Add scanner diagnostics for zero-candidate trade stalls

2026-02-18 00:11:53 +09:00
38 changed files with 433 additions and 10937 deletions
--- a/.env.example
+++ b/.env.example
@@ -1,82 +1,36 @@
 # ============================================================
 # The Ouroboros — Environment Configuration
 # ============================================================
 # Copy this file to .env and fill in your values.
 # Lines starting with # are comments.
 # ============================================================
 # Korea Investment Securities API
 # ============================================================
 KIS_APP_KEY=your_app_key_here
 KIS_APP_SECRET=your_app_secret_here
 KIS_ACCOUNT_NO=12345678-01
 KIS_BASE_URL=https://openapivts.koreainvestment.com:9443
 # Paper trading (VTS): https://openapivts.koreainvestment.com:29443
 # Live trading:        https://openapi.koreainvestment.com:9443
 KIS_BASE_URL=https://openapivts.koreainvestment.com:29443
 # ============================================================
 # Trading Mode
 # ============================================================
 # paper = 모의투자 (safe for testing), live = 실전투자 (real money)
 MODE=paper
 # daily = batch per session, realtime = per-stock continuous scan
 TRADE_MODE=daily
 # Comma-separated market codes: KR, US, JP, HK, CN, VN
 ENABLED_MARKETS=KR,US
 # Simulated USD cash for paper (VTS) overseas trading.
 # VTS overseas balance API often returns 0; this value is used as fallback.
 # Set to 0 to disable fallback (not used in live mode).
 PAPER_OVERSEAS_CASH=50000.0
 # ============================================================
 # Google Gemini
 # ============================================================
 GEMINI_API_KEY=your_gemini_api_key_here
-# Recommended: gemini-2.0-flash-exp or gemini-1.5-pro
+GEMINI_MODEL=gemini-pro
 GEMINI_MODEL=gemini-2.0-flash-exp
 # ============================================================
 # Risk Management
 # ============================================================
 CIRCUIT_BREAKER_PCT=-3.0
 FAT_FINGER_PCT=30.0
 CONFIDENCE_THRESHOLD=80
 # ============================================================
 # Database
 # ============================================================
 DB_PATH=data/trade_logs.db
-# ============================================================
+# Rate Limiting (requests per second for KIS API)
-# Rate Limiting
+# Reduced to 5.0 to avoid "초당 거래건수 초과" errors (EGW00201)
-# ============================================================
+RATE_LIMIT_RPS=5.0
 # KIS API real limit is ~2 RPS. Keep at 2.0 for maximum safety.
 # Increasing this risks EGW00201 "초당 거래건수 초과" errors.
 RATE_LIMIT_RPS=2.0
-# ============================================================
+# Trading Mode (paper / live)
-# External Data APIs (optional)
+MODE=paper
-# ============================================================
+
 # External Data APIs (optional — for enhanced decision-making)
 # NEWS_API_KEY=your_news_api_key_here
 # NEWS_API_PROVIDER=alphavantage
 # MARKET_DATA_API_KEY=your_market_data_key_here
 # ============================================================
 # Telegram Notifications (optional)
 # ============================================================
 # Get bot token from @BotFather on Telegram
 # Get chat ID from @userinfobot or your chat
 # TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
 # TELEGRAM_CHAT_ID=123456789
 # TELEGRAM_ENABLED=true
 # ============================================================
 # Dashboard (optional)
 # ============================================================
 # DASHBOARD_ENABLED=false
 # DASHBOARD_HOST=127.0.0.1
 # DASHBOARD_PORT=8080
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -94,7 +94,6 @@ Smart Scanner runs in `TRADE_MODE=realtime` only. Daily mode uses static watchli
 - **[Testing](docs/testing.md)** — Test structure, coverage requirements, writing tests
 - **[Agent Policies](docs/agents.md)** — Prime directives, constraints, prohibited actions
 - **[Requirements Log](docs/requirements-log.md)** — User requirements and feedback tracking
 - **[Live Trading Checklist](docs/live-trading-checklist.md)** — 모의→실전 전환 체크리스트
 ## Core Principles
@@ -171,7 +170,7 @@ Markets auto-detected based on timezone and enabled in `ENABLED_MARKETS` env var
 - `src/core/risk_manager.py` is **READ-ONLY** — changes require human approval
 - Circuit breaker at -3.0% P&L — may only be made **stricter**
 - Fat-finger protection: max 30% of cash per order — always enforced
- Confidence 임계값 (market_outlook별, 낮출 수 없음): BEARISH ≥ 90, NEUTRAL/기본 ≥ 80, BULLISH ≥ 75
+- Confidence < 80 → force HOLD — cannot be weakened
 - All code changes → corresponding tests → coverage ≥ 80%
 ## Contributing
--- a/docs/commands.md
+++ b/docs/commands.md
@@ -192,27 +192,6 @@ When `TELEGRAM_COMMANDS_ENABLED=true` (default), the bot accepts these interacti
 Commands are only processed from the authorized `TELEGRAM_CHAT_ID`.
 ## KIS API TR_ID 참조 문서
 **TR_ID를 추가하거나 수정할 때 반드시 공식 문서를 먼저 확인할 것.**
 공식 문서: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx`
 > ⚠️ 커뮤니티 블로그, GitHub 예제 등 비공식 자료의 TR_ID는 오래되거나 틀릴 수 있음.
 > 실제로 `VTTT1006U`(미국 매도 — 잘못됨)가 오랫동안 코드에 남아있던 사례가 있음 (Issue #189).
 ### 주요 TR_ID 목록
 | 구분 | 모의투자 TR_ID | 실전투자 TR_ID | 시트명 |
 |------|---------------|---------------|--------|
 | 해외주식 매수 (미국) | `VTTT1002U` | `TTTT1002U` | 해외주식 주문 |
 | 해외주식 매도 (미국) | `VTTT1001U` | `TTTT1006U` | 해외주식 주문 |
 새로운 TR_ID가 필요할 때:
 1. 위 xlsx 파일에서 해당 거래 유형의 시트를 찾는다.
 2. 모의투자(`VTTT`) / 실전투자(`TTTT`) 컬럼을 구분하여 정확한 값을 사용한다.
 3. 코드에 출처 주석을 남긴다: `# Source: 한국투자증권_오픈API_전체문서 — '<시트명>' 시트`
 ## Environment Setup
 ```bash
--- a/docs/issues/ISSUE-2026-02-17-no-trades-zero-candidates.md
+++ b/docs/issues/ISSUE-2026-02-17-no-trades-zero-candidates.md
@@ -0,0 +1,29 @@
 # Issue: Realtime 모드에서 거래가 지속적으로 0건
 ## Summary
 `realtime` 실행 중 주문 단계까지 진입하지 못하고, 스캐너 단계에서 후보가 0건으로 반복 종료된다.
 ## Observed
 - 로그에서 반복적으로 `Smart Scanner: No candidates ... — no trades` 출력
 - 해외 시장에서 `Overseas ranking endpoint unavailable (404)` 다수 발생
 - fallback 심볼 스캔도 `0 candidates`로 종료
 - `data/trade_logs.db` 기준 최근 구간에 `BUY/SELL` 없음
 ## Impact
 - 매매 전략 품질과 무관하게 주문 경로가 실행되지 않아 실질 거래 불가
 - 장애 원인을 로그만으로 즉시 분해하기 어려움
 ## Root-Cause Hypothesis
 - 스캐너 필터(가격/변동성) 단계에서 대부분 탈락
 - 해외 랭킹 API 불가 시 입력 유니버스가 빈 상태가 되어 후보 생성 실패
 - 기존 로그는 최종 결과(0 candidates)만 보여 원인별 분해가 어려움
 ## Acceptance Criteria
 - 스캔 1회마다 탈락 사유가 구조화되어 로그에 남아야 함
 - 국내/해외(랭킹/폴백) 경로 모두 동일한 진단 지표를 제공해야 함
 - 운영자가 로그만 보고 `왜 0 candidates인지`를 즉시 판단 가능해야 함
 ## Scope
 - 이번 이슈는 **진단 가능성 개선(Observability)** 에 한정
 - 후보 생성 전략 변경(기본 유니버스 강제 추가 등)은 별도 이슈로 분리
--- a/docs/live-trading-checklist.md
+++ b/docs/live-trading-checklist.md
@@ -1,131 +0,0 @@
 # 실전 전환 체크리스트
 모의 거래(paper)에서 실전(live)으로 전환하기 전에 아래 항목을 **순서대로** 모두 확인하세요.
 ---
 ## 1. 사전 조건
 ### 1-1. KIS OpenAPI 실전 계좌 준비
 - [ ] 한국투자증권 계좌 개설 완료 (일반 위탁 계좌)
 - [ ] OpenAPI 실전 사용 신청 (KIS 홈페이지 → Open API → 서비스 신청)
 - [ ] 실전용 APP_KEY / APP_SECRET 발급 완료
 - [ ] KIS_ACCOUNT_NO 형식 확인: `XXXXXXXX-XX` (8자리-2자리)
 ### 1-2. 리스크 파라미터 검토
 - [ ] `CIRCUIT_BREAKER_PCT` 확인: 기본값 -3.0% (더 엄격하게 조정 권장)
 - [ ] `FAT_FINGER_PCT` 확인: 기본값 30.0% (1회 주문 최대 잔고 대비 %)
 - [ ] `CONFIDENCE_THRESHOLD` 확인: BEARISH ≥ 90, NEUTRAL ≥ 80, BULLISH ≥ 75
 - [ ] 초기 투자금 결정 및 해외 주식 운용 한도 설정
 ### 1-3. 시스템 요건
 - [ ] 커버리지 80% 이상 유지 확인: `pytest --cov=src`
 - [ ] 타입 체크 통과: `mypy src/ --strict`
 - [ ] Lint 통과: `ruff check src/ tests/`
 ---
 ## 2. 환경 설정
 ### 2-1. `.env` 파일 수정
 ```bash
 # 1. KIS 실전 URL로 변경 (모의: openapivts 포트 29443)
 KIS_BASE_URL=https://openapi.koreainvestment.com:9443
 # 2. 실전 APP_KEY / APP_SECRET으로 교체
 KIS_APP_KEY=<실전_APP_KEY>
 KIS_APP_SECRET=<실전_APP_SECRET>
 KIS_ACCOUNT_NO=<실전_계좌번호>
 # 3. 모드를 live로 변경
 MODE=live
 # 4. PAPER_OVERSEAS_CASH 비활성화 (live 모드에선 무시되지만 명시적으로 0 설정)
 PAPER_OVERSEAS_CASH=0
 ```
 > ⚠️ `KIS_BASE_URL` 포트 주의:
 > - **모의(VTS)**: `https://openapivts.koreainvestment.com:29443`
 > - **실전**: `https://openapi.koreainvestment.com:9443`
 ### 2-2. TR_ID 자동 분기 확인
 아래 TR_ID는 `MODE` 값에 따라 코드에서 **자동으로 선택**됩니다.
