feat(study): Phase 4-A 운영 가시화 — 통계 대시보드 AI 풀이 카드

Phase 4-A 가 wrong/unsure 풀이를 background batch 로 캐시하는데, 사용자/운영자
입장에서 (1) 지금까지 얼마나 캐시 채워졌는지, (2) 환각 차단/파싱 실패/자료 없음
같은 worker 결과 분포를 볼 수 없었음. 통계 대시보드에 카드 추가.

Backend (study_question_progress.py /stats):
- StatsAiExplanation 신규 응답 섹션
  · status_distribution — 토픽 전체 study_questions.ai_explanation_status 분포
    (none/ready/failed/skipped/stale/pending 6 키 default 0)
  · target_total / target_ready — wrong/unsure progress 의 ready 비율
    (캐시 hit 가능성 추정 핵심 지표)
  · recent_jobs — 최근 7일 study_question_jobs 의 (status, error_code) 분포
    ('completed', 'failed:guard_fail', 'failed:parse_fail', 'skipped:evidence_missing'
    같은 합성 키)

Frontend (/study/topics/[id]/stats):
- 신규 Card "AI 풀이 캐시" — Sparkles 아이콘
  · 큰 숫자 + 진행률 바: ready / wrong+unsure
  · 토픽 전체 status 분포 inline (한국어 라벨)
  · 최근 7일 worker 결과 grid (환각 차단 / 파싱 실패 / 자료 없음 skip 등 분리)
- statusLabel / jobLabel 헬퍼 — 운영자 친화 한국어

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

app/api/study_question_progress.py

@@ -353,6 +353,17 @@ class StatsSubjectBreakdown(BaseModel):
     chronic: int
 
 
+class StatsAiExplanation(BaseModel):
+    """Phase 4-A 운영 관찰 — AI 풀이 캐시 진척 + 최근 7일 worker 결과."""
+    # study_questions.ai_explanation_status 분포 (이 토픽 전체)
+    status_distribution: dict  # 'none' / 'ready' / 'failed' / 'skipped' / 'stale' / 'pending'
+    # wrong/unsure 중 ready 박힌 비율 (캐시 hit 가능성 추정)
+    target_total: int        # progress.last_outcome IN (wrong, unsure) 의 qid 수
+    target_ready: int        # 그 중 ai_explanation_status='ready' 인 수
+    # 최근 7일 study_question_jobs 의 (status, error_code) 분포
+    recent_jobs: dict  # {'completed': N, 'failed:guard_fail': N, 'failed:parse_fail': N, 'skipped:evidence_missing': N, 'pending': N, ...}
+
+
 class StatsResponse(BaseModel):
     questions: StatsQuestions
     pattern_distribution: dict  # state(or "unattempted") → count
@@ -361,6 +372,7 @@ class StatsResponse(BaseModel):
     session_trend: list[StatsSessionTrendItem]  # 최근 done 세션 newest→oldest
     daily_attempts_30d: list[StatsDailyAttempt]
     subject_breakdown: list[StatsSubjectBreakdown]
+    ai_explanation: StatsAiExplanation
 
 
 @router.get("/{topic_id}/stats", response_model=StatsResponse)
@@ -615,6 +627,88 @@ async def topic_stats(
         for r in subj_rows
     ]
 
+    # 8. Phase 4-A: AI 풀이 캐시 진척 + 최근 7일 worker 결과
+    # 8a. study_questions.ai_explanation_status 분포 (토픽 전체)
+    ai_status_rows = (
+        await session.execute(
+            select(
+                func.coalesce(StudyQuestion.ai_explanation_status, "none").label("st"),
+                func.count().label("cnt"),
+            )
+            .where(
+                StudyQuestion.user_id == user.id,
+                StudyQuestion.study_topic_id == topic_id,
+                StudyQuestion.deleted_at.is_(None),
+            )
+            .group_by("st")
+        )
+    ).all()
+    ai_status_distribution = {r.st: int(r.cnt) for r in ai_status_rows}
+    for k in ("none", "ready", "failed", "skipped", "stale", "pending"):
+        ai_status_distribution.setdefault(k, 0)
+
+    # 8b. wrong/unsure 의 ready 비율 (캐시 hit 가능성)
+    target_total_row = await session.execute(
+        select(func.count())
+        .select_from(StudyQuestionProgress)
+        .where(
+            StudyQuestionProgress.user_id == user.id,
+            StudyQuestionProgress.study_topic_id == topic_id,
+            StudyQuestionProgress.last_outcome.in_(("wrong", "unsure")),
+        )
+    )
+    target_total = int(target_total_row.scalar() or 0)
+
+    target_ready_row = await session.execute(
+        select(func.count())
+        .select_from(StudyQuestionProgress)
+        .join(
+            StudyQuestion,
+            and_(
+                StudyQuestion.id == StudyQuestionProgress.study_question_id,
+                StudyQuestion.deleted_at.is_(None),
+            ),
+        )
+        .where(
+            StudyQuestionProgress.user_id == user.id,
+            StudyQuestionProgress.study_topic_id == topic_id,
+            StudyQuestionProgress.last_outcome.in_(("wrong", "unsure")),
+            StudyQuestion.ai_explanation_status == "ready",
+        )
+    )
+    target_ready = int(target_ready_row.scalar() or 0)
+
+    # 8c. 최근 7일 study_question_jobs 분포 — terminal status × error_code
+    from models.study_question_job import StudyQuestionJob
+
+    recent_cutoff = now - timedelta(days=7)
+    job_rows = (
+        await session.execute(
+            select(
+                StudyQuestionJob.status.label("st"),
+                func.coalesce(StudyQuestionJob.error_code, "").label("err"),
+                func.count().label("cnt"),
+            )
+            .join(
+                StudyQuestion,
+                and_(
+                    StudyQuestion.id == StudyQuestionJob.study_question_id,
+                    StudyQuestion.study_topic_id == topic_id,
+                    StudyQuestion.user_id == user.id,
+                ),
+            )
+            .where(
+                StudyQuestionJob.user_id == user.id,
+                StudyQuestionJob.created_at >= recent_cutoff,
+            )
+            .group_by("st", "err")
+        )
+    ).all()
+    recent_jobs: dict[str, int] = {}
+    for r in job_rows:
+        key = f"{r.st}:{r.err}" if r.err else r.st
+        recent_jobs[key] = int(r.cnt)
+
     return StatsResponse(
         questions=StatsQuestions(
             total=total_q, attempted=attempted, unattempted=unattempted
@@ -625,4 +719,10 @@ async def topic_stats(
         session_trend=session_trend,
         daily_attempts_30d=daily_attempts_30d,
         subject_breakdown=subject_breakdown,
+        ai_explanation=StatsAiExplanation(
+            status_distribution=ai_status_distribution,
+            target_total=target_total,
+            target_ready=target_ready,
+            recent_jobs=recent_jobs,
+        ),
     )

