted(set(found))
 
@@ -307,6 +319,50 @@ def mask_pii(text: str) -> MaskResult:
     )
 
 
+def mask_synthetic_generated_pii(text: str) -> MaskResult:
+    """PII gate for model-generated text from validated synthetic sources.
+
+    Explicit name labels, self-introductions, relationship/name contexts,
+    honorifics, optional recognizers, Presidio and every non-name PII pattern stay
+    enabled. Only the ambiguous contextless Korean surname heuristic is omitted.
+    """
+
+    if not text:
+        return MaskResult(text_masked=text, entities=[], used_presidio=False)
+
+    analyzer, anonymizer = _try_load_presidio()
+    if analyzer is not None and anonymizer is not None:
+        try:
+            results = analyzer.analyze(text=text, language="en")
+            ents = sorted({r.entity_type for r in results})
+            anonymized = anonymizer.anonymize(text=text, analyzer_results=results)
+            ko_masked, ko_ents, used_ko = _mask_ko_recognizer_pii(anonymized.text)
+            masked, regex_ents = _mask_regex_pii(
+                ko_masked,
+                _SYNTHETIC_GENERATED_PII_PATTERNS,
+            )
+            return MaskResult(
+                text_masked=masked,
+                entities=sorted(set(ents + ko_ents + regex_ents)),
+                used_presidio=True,
+                used_ko_recognizer=used_ko,
+            )
+        except Exception:
+            pass
+
+    ko_masked, ko_ents, used_ko = _mask_ko_recognizer_pii(text)
+    masked, found = _mask_regex_pii(
+        ko_masked,
+        _SYNTHETIC_GENERATED_PII_PATTERNS,
+    )
+    return MaskResult(
+        text_masked=masked,
+        entities=sorted(set(ko_ents + found)),
+        used_presidio=False,
+        used_ko_recognizer=used_ko,
+    )
+
+
 # ════════════════════════════════════════════════════════════════════════════
 # 2. 위기 분류 (입력 — 실제위기 vs 페르소나 연기 구분, R8)
 # ════════════════════════════════════════════════════════════════════════════