 별도 설정 불필요하나, 문제 발생 시 아래 표를 참조하세요.
 | 구분 | 모의 TR_ID | 실전 TR_ID |
 |------|-----------|-----------|
 | 국내 잔고 조회 | `VTTC8434R` | `TTTC8434R` |
 | 국내 현금 매수 | `VTTC0012U` | `TTTC0012U` |
 | 국내 현금 매도 | `VTTC0011U` | `TTTC0011U` |
 | 해외 잔고 조회 | `VTTS3012R` | `TTTS3012R` |
 | 해외 매수 | `VTTT1002U` | `TTTT1002U` |
 | 해외 매도 | `VTTT1001U` | `TTTT1006U` |
 > **출처**: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx` (공식 문서 기준)
 ---
 ## 3. 최종 확인
 ### 3-1. 실전 시작 전 점검
 - [ ] DB 백업 완료: `data/trade_logs.db` → `data/backups/`
 - [ ] Telegram 알림 설정 확인 (실전에서는 알림이 더욱 중요)
 - [ ] 소액으로 첫 거래 진행 후 TR_ID/계좌 정상 동작 확인
 ### 3-2. 실행 명령
 ```bash
 # 실전 모드로 실행
 python -m src.main --mode=live
 # 대시보드 함께 실행 (별도 터미널에서 모니터링)
 python -m src.main --mode=live --dashboard
 ```
 ### 3-3. 실전 시작 직후 확인 사항
 - [ ] 로그에 `MODE=live` 출력 확인
 - [ ] 첫 잔고 조회 성공 (ConnectionError 없음)
 - [ ] Telegram 알림 수신 확인 ("System started")
 - [ ] 첫 주문 후 KIS 앱에서 체결 내역 확인
 ---
 ## 4. 비상 정지 방법
 ### 즉각 정지
 ```bash
 # 터미널에서 Ctrl+C (정상 종료 트리거)
 # 또는 Telegram 봇 명령:
 /stop
 ```
 ### Circuit Breaker 발동 시
 - CB가 발동되면 자동으로 거래 중단 및 Telegram 알림 전송
 - CB 임계값: `CIRCUIT_BREAKER_PCT` (기본 -3.0%)
 - **임계값은 엄격하게만 조정 가능** (더 낮은 음수 값으로만 변경)
 ---
 ## 5. 롤백 절차
 실전 전환 후 문제 발생 시:
 ```bash
 # 1. 즉시 .env에서 MODE=paper로 복원
 # 2. 재시작
 python -m src.main --mode=paper
 # 3. DB에서 최근 거래 확인
 sqlite3 data/trade_logs.db "SELECT * FROM trades ORDER BY id DESC LIMIT 20;"
 ```
 ---
 ## 관련 문서
 - [시스템 아키텍처](architecture.md)
 - [워크플로우 가이드](workflow.md)
 - [재해 복구](disaster_recovery.md)
 - [Agent 제약 조건](agents.md)
--- a/docs/prs/PR-2026-02-17-scanner-diagnostics-for-zero-candidates.md
+++ b/docs/prs/PR-2026-02-17-scanner-diagnostics-for-zero-candidates.md
@@ -0,0 +1,32 @@
 # PR: Smart Scanner 진단 로그 추가 (0 candidates 원인 분해)
 ## Linked Issue
 - `docs/issues/ISSUE-2026-02-17-no-trades-zero-candidates.md`
 ## What Changed
 - `src/analysis/smart_scanner.py`에 스캔 진단 카운터 추가
 - 국내 스캔 진단 로그 추가
 - 해외 랭킹 스캔 진단 로그 추가
 - 해외 fallback 심볼 스캔 진단 로그 추가
 ## Diagnostics Keys
 - `total_rows`
 - `missing_code`
 - `invalid_price`
 - `low_volatility`
 - `connection_error` (해당 경로에서만)
 - `unexpected_error` (해당 경로에서만)
 - `qualified`
 ## Expected Log Examples
 - `Domestic scan diagnostics: {...}`
 - `Overseas ranking scan diagnostics for US_NASDAQ: {...}`
 - `Overseas fallback scan diagnostics for US_NYSE: {...}`
 ## Out of Scope
 - 해외 랭킹 404 시 기본 심볼 유니버스 강제 주입
 - 국내 경로 fallback 정책 변경
 ## Validation
 - `.venv/bin/python -m py_compile src/analysis/smart_scanner.py`
--- a/docs/requirements-log.md
+++ b/docs/requirements-log.md
@@ -7,32 +7,6 @@
 ---
 ## 2026-02-21
 ### 거래 상태 확인 중 발견된 버그 (#187)
 - 거래 상태 점검 요청 → SELL 주문(손절/익절)이 Fat Finger에 막혀 전혀 실행 안 됨 발견
 - **#187 (Critical)**: SELL 주문에서 Fat Finger 오탐 — `order_amount/total_cash > 30%`가 SELL에도 적용되어 대형 포지션 매도 불가
  - JELD stop-loss -6.20% → 차단, RXT take-profit +46.13% → 차단
  - 수정: SELL은 `check_circuit_breaker`만 호출, `validate_order`(Fat Finger 포함) 미호출
 ---
 ## 2026-02-20
 ### 지속적 모니터링 및 개선점 도출 (이슈 #178~#182)
 - Dashboard 포함해서 실행하며 간헐적 문제 모니터링 및 개선점 자동 도출 요청
 - 모니터링 결과 발견된 이슈 목록:
  - **#178**: uvicorn 미설치 → dashboard 미작동 + 오해의 소지 있는 시작 로그 → uvicorn 설치 완료
  - **#179 (Critical)**: 잔액 부족 주문 실패 후 매 사이클마다 무한 재시도 (MLECW 20분 이상 반복)
  - **#180**: 다중 인스턴스 실행 시 Telegram 409 충돌
  - **#181**: implied_rsi 공식 포화 문제 (change_rate≥12.5% → RSI=100)
  - **#182 (Critical)**: 보유 종목이 SmartScanner 변동성 필터에 걸려 SELL 신호 미생성 → SELL 체결 0건, 잔고 소진
 - 요구사항: 모니터링 자동화 및 주기적 개선점 리포트 도출
 ---
 ## 2026-02-05
 ### API 효율화
@@ -191,167 +165,3 @@
 **효과:**
 - 국내/해외 스캐너 기준이 변동성 중심으로 일관화
 - 고변동 구간에서 자동 익스포저 축소, 저변동 구간에서 과소진입 완화
 ## 2026-02-18
 ### KIS 해외 랭킹 API 404 에러 수정
 **배경:**
 - KIS 해외주식 랭킹 API(`fetch_overseas_rankings`)가 모든 거래소에서 HTTP 404를 반환
 - Smart Scanner가 해외 시장 후보 종목을 찾지 못해 거래가 전혀 실행되지 않음
 **근본 원인:**
 - TR_ID, API 경로, 거래소 코드가 모두 KIS 공식 문서와 불일치
 **구현 결과:**
 - `src/config.py`: TR_ID/Path 기본값을 KIS 공식 스펙으로 수정
 - `src/broker/overseas.py`: 랭킹 API 전용 거래소 코드 매핑 추가 (NASD→NAS, NYSE→NYS, AMEX→AMS), 올바른 API 파라미터 사용
 - `tests/test_overseas_broker.py`: 19개 단위 테스트 추가
 **효과:**
 - 해외 시장 랭킹 스캔이 정상 동작하여 Smart Scanner가 후보 종목 탐지 가능
 ### Gemini prompt_override 미적용 버그 수정
 **배경:**
 - `run_overnight` 실행 시 모든 시장에서 Playbook 생성 실패 (`JSONDecodeError`)
 - defensive playbook으로 폴백되어 모든 종목이 HOLD 처리
 **근본 원인:**
 - `pre_market_planner.py`가 `market_data["prompt_override"]`에 Playbook 전용 프롬프트를 넣어 `gemini.decide()` 호출
 - `gemini_client.py`의 `decide()` 메서드가 `prompt_override` 키를 전혀 확인하지 않고 항상 일반 트레이드 결정 프롬프트 생성
 - Gemini가 Playbook JSON 대신 일반 트레이드 결정을 반환하여 파싱 실패
 **구현 결과:**
 - `src/brain/gemini_client.py`: `decide()` 메서드에서 `prompt_override` 우선 사용 로직 추가
 - `tests/test_brain.py`: 3개 테스트 추가 (override 전달, optimization 우회, 미지정 시 기존 동작 유지)
 **이슈/PR:** #143
 ### 미국장 거래 미실행 근본 원인 분석 및 수정 (자율 실행 세션)
 **배경:**
 - 사용자 요청: "미국장 열면 프로그램 돌려서 거래 한 번도 못 한 거 꼭 원인 찾아서 해결해줘"
 - 프로그램을 미국장 개장(9:30 AM EST) 전부터 실행하여 실시간 로그를 분석
 **발견된 근본 원인 #1: Defensive Playbook — BUY 조건 없음**
 - Gemini free tier (20 RPD) 소진 → `generate_playbook()` 실패 → `_defensive_playbook()` 폴백
 - Defensive playbook은 `price_change_pct_below: -3.0 → SELL` 조건만 존재, BUY 조건 없음
 - ScenarioEngine이 항상 HOLD 반환 → 거래 0건
 **수정 #1 (PR #146, Issue #145):**
 - `src/strategy/pre_market_planner.py`: `_smart_fallback_playbook()` 메서드 추가
  - 스캐너 signal 기반 BUY 조건 생성: `momentum → volume_ratio_above`, `oversold → rsi_below`
  - 기존 defensive stop-loss SELL 조건 유지
 - Gemini 실패 시 defensive → smart fallback으로 전환
 - 테스트 10개 추가
 **발견된 근본 원인 #2: 가격 API 거래소 코드 불일치 + VTS 잔고 API 오류**
 실제 로그:
 ```
 Scenario matched for MRNX: BUY (confidence=80)  ✓
 Decision for EWUS (NYSE American): BUY (confidence=80)  ✓
 Skip BUY APLZ (NYSE American): no affordable quantity (cash=0.00, price=0.00)  ✗
 ```
 - `get_overseas_price()`: `NASD`/`NYSE`/`AMEX` 전송 → API가 `NAS`/`NYS`/`AMS` 기대 → 빈 응답 → `price=0`
 - `VTTS3012R` 잔고 API: "ERROR : INPUT INVALID_CHECK_ACNO" → `total_cash=0`
 - 결과: `_determine_order_quantity()` 가 0 반환 → 주문 건너뜀
 **수정 #2 (PR #148, Issue #147):**
 - `src/broker/overseas.py`: `_PRICE_EXCHANGE_MAP = _RANKING_EXCHANGE_MAP` 추가, 가격 API에 매핑 적용
 - `src/config.py`: `PAPER_OVERSEAS_CASH: float = Field(default=50000.0)` — paper 모드 시뮬레이션 잔고
 - `src/main.py`: 잔고 0일 때 PAPER_OVERSEAS_CASH 폴백, 가격 0일 때 candidate.price 폴백
 - 테스트 8개 추가
 **효과:**
 - BUY 결정 → 실제 주문 전송까지의 파이프라인이 완전히 동작
 - Paper 모드에서 KIS VTS 해외 잔고 API 오류에 관계없이 시뮬레이션 거래 가능
 **이슈/PR:** #145, #146, #147, #148
 ### 해외주식 시장가 주문 거부 수정 (Fix #3, 연속 발견)
 **배경:**
 - Fix #147 적용 후 주문 전송 시작 → KIS VTS가 거부: "지정가만 가능한 상품입니다"
