diff --git a/app/workers/study_session_analysis_worker.py b/app/workers/study_session_analysis_worker.py
index bcbe3a7..7571150 100644
--- a/app/workers/study_session_analysis_worker.py
+++ b/app/workers/study_session_analysis_worker.py
@@ -42,6 +42,9 @@ logger = logging.getLogger(__name__)
 LLM_TIMEOUT_S = 30.0
 # wrong/unsure 5 미만은 분석 의미 X — insufficient_attempts skip
 MIN_ATTEMPTS_FOR_ANALYSIS = 5
+# 큰 세션 (84건 등) 에서 prompt 과대 + LLM timeout 방어. 가장 최근 attempt 기준 cap.
+# plan 가정 5~30건 — 30건이면 prompt 6~8K 자 안에 들어옴.
+MAX_ATTEMPTS_IN_PROMPT = 30
 # 응답 800자 hard cap (말줄임표 포함 ≤ 801)
 SUMMARY_MAX_CHARS = 800
 
@@ -210,8 +213,12 @@ async def run_session_analysis_job(session: AsyncSession, job: StudyQuizSessionJ
             job.completed_at = now()
             return
 
-        # 3. RAG (documents 만, 없어도 호출 진행)
-        questions = [a["question"] for a in valid_attempts]
+        # 3. prompt 입력 cap — 큰 세션 (84건 등) 에서 prompt 과대 방지.
+        # 가장 최근 attempts 우선 (이미 answered_at asc 정렬되어 있어 끝쪽 = 최근)
+        prompt_attempts = valid_attempts[-MAX_ATTEMPTS_IN_PROMPT:]
+
+        # 4. RAG (documents 만, 없어도 호출 진행)
+        questions = [a["question"] for a in prompt_attempts]
         ctx_docs = await gather_session_summary_context(
             session,
             user_id=qs.user_id,
@@ -219,8 +226,8 @@ async def run_session_analysis_job(session: AsyncSession, job: StudyQuizSessionJ
             wrong_unsure_questions=questions,
         )
 
-        # 4. prompt 조립 + MLX
-        prompt = _render_session_summary_prompt(qs, valid_attempts, ctx_docs)
+        # 5. prompt 조립 + MLX
+        prompt = _render_session_summary_prompt(qs, prompt_attempts, ctx_docs)
         ai_client = AIClient()
         try:
             async with get_mlx_gate():