frontend/src/routes/study/topics/[id]/stats/+page.svelte

@@ -9,7 +9,7 @@
   import { page } from '$app/stores';
   import { api } from '$lib/api';
   import { addToast } from '$lib/stores/toast';
-  import { ArrowLeft, BarChart3, BookOpen, Clock, TrendingUp } from 'lucide-svelte';
+  import { ArrowLeft, BarChart3, BookOpen, Clock, TrendingUp, Sparkles } from 'lucide-svelte';
   import Button from '$lib/components/ui/Button.svelte';
   import Card from '$lib/components/ui/Card.svelte';
   import Skeleton from '$lib/components/ui/Skeleton.svelte';
@@ -103,6 +103,29 @@
   let dailyChart = $derived(buildBars(stats?.daily_attempts_30d ?? [], 300, 60));
   let sessionChart = $derived(buildSparkline(sessionPoints, 300, 60));
 
+  function statusLabel(k) {
+    return ({
+      none: '미생성',
+      ready: '캐시됨',
+      pending: '생성 중',
+      failed: '실패',
+      skipped: '자료 부족',
+      stale: '구버전',
+    }[k] ?? k);
+  }
+  function jobLabel(k) {
+    return ({
+      'completed': '완료',
+      'pending': '대기',
+      'processing': '처리 중',
+      'failed:guard_fail': '환각 차단',
+      'failed:parse_fail': '파싱 실패',
+      'failed:llm_timeout': 'LLM timeout',
+      'failed:unknown': '알 수 없음',
+      'skipped:evidence_missing': '자료 없음 skip',
+    }[k] ?? k);
+  }
+
   let totalQ = $derived(stats?.questions?.total ?? 0);
   let attempted = $derived(stats?.questions?.attempted ?? 0);
   let attemptedPct = $derived(totalQ > 0 ? Math.round((attempted / totalQ) * 100) : 0);
@@ -298,6 +321,58 @@
         {/snippet}
       </Card>
 
+      <!-- 6.5 Phase 4-A: AI 풀이 캐시 진척 + 최근 7일 worker 결과 -->
+      {#if stats.ai_explanation}
+        {@const ae = stats.ai_explanation}
+        {@const targetPct = ae.target_total > 0 ? Math.round((ae.target_ready / ae.target_total) * 100) : 0}
+        <Card>
+          {#snippet children()}
+            <div class="p-5 flex flex-col gap-3">
+              <div class="flex items-center gap-2">
+                <Sparkles size={14} class="text-accent" />
+                <h2 class="text-sm font-semibold text-text">AI 풀이 캐시</h2>
+              </div>
+
+              <!-- 핵심 진척: wrong/unsure 중 ready 비율 -->
+              {#if ae.target_total > 0}
+                <div class="flex items-baseline gap-3">
+                  <span class="text-2xl font-semibold text-text">{ae.target_ready}</span>
+                  <span class="text-sm text-dim">/ {ae.target_total} 오답·모르겠음 풀이 준비됨 ({targetPct}%)</span>
+                </div>
+                <div class="h-2 bg-bg/30 rounded-full overflow-hidden">
+                  <div class="h-full bg-success" style="width: {targetPct}%"></div>
+                </div>
+              {:else}
+                <div class="text-xs text-dim">오답·모르겠음 문제가 없습니다.</div>
+              {/if}
+
+              <!-- 토픽 전체 status 분포 -->
+              <div class="text-[11px] text-dim">
+                토픽 전체 풀이 상태:
+                {#each Object.entries(ae.status_distribution).filter(([_,v]) => v > 0) as [k, v], i}
+                  <span>{i > 0 ? ' · ' : ''}{statusLabel(k)} {v}</span>
+                {/each}
+              </div>
+
+              <!-- 최근 7일 worker 결과 분포 (운영 관찰) -->
+              {#if Object.keys(ae.recent_jobs).length > 0}
+                <div class="border-t border-default pt-2 text-[11px] text-dim">
+                  <div class="mb-1">최근 7일 worker:</div>
+                  <ul class="grid grid-cols-2 sm:grid-cols-3 gap-x-3 gap-y-0.5">
+                    {#each Object.entries(ae.recent_jobs) as [k, v]}
+                      <li class="flex justify-between">
+                        <span>{jobLabel(k)}</span>
+                        <span class="text-text">{v}</span>
+                      </li>
+                    {/each}
+                  </ul>
+                </div>
+              {/if}
+            </div>
+          {/snippet}
+        </Card>
+      {/if}
+
       <!-- 6. 과목별 약점 -->
       <Card>
         {#snippet children()}