 **근본 원인:**
 - `trading_cycle()`, `run_daily_session()` 양쪽에서 `send_overseas_order(price=0.0)` 하드코딩
 - `price=0` → `ORD_DVSN="01"` (시장가) 전송 → KIS VTS 거부
 - Fix #147에서 이미 `current_price`를 올바르게 계산했으나 주문 시 미사용
 **구현 결과:**
 - `src/main.py`: 두 곳에서 `price=0.0` → `price=current_price`/`price=stock_data["current_price"]`
 - `tests/test_main.py`: 회귀 테스트 `test_overseas_buy_order_uses_limit_price` 추가
 **최종 확인 로그:**
 ```
 Order result: 모의투자 매수주문이 완료 되었습니다.  ✓
 ```
 **이슈/PR:** #149, #150
 ---
 ## 2026-02-23
 ### 국내주식 지정가 전환 및 미체결 처리 (#232)
 **배경:**
 - 해외주식은 #211에서 지정가로 전환했으나 국내주식은 여전히 `price=0` (시장가)
 - KRX도 지정가 주문 사용 시 동일한 미체결 위험이 존재
 - 지정가 전환 + 미체결 처리를 함께 구현
 **구현 내용:**
 1. `src/broker/kis_api.py`
   - `get_domestic_pending_orders()`: 모의 즉시 `[]`, 실전 `TTTC0084R` GET
   - `cancel_domestic_order()`: 실전 `TTTC0013U` / 모의 `VTTC0013U`, hashkey 필수
 2. `src/main.py`
   - import `kr_round_down` 추가
   - `trading_cycle`, `run_daily_session` 국내 주문 `price=0` → 지정가:
     BUY +0.2% / SELL -0.2%, `kr_round_down` KRX 틱 반올림 적용
   - `handle_domestic_pending_orders` 함수: BUY→취소+쿨다운, SELL→취소+재주문(-0.4%, 최대1회)
   - daily/realtime 두 모드에서 domestic pending 체크 호출 추가
 3. 테스트 14개 추가:
   - `TestGetDomesticPendingOrders` (3), `TestCancelDomesticOrder` (5)
   - `TestHandleDomesticPendingOrders` (4), `TestDomesticLimitOrderPrice` (2)
 **이슈/PR:** #232, PR #233
 ---
 ## 2026-02-24
 ### 해외잔고 ghost position 수정 — '모의투자 잔고내역이 없습니다' 반복 방지 (#235)
 **배경:**
 - 모의투자 실행 시 MLECW, KNRX, NBY, SNSE 등 만료/정지된 종목에 대해
  `모의투자 잔고내역이 없습니다` 오류가 매 사이클 반복됨
 **근본 원인:**
 1. `ovrs_cblc_qty` (해외잔고수량, 총 보유) vs `ord_psbl_qty` (주문가능수량, 실제 매도 가능)
   - 기존 코드: `ovrs_cblc_qty` 우선 사용 → 만료 Warrant가 `ovrs_cblc_qty=289456`이지만 실제 `ord_psbl_qty=0`
   - startup sync / build_overseas_symbol_universe가 이 종목들을 포지션으로 기록
 2. SELL 실패 시 DB 포지션이 닫히지 않아 다음 사이클에서도 재시도 (무한 반복)
 **구현 내용:**
 1. `src/main.py` — `_extract_held_codes_from_balance`, `_extract_held_qty_from_balance`
   - 해외 잔고 필드 우선순위 변경: `ord_psbl_qty` → `ovrs_cblc_qty` → `hldg_qty` (fallback 유지)
   - KIS 공식 문서(VTTS3012R) 기준: `ord_psbl_qty`가 실제 매도 가능 수량
 2. `src/main.py` — `trading_cycle` ghost-close 처리
   - 해외 SELL이 `잔고내역이 없습니다`로 실패 시 DB 포지션을 `[ghost-close]` SELL로 종료
   - exchange code 불일치 등 예외 상황에서 무한 반복 방지
 3. 테스트 7개 추가:
   - `TestExtractHeldQtyFromBalance` 3개: ord_psbl_qty 우선, 0이면 0 반환, fallback
   - `TestExtractHeldCodesFromBalance` 2개: ord_psbl_qty=0인 종목 제외, fallback
   - `TestOverseasGhostPositionClose` 2개: ghost-close 로그 확인, 일반 오류 무시
 **이슈/PR:** #235, PR #236
--- a/scripts/run_overnight.sh
+++ b/scripts/run_overnight.sh
@@ -23,7 +23,7 @@ if [ -z "${APP_CMD:-}" ]; then
    dashboard_port="${DASHBOARD_PORT:-8080}"
-    APP_CMD="DASHBOARD_PORT=$dashboard_port $PYTHON_BIN -m src.main --mode=live --dashboard"
+    APP_CMD="DASHBOARD_PORT=$dashboard_port $PYTHON_BIN -m src.main --mode=paper --dashboard"
 fi
 mkdir -p "$LOG_DIR"
--- a/src/analysis/smart_scanner.py
+++ b/src/analysis/smart_scanner.py
@@ -128,6 +128,16 @@ class SmartVolatilityScanner:
        if not fluct_rows:
            return []
        diagnostics: dict[str, int | float] = {
            "total_rows": len(fluct_rows),
            "missing_code": 0,
            "invalid_price": 0,
            "low_volatility": 0,
            "connection_error": 0,
            "unexpected_error": 0,
            "qualified": 0,
        }
        volume_rank_bonus: dict[str, float] = {}
        for idx, row in enumerate(volume_rows):
            code = _extract_stock_code(row)
@@ -139,6 +149,7 @@ class SmartVolatilityScanner:
        for stock in fluct_rows:
            stock_code = _extract_stock_code(stock)
            if not stock_code:
                diagnostics["missing_code"] += 1
                continue
            try:
@@ -168,14 +179,18 @@ class SmartVolatilityScanner:
                            volume_ratio = max(volume_ratio, volume / prev_day_volume)
                volatility_pct = max(abs(change_rate), intraday_range_pct)
-                if price <= 0 or volatility_pct < 0.8:
+                if price <= 0:
                    diagnostics["invalid_price"] += 1
                    continue
                if volatility_pct < 0.8:
                    diagnostics["low_volatility"] += 1
                    continue
                volatility_score = min(volatility_pct / 10.0, 1.0) * 85.0
                liquidity_score = volume_rank_bonus.get(stock_code, 0.0)
                score = min(100.0, volatility_score + liquidity_score)
                signal = "momentum" if change_rate >= 0 else "oversold"
-                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
+                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
                candidates.append(
                    ScanCandidate(
@@ -189,14 +204,22 @@ class SmartVolatilityScanner:
                        score=score,
                    )
                )
                diagnostics["qualified"] += 1
            except ConnectionError as exc:
                diagnostics["connection_error"] += 1
                logger.warning("Failed to analyze %s: %s", stock_code, exc)
                continue
            except Exception as exc:
                diagnostics["unexpected_error"] += 1
                logger.error("Unexpected error analyzing %s: %s", stock_code, exc)
                continue
        logger.info(
            "Domestic scan diagnostics: %s (volatility_threshold=0.8, top_n=%d)",
            diagnostics,
            self.top_n,
        )
        logger.info("Domestic ranking scan found %d candidates", len(candidates))
        candidates.sort(key=lambda c: c.score, reverse=True)
        return candidates[: self.top_n]
@@ -242,6 +265,14 @@ class SmartVolatilityScanner:
        if not fluct_rows:
            return []
        diagnostics: dict[str, int | float] = {
            "total_rows": len(fluct_rows),
            "missing_code": 0,
            "invalid_price": 0,
            "low_volatility": 0,
            "qualified": 0,
        }
        volume_rank_bonus: dict[str, float] = {}
        try:
            volume_rows = await self.overseas_broker.fetch_overseas_rankings(
@@ -266,6 +297,7 @@ class SmartVolatilityScanner:
        for row in fluct_rows:
            stock_code = _extract_stock_code(row)
            if not stock_code:
                diagnostics["missing_code"] += 1
                continue
            price = _extract_last_price(row)
@@ -275,14 +307,18 @@ class SmartVolatilityScanner:
            volatility_pct = max(abs(change_rate), intraday_range_pct)
            # Volatility-first filter (not simple gainers/value ranking).
-            if price <= 0 or volatility_pct < 0.8:
+            if price <= 0:
                diagnostics["invalid_price"] += 1
                continue
            if volatility_pct < 0.8:
                diagnostics["low_volatility"] += 1
                continue
            volatility_score = min(volatility_pct / 10.0, 1.0) * 85.0
            liquidity_score = volume_rank_bonus.get(stock_code, 0.0)
            score = min(100.0, volatility_score + liquidity_score)
            signal = "momentum" if change_rate >= 0 else "oversold"
-            implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
+            implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
            candidates.append(
                ScanCandidate(
                    stock_code=stock_code,
@@ -295,7 +331,14 @@ class SmartVolatilityScanner:
                    score=score,
                )
            )
            diagnostics["qualified"] += 1
        logger.info(
            "Overseas ranking scan diagnostics for %s: %s (volatility_threshold=0.8, top_n=%d)",
            market.code,
            diagnostics,
            self.top_n,
        )
        if candidates:
            logger.info(
                "Overseas ranking scan found %d candidates for %s",
@@ -320,6 +363,14 @@ class SmartVolatilityScanner:
            len(symbols),
            market.name,
        )
        diagnostics: dict[str, int | float] = {
            "total_rows": len(symbols),
            "invalid_price": 0,
            "low_volatility": 0,
            "connection_error": 0,
            "unexpected_error": 0,
            "qualified": 0,
        }
        candidates: list[ScanCandidate] = []
        for stock_code in symbols:
            try:
@@ -333,12 +384,16 @@ class SmartVolatilityScanner:
                intraday_range_pct = _extract_intraday_range_pct(output, price)
                volatility_pct = max(abs(change_rate), intraday_range_pct)
-                if price <= 0 or volatility_pct < 0.8:
+                if price <= 0:
                    diagnostics["invalid_price"] += 1
                    continue
                if volatility_pct < 0.8:
                    diagnostics["low_volatility"] += 1
                    continue
                score = min(volatility_pct / 10.0, 1.0) * 100.0
                signal = "momentum" if change_rate >= 0 else "oversold"
-                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
+                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
                candidates.append(
                    ScanCandidate(
                        stock_code=stock_code,
@@ -351,10 +406,19 @@ class SmartVolatilityScanner:
                        score=score,
                    )
                )
                diagnostics["qualified"] += 1
            except ConnectionError as exc:
                diagnostics["connection_error"] += 1
                logger.warning("Failed to analyze overseas %s: %s", stock_code, exc)
            except Exception as exc:
                diagnostics["unexpected_error"] += 1
                logger.error("Unexpected error analyzing overseas %s: %s", stock_code, exc)
        logger.info(
            "Overseas fallback scan diagnostics for %s: %s (volatility_threshold=0.8, top_n=%d)",
            market.code,
            diagnostics,
            self.top_n,
        )
        logger.info(
            "Overseas symbol fallback scan found %d candidates for %s",
            len(candidates),
--- a/src/brain/gemini_client.py
+++ b/src/brain/gemini_client.py
@@ -346,10 +346,8 @@ class GeminiClient:
        # Validate required fields
        if not all(k in data for k in ("action", "confidence", "rationale")):
            logger.warning("Missing fields in Gemini response — defaulting to HOLD")
            # Preserve raw text in rationale so prompt_override callers (e.g. pre_market_planner)
            # can extract their own JSON format from decision.rationale (#245)
            return TradeDecision(
-                action="HOLD", confidence=0, rationale=raw
+                action="HOLD", confidence=0, rationale="Missing required fields"
            )
        action = str(data["action"]).upper()
@@ -412,10 +410,8 @@ class GeminiClient:
                    cached=True,
                )
-        # Build prompt (prompt_override takes priority for callers like pre_market_planner)
+        # Build optimized prompt
-        if "prompt_override" in market_data:
+        if self._enable_optimization:
            prompt = market_data["prompt_override"]
        elif self._enable_optimization:
            prompt = self._optimizer.build_compressed_prompt(market_data)
        else:
            prompt = await self.build_prompt(market_data, news_sentiment)
@@ -441,18 +437,6 @@ class GeminiClient:
                action="HOLD", confidence=0, rationale=f"API error: {exc}", token_count=token_count
            )
        # prompt_override callers (e.g. pre_market_planner) expect raw text back,
        # not a parsed TradeDecision. Skip parse_response to avoid spurious
        # "Missing fields" warnings and return the raw response directly. (#247)
        if "prompt_override" in market_data:
            logger.info(
                "Gemini raw response received (prompt_override, tokens=%d)", token_count
            )
            # Not a trade decision — don't inflate _total_decisions metrics
            return TradeDecision(
                action="HOLD", confidence=0, rationale=raw, token_count=token_count
            )
        decision = self.parse_response(raw)
        self._total_decisions += 1
--- a/src/brain/prompt_optimizer.py
+++ b/src/brain/prompt_optimizer.py
@@ -179,8 +179,8 @@ class PromptOptimizer:
            # Minimal instructions
            prompt = (
                f"{market_name} trader. Analyze:\n{data_str}\n\n"
-                'Return JSON: {"action":"BUY"|"SELL"|"HOLD","confidence":<0-100>,"rationale":"<text>"}\n'
+                'Return JSON: {"act":"BUY"|"SELL"|"HOLD","conf":<0-100>,"reason":"<text>"}\n'
-                "Rules: action=BUY/SELL/HOLD, confidence=0-100, rationale=concise. No markdown."
+                "Rules: act=BUY/SELL/HOLD, conf=0-100, reason=concise. No markdown."
            )
        else:
            # Data only (for cached contexts where instructions are known)
--- a/src/broker/kis_api.py
+++ b/src/broker/kis_api.py
@@ -8,7 +8,7 @@ from __future__ import annotations
 import asyncio
 import logging
 import ssl
-from typing import Any, cast
+from typing import Any
 import aiohttp
@@ -20,39 +20,6 @@ _KIS_VTS_HOST = "openapivts.koreainvestment.com"
 logger = logging.getLogger(__name__)
 def kr_tick_unit(price: float) -> int:
    """Return KRX tick size for the given price level.
    KRX price tick rules (domestic stocks):
        price < 2,000        →   1원
        2,000  ≤ price < 5,000     →   5원
        5,000  ≤ price < 20,000    →  10원
        20,000 ≤ price < 50,000    →  50원
        50,000 ≤ price < 200,000   → 100원
        200,000 ≤ price < 500,000  → 500원
        500,000 ≤ price            → 1,000원
    """
    if price < 2_000:
        return 1
    if price < 5_000:
        return 5
    if price < 20_000:
        return 10
    if price < 50_000:
        return 50
    if price < 200_000:
        return 100
    if price < 500_000:
        return 500
    return 1_000
 def kr_round_down(price: float) -> int:
    """Round *down* price to the nearest KRX tick unit."""
    tick = kr_tick_unit(price)
    return int(price // tick * tick)
 class LeakyBucket:
    """Simple leaky-bucket rate limiter for async code."""
@@ -231,64 +198,12 @@ class KISBroker:
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(f"Network error fetching orderbook: {exc}") from exc
    async def get_current_price(
        self, stock_code: str
    ) -> tuple[float, float, float]:
        """Fetch current price data for a domestic stock.
        Uses the ``inquire-price`` API (FHKST01010100), which works in both
        real and VTS environments and returns the actual last-traded price.
        Returns:
            (current_price, prdy_ctrt, frgn_ntby_qty)
            - current_price: Last traded price in KRW.
            - prdy_ctrt: Day change rate (%).
            - frgn_ntby_qty: Foreigner net buy quantity.
        """
        await self._rate_limiter.acquire()
        session = self._get_session()
        headers = await self._auth_headers("FHKST01010100")
        params = {
            "FID_COND_MRKT_DIV_CODE": "J",
            "FID_INPUT_ISCD": stock_code,
        }
        url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/inquire-price"
        def _f(val: str | None) -> float:
            try:
                return float(val or "0")
            except ValueError:
                return 0.0
        try:
            async with session.get(url, headers=headers, params=params) as resp:
                if resp.status != 200:
                    text = await resp.text()
                    raise ConnectionError(
                        f"get_current_price failed ({resp.status}): {text}"
                    )
                data = await resp.json()
                out = data.get("output", {})
                return (
                    _f(out.get("stck_prpr")),
                    _f(out.get("prdy_ctrt")),
                    _f(out.get("frgn_ntby_qty")),
                )
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error fetching current price: {exc}"
            ) from exc
    async def get_balance(self) -> dict[str, Any]:
        """Fetch current account balance and holdings."""
        await self._rate_limiter.acquire()
        session = self._get_session()
-        # TR_ID: 실전 TTTC8434R, 모의 VTTC8434R
+        headers = await self._auth_headers("VTTC8434R")  # 모의투자 잔고조회
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '국내주식 잔고조회' 시트
        tr_id = "TTTC8434R" if self._settings.MODE == "live" else "VTTC8434R"
        headers = await self._auth_headers(tr_id)
        params = {
            "CANO": self._account_no,
            "ACNT_PRDT_CD": self._product_cd,
@@ -333,30 +248,14 @@ class KISBroker:
        await self._rate_limiter.acquire()
        session = self._get_session()
-        # TR_ID: 실전 BUY=TTTC0012U SELL=TTTC0011U, 모의 BUY=VTTC0012U SELL=VTTC0011U
+        tr_id = "VTTC0802U" if order_type == "BUY" else "VTTC0801U"
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식주문(현금)' 시트
        # ※ TTTC0802U/VTTC0802U는 미수매수(증거금40% 계좌 전용) — 현금주문에 사용 금지
        if self._settings.MODE == "live":
            tr_id = "TTTC0012U" if order_type == "BUY" else "TTTC0011U"
        else:
            tr_id = "VTTC0012U" if order_type == "BUY" else "VTTC0011U"
        # KRX requires limit orders to be rounded down to the tick unit.
        # ORD_DVSN: "00"=지정가, "01"=시장가
        if price > 0:
            ord_dvsn = "00"  # 지정가
            ord_price = kr_round_down(price)
        else:
            ord_dvsn = "01"  # 시장가
            ord_price = 0
        body = {
            "CANO": self._account_no,
            "ACNT_PRDT_CD": self._product_cd,
            "PDNO": stock_code,
-            "ORD_DVSN": ord_dvsn,
+            "ORD_DVSN": "01" if price > 0 else "06",  # 01=지정가, 06=시장가
            "ORD_QTY": str(quantity),
-            "ORD_UNPR": str(ord_price),
+            "ORD_UNPR": str(price),
        }
        hash_key = await self._get_hash_key(body)
@@ -405,46 +304,26 @@ class KISBroker:
        await self._rate_limiter.acquire()
        session = self._get_session()
-        if ranking_type == "volume":
+        # TR_ID for volume ranking
-            # 거래량순위: FHPST01710000 / /quotations/volume-rank
+        tr_id = "FHPST01710000" if ranking_type == "volume" else "FHPST01710100"
            tr_id = "FHPST01710000"
            url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/volume-rank"
            params: dict[str, str] = {
                "FID_COND_MRKT_DIV_CODE": "J",
                "FID_COND_SCR_DIV_CODE": "20171",
                "FID_INPUT_ISCD": "0000",
                "FID_DIV_CLS_CODE": "0",
                "FID_BLNG_CLS_CODE": "0",
                "FID_TRGT_CLS_CODE": "111111111",
                "FID_TRGT_EXLS_CLS_CODE": "0000000000",
                "FID_INPUT_PRICE_1": "0",
                "FID_INPUT_PRICE_2": "0",
                "FID_VOL_CNT": "0",
                "FID_INPUT_DATE_1": "",
            }
        else:
            # 등락률순위: FHPST01700000 / /ranking/fluctuation (소문자 파라미터)
            tr_id = "FHPST01700000"
            url = f"{self._base_url}/uapi/domestic-stock/v1/ranking/fluctuation"
            params = {
                "fid_cond_mrkt_div_code": "J",
                "fid_cond_scr_div_code": "20170",
                "fid_input_iscd": "0000",
                "fid_rank_sort_cls_code": "0",
                "fid_input_cnt_1": str(limit),
                "fid_prc_cls_code": "0",
                "fid_input_price_1": "0",
                "fid_input_price_2": "0",
                "fid_vol_cnt": "0",
                "fid_trgt_cls_code": "0",
                "fid_trgt_exls_cls_code": "0",
                "fid_div_cls_code": "0",
                "fid_rsfl_rate1": "0",
                "fid_rsfl_rate2": "0",
            }
        headers = await self._auth_headers(tr_id)
        params = {
            "FID_COND_MRKT_DIV_CODE": "J",  # Stock/ETF/ETN
            "FID_COND_SCR_DIV_CODE": "20001",  # Volume surge
            "FID_INPUT_ISCD": "0000",  # All stocks
            "FID_DIV_CLS_CODE": "0",  # All types
            "FID_BLNG_CLS_CODE": "0",
            "FID_TRGT_CLS_CODE": "111111111",
            "FID_TRGT_EXLS_CLS_CODE": "000000",
            "FID_INPUT_PRICE_1": "0",
            "FID_INPUT_PRICE_2": "0",
            "FID_VOL_CNT": "0",
            "FID_INPUT_DATE_1": "",
        }
        url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/volume-rank"
        try:
            async with session.get(url, headers=headers, params=params) as resp:
                if resp.status != 200:
@@ -466,7 +345,7 @@ class KISBroker:
            rankings = []
            for item in data.get("output", [])[:limit]:
                rankings.append({
-                    "stock_code": item.get("stck_shrn_iscd") or item.get("mksc_shrn_iscd", ""),
+                    "stock_code": item.get("mksc_shrn_iscd", ""),
                    "name": item.get("hts_kor_isnm", ""),
                    "price": _safe_float(item.get("stck_prpr", "0")),
                    "volume": _safe_float(item.get("acml_vol", "0")),
@@ -478,112 +357,6 @@ class KISBroker:
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(f"Network error fetching rankings: {exc}") from exc
    async def get_domestic_pending_orders(self) -> list[dict[str, Any]]:
        """Fetch unfilled (pending) domestic limit orders.
        The KIS pending-orders API (TTTC0084R) is unsupported in paper (VTS)
        mode, so this method returns an empty list immediately when MODE is
        not "live".
        Returns:
            List of pending order dicts from the KIS ``output`` field.
            Each dict includes keys such as ``odno``, ``orgn_odno``,
            ``ord_gno_brno``, ``psbl_qty``, ``sll_buy_dvsn_cd``, ``pdno``.
        """
        if self._settings.MODE != "live":
            logger.debug(
                "get_domestic_pending_orders: paper mode — TTTC0084R unsupported, returning []"
            )
            return []
        await self._rate_limiter.acquire()
        session = self._get_session()
        # TR_ID: 실전 TTTC0084R (모의 미지원)
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식 미체결조회' 시트
        headers = await self._auth_headers("TTTC0084R")
        params = {
            "CANO": self._account_no,
            "ACNT_PRDT_CD": self._product_cd,
            "INQR_DVSN_1": "0",
            "INQR_DVSN_2": "0",
            "CTX_AREA_FK100": "",
            "CTX_AREA_NK100": "",
        }
        url = f"{self._base_url}/uapi/domestic-stock/v1/trading/inquire-psbl-rvsecncl"
        try:
            async with session.get(url, headers=headers, params=params) as resp:
                if resp.status != 200:
                    text = await resp.text()
                    raise ConnectionError(
                        f"get_domestic_pending_orders failed ({resp.status}): {text}"
                    )
                data = await resp.json()
                return data.get("output", []) or []
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error fetching domestic pending orders: {exc}"
            ) from exc
    async def cancel_domestic_order(
        self,
        stock_code: str,
        orgn_odno: str,
        krx_fwdg_ord_orgno: str,
        qty: int,
    ) -> dict[str, Any]:
        """Cancel an unfilled domestic limit order.
        Args:
            stock_code: 6-digit domestic stock code (``pdno``).
            orgn_odno: Original order number from pending-orders response
                (``orgn_odno`` field).
            krx_fwdg_ord_orgno: KRX forwarding order branch number from
                pending-orders response (``ord_gno_brno`` field).
            qty: Quantity to cancel (use ``psbl_qty`` from pending order).
        Returns:
            Raw KIS API response dict (check ``rt_cd == "0"`` for success).
        """
        await self._rate_limiter.acquire()
        session = self._get_session()
        # TR_ID: 실전 TTTC0013U, 모의 VTTC0013U
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식주문(정정취소)' 시트
        tr_id = "TTTC0013U" if self._settings.MODE == "live" else "VTTC0013U"
        body = {
            "CANO": self._account_no,
            "ACNT_PRDT_CD": self._product_cd,
            "KRX_FWDG_ORD_ORGNO": krx_fwdg_ord_orgno,
            "ORGN_ODNO": orgn_odno,
            "ORD_DVSN": "00",
            "ORD_QTY": str(qty),
            "ORD_UNPR": "0",
            "RVSE_CNCL_DVSN_CD": "02",
            "QTY_ALL_ORD_YN": "Y",
        }
        hash_key = await self._get_hash_key(body)
        headers = await self._auth_headers(tr_id)
        headers["hashkey"] = hash_key
        url = f"{self._base_url}/uapi/domestic-stock/v1/trading/order-rvsecncl"
        try:
            async with session.post(url, headers=headers, json=body) as resp:
                if resp.status != 200:
                    text = await resp.text()
                    raise ConnectionError(
                        f"cancel_domestic_order failed ({resp.status}): {text}"
                    )
                return cast(dict[str, Any], await resp.json())
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error cancelling domestic order: {exc}"
            ) from exc
    async def get_daily_prices(
        self,
        stock_code: str,
--- a/src/broker/overseas.py
+++ b/src/broker/overseas.py
@@ -12,38 +12,6 @@ from src.broker.kis_api import KISBroker
 logger = logging.getLogger(__name__)
 # Ranking API uses different exchange codes than order/quote APIs.
 _RANKING_EXCHANGE_MAP: dict[str, str] = {
    "NASD": "NAS",
    "NYSE": "NYS",
    "AMEX": "AMS",
    "SEHK": "HKS",
    "SHAA": "SHS",
    "SZAA": "SZS",
    "HSX": "HSX",
    "HNX": "HNX",
    "TSE": "TSE",
 }
 # Price inquiry API (HHDFS00000300) uses the same short exchange codes as rankings.
 # NASD → NAS, NYSE → NYS, AMEX → AMS (confirmed: AMEX returns empty, AMS returns price).
 _PRICE_EXCHANGE_MAP: dict[str, str] = _RANKING_EXCHANGE_MAP
 # Cancel order TR_IDs per exchange code — (live_tr_id, paper_tr_id).
 # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문취소' 시트
 _CANCEL_TR_ID_MAP: dict[str, tuple[str, str]] = {
    "NASD": ("TTTT1004U", "VTTT1004U"),
    "NYSE": ("TTTT1004U", "VTTT1004U"),
    "AMEX": ("TTTT1004U", "VTTT1004U"),
    "SEHK": ("TTTS1003U", "VTTS1003U"),
    "TSE":  ("TTTS0309U", "VTTS0309U"),
    "SHAA": ("TTTS0302U", "VTTS0302U"),
    "SZAA": ("TTTS0306U", "VTTS0306U"),
    "HNX":  ("TTTS0312U", "VTTS0312U"),
    "HSX":  ("TTTS0312U", "VTTS0312U"),
 }
 class OverseasBroker:
    """KIS Overseas Stock API wrapper that reuses KISBroker infrastructure."""
@@ -76,11 +44,9 @@ class OverseasBroker:
        session = self._broker._get_session()
        headers = await self._broker._auth_headers("HHDFS00000300")
        # Map internal exchange codes to the short form expected by the price API.
        price_excd = _PRICE_EXCHANGE_MAP.get(exchange_code, exchange_code)
        params = {
            "AUTH": "",
-            "EXCD": price_excd,
+            "EXCD": exchange_code,
            "SYMB": stock_code,
        }
        url = f"{self._broker._base_url}/uapi/overseas-price/v1/quotations/price"
@@ -104,7 +70,7 @@ class OverseasBroker:
        ranking_type: str = "fluctuation",
        limit: int = 30,
    ) -> list[dict[str, Any]]:
-        """Fetch overseas rankings (price change or volume surge).
+        """Fetch overseas rankings (price change or volume amount).
        Ranking API specs may differ by account/product. Endpoint paths and
        TR_IDs are configurable via settings and can be overridden in .env.
@@ -115,65 +81,66 @@ class OverseasBroker:
        await self._broker._rate_limiter.acquire()
        session = self._broker._get_session()
        ranking_excd = _RANKING_EXCHANGE_MAP.get(exchange_code, exchange_code)
        if ranking_type == "volume":
-            tr_id = self._broker._settings.OVERSEAS_RANKING_VOLUME_TR_ID
+            configured_tr_id = self._broker._settings.OVERSEAS_RANKING_VOLUME_TR_ID
-            path = self._broker._settings.OVERSEAS_RANKING_VOLUME_PATH
+            configured_path = self._broker._settings.OVERSEAS_RANKING_VOLUME_PATH
-            params: dict[str, str] = {
+            default_tr_id = "HHDFS76200200"
-                "KEYB": "",  # NEXT KEY BUFF — Required, 공백
+            default_path = "/uapi/overseas-price/v1/quotations/inquire-volume-rank"
                "AUTH": "",
                "EXCD": ranking_excd,
                "MIXN": "0",
                "VOL_RANG": "0",
            }
        else:
-            tr_id = self._broker._settings.OVERSEAS_RANKING_FLUCT_TR_ID
+            configured_tr_id = self._broker._settings.OVERSEAS_RANKING_FLUCT_TR_ID
-            path = self._broker._settings.OVERSEAS_RANKING_FLUCT_PATH
+            configured_path = self._broker._settings.OVERSEAS_RANKING_FLUCT_PATH
-            params = {
+            default_tr_id = "HHDFS76200100"
-                "KEYB": "",  # NEXT KEY BUFF — Required, 공백
+            default_path = "/uapi/overseas-price/v1/quotations/inquire-updown-rank"
                "AUTH": "",
                "EXCD": ranking_excd,
                "NDAY": "0",
                "GUBN": "1",  # 0=하락율, 1=상승율 — 변동성 스캐너는 급등 종목 우선
                "VOL_RANG": "0",
            }
-        headers = await self._broker._auth_headers(tr_id)
+        endpoint_specs: list[tuple[str, str]] = [(configured_tr_id, configured_path)]
-        url = f"{self._broker._base_url}{path}"
+        if (configured_tr_id, configured_path) != (default_tr_id, default_path):
            endpoint_specs.append((default_tr_id, default_path))
-        try:
+        # Try common param variants used by KIS overseas quotation APIs.
-            async with session.get(url, headers=headers, params=params) as resp:
+        param_variants = [
-                if resp.status != 200:
+            {"AUTH": "", "EXCD": exchange_code, "NREC": str(max(limit, 30))},
-                    text = await resp.text()
+            {"AUTH": "", "OVRS_EXCG_CD": exchange_code, "NREC": str(max(limit, 30))},
-                    if resp.status == 404:
+            {"AUTH": "", "EXCD": exchange_code},
-                        logger.warning(
+            {"AUTH": "", "OVRS_EXCG_CD": exchange_code},
-                            "Overseas ranking endpoint unavailable (404) for %s/%s; "
+        ]
                            "using symbol fallback scan",
                            exchange_code,
                            ranking_type,
                        )
                        return []
                    raise ConnectionError(
                        f"fetch_overseas_rankings failed ({resp.status}): {text}"
                    )
-                data = await resp.json()
+        last_error: str | None = None
-                rows = self._extract_ranking_rows(data)
+        saw_http_404 = False
-                if rows:
+        for tr_id, path in endpoint_specs:
-                    return rows[:limit]
+            headers = await self._broker._auth_headers(tr_id)
            url = f"{self._broker._base_url}{path}"
            for params in param_variants:
                try:
                    async with session.get(url, headers=headers, params=params) as resp:
                        text = await resp.text()
                        if resp.status != 200:
                            last_error = f"HTTP {resp.status}: {text}"
                            if resp.status == 404:
                                saw_http_404 = True
                            continue
-                logger.debug(
+                        data = await resp.json()
-                    "Overseas ranking returned empty for %s/%s (keys=%s)",
+                        rows = self._extract_ranking_rows(data)
-                    exchange_code,
+                        if rows:
-                    ranking_type,
+                            return rows[:limit]
-                    list(data.keys()),
+
-                )
+                        # keep trying another param variant if response has no usable rows
-                return []
+                        last_error = f"empty output (keys={list(data.keys())})"
-        except (TimeoutError, aiohttp.ClientError) as exc:
+                except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
+                    last_error = str(exc)
-                f"Network error fetching overseas rankings: {exc}"
+                    continue
-            ) from exc
+
        if saw_http_404:
            logger.warning(
                "Overseas ranking endpoint unavailable (404) for %s/%s; using symbol fallback scan",
                exchange_code,
                ranking_type,
            )
            return []
        raise ConnectionError(
            f"fetch_overseas_rankings failed for {exchange_code}/{ranking_type}: {last_error}"
        )
    async def get_overseas_balance(self, exchange_code: str) -> dict[str, Any]:
        """
@@ -191,12 +158,8 @@ class OverseasBroker:
        await self._broker._rate_limiter.acquire()
        session = self._broker._get_session()
-        # TR_ID: 실전 TTTS3012R, 모의 VTTS3012R
+        # Virtual trading TR_ID for overseas balance inquiry
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 잔고조회' 시트
+        headers = await self._broker._auth_headers("VTTS3012R")
        balance_tr_id = (
            "TTTS3012R" if self._broker._settings.MODE == "live" else "VTTS3012R"
        )
        headers = await self._broker._auth_headers(balance_tr_id)
        params = {
            "CANO": self._broker._account_no,
            "ACNT_PRDT_CD": self._broker._product_cd,
@@ -222,59 +185,6 @@ class OverseasBroker:
                f"Network error fetching overseas balance: {exc}"
            ) from exc
    async def get_overseas_buying_power(
        self,
        exchange_code: str,
        stock_code: str,
        price: float,
    ) -> dict[str, Any]:
        """
        Fetch overseas buying power for a specific stock and price.
        Args:
            exchange_code: Exchange code (e.g., "NASD", "NYSE")
            stock_code: Stock ticker symbol
            price: Current stock price (used for quantity calculation)
        Returns:
            API response; key field: output.ord_psbl_frcr_amt (주문가능외화금액)
        Raises:
            ConnectionError: On network or API errors
        """
        await self._broker._rate_limiter.acquire()
        session = self._broker._get_session()
        # TR_ID: 실전 TTTS3007R, 모의 VTTS3007R
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 매수가능금액조회' 시트
        ps_tr_id = (
            "TTTS3007R" if self._broker._settings.MODE == "live" else "VTTS3007R"
        )
        headers = await self._broker._auth_headers(ps_tr_id)
        params = {
            "CANO": self._broker._account_no,
            "ACNT_PRDT_CD": self._broker._product_cd,
            "OVRS_EXCG_CD": exchange_code,
            "OVRS_ORD_UNPR": f"{price:.2f}",
            "ITEM_CD": stock_code,
        }
        url = (
            f"{self._broker._base_url}/uapi/overseas-stock/v1/trading/inquire-psamount"
        )
        try:
            async with session.get(url, headers=headers, params=params) as resp:
                if resp.status != 200:
                    text = await resp.text()
                    raise ConnectionError(
                        f"get_overseas_buying_power failed ({resp.status}): {text}"
                    )
                return await resp.json()
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error fetching overseas buying power: {exc}"
            ) from exc
    async def send_overseas_order(
        self,
        exchange_code: str,
@@ -302,12 +212,8 @@ class OverseasBroker:
        await self._broker._rate_limiter.acquire()
        session = self._broker._get_session()
-        # TR_ID: 실전 BUY=TTTT1002U SELL=TTTT1006U, 모의 BUY=VTTT1002U SELL=VTTT1001U
+        # Virtual trading TR_IDs for overseas orders
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문' 시트
+        tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1006U"
        if self._broker._settings.MODE == "live":
            tr_id = "TTTT1002U" if order_type == "BUY" else "TTTT1006U"
        else:
            tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1001U"
        body = {
            "CANO": self._broker._account_no,
@@ -334,158 +240,20 @@ class OverseasBroker:
                        f"send_overseas_order failed ({resp.status}): {text}"
                    )
                data = await resp.json()
-                rt_cd = data.get("rt_cd", "")
+                logger.info(
-                msg1 = data.get("msg1", "")
+                    "Overseas order submitted",
-                if rt_cd == "0":
+                    extra={
-                    logger.info(
+                        "exchange": exchange_code,
-                        "Overseas order submitted",
+                        "stock_code": stock_code,
-                        extra={
+                        "action": order_type,
-                            "exchange": exchange_code,
+                    },
-                            "stock_code": stock_code,
+                )
                            "action": order_type,
                        },
                    )
                else:
                    logger.warning(
                        "Overseas order rejected (rt_cd=%s): %s [%s %s %s qty=%d]",
                        rt_cd,
                        msg1,
                        order_type,
                        stock_code,
                        exchange_code,
                        quantity,
                    )
                return data
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error sending overseas order: {exc}"
            ) from exc
    async def get_overseas_pending_orders(
        self, exchange_code: str
    ) -> list[dict[str, Any]]:
        """Fetch unfilled (pending) overseas orders for a given exchange.
        Args:
            exchange_code: Exchange code (e.g., "NASD", "SEHK").
                For US markets, NASD returns all US pending orders (NASD/NYSE/AMEX).
        Returns:
            List of pending order dicts with fields: odno, pdno, sll_buy_dvsn_cd,
            ft_ord_qty, nccs_qty, ft_ord_unpr3, ovrs_excg_cd.
            Always returns [] in paper mode (TTTS3018R is live-only).
        Raises:
            ConnectionError: On network or API errors (live mode only).
        """
        if self._broker._settings.MODE != "live":
            logger.debug(
                "Pending orders API (TTTS3018R) not supported in paper mode; returning []"
            )
            return []
        await self._broker._rate_limiter.acquire()
        session = self._broker._get_session()
        # TTTS3018R: 해외주식 미체결내역조회 (실전 전용)
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 미체결조회' 시트
        headers = await self._broker._auth_headers("TTTS3018R")
        params = {
            "CANO": self._broker._account_no,
            "ACNT_PRDT_CD": self._broker._product_cd,
            "OVRS_EXCG_CD": exchange_code,
            "SORT_SQN": "DS",
            "CTX_AREA_FK200": "",
            "CTX_AREA_NK200": "",
        }
        url = (
            f"{self._broker._base_url}/uapi/overseas-stock/v1/trading/inquire-nccs"
        )
        try:
            async with session.get(url, headers=headers, params=params) as resp:
                if resp.status != 200:
                    text = await resp.text()
                    raise ConnectionError(
                        f"get_overseas_pending_orders failed ({resp.status}): {text}"
                    )
                data = await resp.json()
                output = data.get("output", [])
                if isinstance(output, list):
                    return output
                return []
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error fetching pending orders: {exc}"
            ) from exc
    async def cancel_overseas_order(
        self,
        exchange_code: str,
        stock_code: str,
        odno: str,
        qty: int,
    ) -> dict[str, Any]:
        """Cancel an overseas limit order.
        Args:
            exchange_code: Exchange code (e.g., "NASD", "SEHK").
            stock_code: Stock ticker symbol.
            odno: Original order number to cancel.
            qty: Unfilled quantity to cancel.
        Returns:
            API response dict containing rt_cd and msg1.
        Raises:
            ValueError: If exchange_code has no cancel TR_ID mapping.
            ConnectionError: On network or API errors.
        """
        tr_ids = _CANCEL_TR_ID_MAP.get(exchange_code)
        if tr_ids is None:
            raise ValueError(f"No cancel TR_ID mapping for exchange: {exchange_code}")
        live_tr_id, paper_tr_id = tr_ids
        tr_id = live_tr_id if self._broker._settings.MODE == "live" else paper_tr_id
        await self._broker._rate_limiter.acquire()
        session = self._broker._get_session()
        # RVSE_CNCL_DVSN_CD="02" means cancel (not revision).
        # OVRS_ORD_UNPR must be "0" for cancellations.
        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 정정취소주문' 시트
        body = {
            "CANO": self._broker._account_no,
            "ACNT_PRDT_CD": self._broker._product_cd,
            "OVRS_EXCG_CD": exchange_code,
            "PDNO": stock_code,
            "ORGN_ODNO": odno,
            "RVSE_CNCL_DVSN_CD": "02",
            "ORD_QTY": str(qty),
            "OVRS_ORD_UNPR": "0",
            "ORD_SVR_DVSN_CD": "0",
        }
        hash_key = await self._broker._get_hash_key(body)
        headers = await self._broker._auth_headers(tr_id)
        headers["hashkey"] = hash_key
        url = (
            f"{self._broker._base_url}/uapi/overseas-stock/v1/trading/order-rvsecncl"
        )
        try:
            async with session.post(url, headers=headers, json=body) as resp:
                if resp.status != 200:
                    text = await resp.text()
                    raise ConnectionError(
                        f"cancel_overseas_order failed ({resp.status}): {text}"
                    )
                return await resp.json()
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
                f"Network error cancelling overseas order: {exc}"
            ) from exc
    def _get_currency_code(self, exchange_code: str) -> str:
        """
        Map exchange code to currency code.
--- a/src/config.py
+++ b/src/config.py
@@ -13,11 +13,11 @@ class Settings(BaseSettings):
    KIS_APP_KEY: str
    KIS_APP_SECRET: str
    KIS_ACCOUNT_NO: str  # format: "XXXXXXXX-XX"
-    KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:29443"
+    KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:9443"
    # Google Gemini
    GEMINI_API_KEY: str
-    GEMINI_MODEL: str = "gemini-2.0-flash"
+    GEMINI_MODEL: str = "gemini-pro"
    # External Data APIs (optional — for data-driven decisions)
    NEWS_API_KEY: str | None = None
@@ -55,11 +55,6 @@ class Settings(BaseSettings):
    # Trading mode
    MODE: str = Field(default="paper", pattern="^(paper|live)$")
    # Simulated USD cash for VTS (paper) overseas trading.
    # KIS VTS overseas balance API returns errors for most accounts.
    # This value is used as a fallback when the balance API returns 0 in paper mode.
    PAPER_OVERSEAS_CASH: float = Field(default=50000.0, ge=0.0)
    # Trading frequency mode (daily = batch API calls, realtime = per-stock calls)
    TRADE_MODE: str = Field(default="daily", pattern="^(daily|realtime)$")
    DAILY_SESSIONS: int = Field(default=4, ge=1, le=10)
@@ -93,26 +88,16 @@ class Settings(BaseSettings):
    TELEGRAM_COMMANDS_ENABLED: bool = True
    TELEGRAM_POLLING_INTERVAL: float = 1.0  # seconds
    # Telegram notification type filters (granular control)
    # circuit_breaker is always sent regardless — safety-critical
    TELEGRAM_NOTIFY_TRADES: bool = True           # BUY/SELL execution alerts
    TELEGRAM_NOTIFY_MARKET_OPEN_CLOSE: bool = True  # Market open/close alerts
    TELEGRAM_NOTIFY_FAT_FINGER: bool = True       # Fat-finger rejection alerts
    TELEGRAM_NOTIFY_SYSTEM_EVENTS: bool = True    # System start/shutdown alerts
    TELEGRAM_NOTIFY_PLAYBOOK: bool = True         # Playbook generated/failed alerts
    TELEGRAM_NOTIFY_SCENARIO_MATCH: bool = True   # Scenario matched alerts (most frequent)
    TELEGRAM_NOTIFY_ERRORS: bool = True           # Error alerts
    # Overseas ranking API (KIS endpoint/TR_ID may vary by account/product)
    # Override these from .env if your account uses different specs.
    OVERSEAS_RANKING_ENABLED: bool = True
-    OVERSEAS_RANKING_FLUCT_TR_ID: str = "HHDFS76290000"
+    OVERSEAS_RANKING_FLUCT_TR_ID: str = "HHDFS76200100"
-    OVERSEAS_RANKING_VOLUME_TR_ID: str = "HHDFS76270000"
+    OVERSEAS_RANKING_VOLUME_TR_ID: str = "HHDFS76200200"
    OVERSEAS_RANKING_FLUCT_PATH: str = (
-        "/uapi/overseas-stock/v1/ranking/updown-rate"
+        "/uapi/overseas-price/v1/quotations/inquire-updown-rank"
    )
    OVERSEAS_RANKING_VOLUME_PATH: str = (
-        "/uapi/overseas-stock/v1/ranking/volume-surge"
+        "/uapi/overseas-price/v1/quotations/inquire-volume-rank"
    )
    # Dashboard (optional)
--- a/src/dashboard/app.py
+++ b/src/dashboard/app.py
@@ -3,9 +3,8 @@
 from __future__ import annotations
 import json
 import os
 import sqlite3
-from datetime import UTC, datetime, timezone
+from datetime import UTC, datetime
 from pathlib import Path
 from typing import Any
@@ -13,11 +12,10 @@ from fastapi import FastAPI, HTTPException, Query
 from fastapi.responses import FileResponse
-def create_dashboard_app(db_path: str, mode: str = "paper") -> FastAPI:
+def create_dashboard_app(db_path: str) -> FastAPI:
    """Create dashboard FastAPI app bound to a SQLite database path."""
    app = FastAPI(title="The Ouroboros Dashboard", version="1.0.0")
    app.state.db_path = db_path
    app.state.mode = mode
    @app.get("/")
    def index() -> FileResponse:
@@ -81,49 +79,14 @@ def create_dashboard_app(db_path: str, mode: str = "paper") -> FastAPI:
                total_pnl += market_status[market]["total_pnl"]
                total_decisions += market_status[market]["decision_count"]
            cb_threshold = float(os.getenv("CIRCUIT_BREAKER_PCT", "-3.0"))
            pnl_pct_rows = conn.execute(
                """
                SELECT key, value
                FROM system_metrics
                WHERE key LIKE 'portfolio_pnl_pct_%'
                ORDER BY updated_at DESC
                LIMIT 20
                """
            ).fetchall()
            current_pnl_pct: float | None = None
            if pnl_pct_rows:
                values = [
                    json.loads(row["value"]).get("pnl_pct")
                    for row in pnl_pct_rows
                    if json.loads(row["value"]).get("pnl_pct") is not None
                ]
                if values:
                    current_pnl_pct = round(min(values), 4)
            if current_pnl_pct is None:
                cb_status = "unknown"
            elif current_pnl_pct <= cb_threshold:
                cb_status = "tripped"
            elif current_pnl_pct <= cb_threshold + 1.0:
                cb_status = "warning"
            else:
                cb_status = "ok"
            return {
                "date": today,
                "mode": mode,
                "markets": market_status,
                "totals": {
                    "trade_count": total_trades,
                    "total_pnl": round(total_pnl, 2),
                    "decision_count": total_decisions,
                },
                "circuit_breaker": {
                    "threshold_pct": cb_threshold,
                    "current_pnl_pct": current_pnl_pct,
                    "status": cb_status,
                },
            }
    @app.get("/api/playbook/{date_str}")
@@ -296,50 +259,6 @@ def create_dashboard_app(db_path: str, mode: str = "paper") -> FastAPI:
                )
            return {"market": market, "count": len(decisions), "decisions": decisions}
    @app.get("/api/pnl/history")
    def get_pnl_history(
        days: int = Query(default=30, ge=1, le=365),
        market: str = Query("all"),
    ) -> dict[str, Any]:
        """Return daily P&L history for charting."""
        with _connect(db_path) as conn:
            if market == "all":
                rows = conn.execute(
                    """
                    SELECT DATE(timestamp) AS date,
                           SUM(pnl) AS daily_pnl,
                           COUNT(*) AS trade_count
                    FROM trades
                    WHERE pnl IS NOT NULL
                      AND DATE(timestamp) >= DATE('now', ?)
                    GROUP BY DATE(timestamp)
                    ORDER BY DATE(timestamp)
                    """,
                    (f"-{days} days",),
                ).fetchall()
            else:
                rows = conn.execute(
                    """
                    SELECT DATE(timestamp) AS date,
                           SUM(pnl) AS daily_pnl,
                           COUNT(*) AS trade_count
                    FROM trades
                    WHERE pnl IS NOT NULL
                      AND market = ?
                      AND DATE(timestamp) >= DATE('now', ?)
                    GROUP BY DATE(timestamp)
                    ORDER BY DATE(timestamp)
                    """,
                    (market, f"-{days} days"),
                ).fetchall()
            return {
                "days": days,
                "market": market,
                "labels": [row["date"] for row in rows],
                "pnl": [round(float(row["daily_pnl"]), 2) for row in rows],
                "trades": [int(row["trade_count"]) for row in rows],
            }
    @app.get("/api/scenarios/active")
    def get_active_scenarios(
        market: str = Query("US"),
@@ -378,68 +297,12 @@ def create_dashboard_app(db_path: str, mode: str = "paper") -> FastAPI:
                )
            return {"market": market, "date": date_str, "count": len(matches), "matches": matches}
    @app.get("/api/positions")
    def get_positions() -> dict[str, Any]:
        """Return all currently open positions (last trade per symbol is BUY)."""
        with _connect(db_path) as conn:
            rows = conn.execute(
                """
                SELECT stock_code, market, exchange_code,
                       price AS entry_price, quantity, timestamp AS entry_time,
                       decision_id
                FROM (
                    SELECT stock_code, market, exchange_code, price, quantity,
                           timestamp, decision_id, action,
                           ROW_NUMBER() OVER (
                               PARTITION BY stock_code, market
                               ORDER BY timestamp DESC
                           ) AS rn
                    FROM trades
                )
                WHERE rn = 1 AND action = 'BUY'
                ORDER BY entry_time DESC
                """
            ).fetchall()
            now = datetime.now(timezone.utc)
            positions = []
            for row in rows:
                entry_time_str = row["entry_time"]
                try:
                    entry_dt = datetime.fromisoformat(entry_time_str.replace("Z", "+00:00"))
                    held_seconds = int((now - entry_dt).total_seconds())
                    held_hours = held_seconds // 3600
                    held_minutes = (held_seconds % 3600) // 60
                    if held_hours >= 1:
                        held_display = f"{held_hours}h {held_minutes}m"
                    else:
                        held_display = f"{held_minutes}m"
                except (ValueError, TypeError):
                    held_display = "--"
                positions.append(
                    {
                        "stock_code": row["stock_code"],
                        "market": row["market"],
                        "exchange_code": row["exchange_code"],
                        "entry_price": row["entry_price"],
                        "quantity": row["quantity"],
                        "entry_time": entry_time_str,
                        "held": held_display,
                        "decision_id": row["decision_id"],
                    }
                )
            return {"count": len(positions), "positions": positions}
    return app
 def _connect(db_path: str) -> sqlite3.Connection:
    conn = sqlite3.connect(db_path)
    conn.row_factory = sqlite3.Row
    conn.execute("PRAGMA journal_mode=WAL")
    conn.execute("PRAGMA busy_timeout=8000")
    return conn
--- a/src/dashboard/static/index.html
+++ b/src/dashboard/static/index.html
@@ -1,10 +1,9 @@
 <!doctype html>
-<html lang="ko">
+<html lang="en">
  <head>
    <meta charset="UTF-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0" />
    <title>The Ouroboros Dashboard</title>
    <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
    <style>
      :root {
        --bg: #0b1724;
@@ -12,787 +11,51 @@
        --fg: #e6eef7;
        --muted: #9fb3c8;
        --accent: #3cb371;
        --red: #e05555;
        --warn: #e8a040;
        --border: #28455f;
      }
      * { box-sizing: border-box; margin: 0; padding: 0; }
      body {
        margin: 0;
        font-family: ui-monospace, SFMono-Regular, Menlo, monospace;
        background: radial-gradient(circle at top left, #173b58, var(--bg));
        color: var(--fg);
        min-height: 100vh;
        font-size: 13px;
      }
-      .wrap { max-width: 1100px; margin: 0 auto; padding: 20px 16px; }
+      .wrap {
-
+        max-width: 900px;
-      /* Header */
+        margin: 48px auto;
-      header {
+        padding: 0 16px;
        display: flex;
        align-items: center;
        justify-content: space-between;
        margin-bottom: 20px;
        padding-bottom: 12px;
        border-bottom: 1px solid var(--border);
      }
      header h1 { font-size: 18px; color: var(--accent); letter-spacing: 0.5px; }
      .header-right { display: flex; align-items: center; gap: 12px; color: var(--muted); font-size: 12px; }
      .refresh-btn {
        background: none; border: 1px solid var(--border); color: var(--muted);
        padding: 4px 10px; border-radius: 6px; cursor: pointer; font-family: inherit;
        font-size: 12px; transition: border-color 0.2s;
      }
      .refresh-btn:hover { border-color: var(--accent); color: var(--accent); }
      .mode-badge {
        padding: 3px 10px; border-radius: 5px; font-size: 12px; font-weight: 700;
        letter-spacing: 0.5px;
      }
      .mode-badge.live {
        background: rgba(224, 85, 85, 0.15); color: var(--red);
        border: 1px solid rgba(224, 85, 85, 0.4);
        animation: pulse-warn 2s ease-in-out infinite;
      }
      .mode-badge.paper {
        background: rgba(232, 160, 64, 0.15); color: var(--warn);
        border: 1px solid rgba(232, 160, 64, 0.4);
      }
      /* CB Gauge */
      .cb-gauge-wrap {
        display: flex; align-items: center; gap: 8px;
        font-size: 11px; color: var(--muted);
      }
      .cb-dot {
        width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0;
      }
      .cb-dot.ok      { background: var(--accent); }
      .cb-dot.warning { background: var(--warn); animation: pulse-warn 1.2s ease-in-out infinite; }
      .cb-dot.tripped { background: var(--red);  animation: pulse-warn 0.6s ease-in-out infinite; }
      .cb-dot.unknown { background: var(--border); }
      @keyframes pulse-warn {
        0%, 100% { opacity: 1; }
        50%       { opacity: 0.35; }
      }
      .cb-bar-wrap { width: 64px; height: 5px; background: rgba(255,255,255,0.08); border-radius: 3px; overflow: hidden; }
      .cb-bar-fill { height: 100%; border-radius: 3px; transition: width 0.4s, background 0.4s; }
      /* Summary cards */
      .cards { display: grid; grid-template-columns: repeat(4, 1fr); gap: 12px; margin-bottom: 20px; }
      @media (max-width: 700px) { .cards { grid-template-columns: repeat(2, 1fr); } }
      .card {
-        background: var(--panel);
+        background: color-mix(in oklab, var(--panel), black 12%);
-        border: 1px solid var(--border);
+        border: 1px solid #28455f;
-        border-radius: 10px;
+        border-radius: 12px;
-        padding: 16px;
+        padding: 20px;
      }
-      .card-label { color: var(--muted); font-size: 11px; margin-bottom: 6px; text-transform: uppercase; letter-spacing: 0.5px; }
+      h1 {
-      .card-value { font-size: 22px; font-weight: 700; }
+        margin-top: 0;
      .card-sub { color: var(--muted); font-size: 11px; margin-top: 4px; }
      .positive { color: var(--accent); }
      .negative { color: var(--red); }
      .neutral { color: var(--fg); }
      /* Chart panel */
      .chart-panel {
        background: var(--panel);
        border: 1px solid var(--border);
        border-radius: 10px;
        padding: 16px;
        margin-bottom: 20px;
      }
-      .panel-header {
+      code {
-        display: flex;
+        color: var(--accent);
        align-items: center;
        justify-content: space-between;
        margin-bottom: 16px;
      }
-      .panel-title { font-size: 13px; color: var(--muted); font-weight: 600; }
+      li {
-      .chart-container { position: relative; height: 180px; }
+        margin: 6px 0;
-      .chart-error { color: var(--muted); text-align: center; padding: 40px 0; font-size: 12px; }
+        color: var(--muted);
      /* Days selector */
      .days-selector { display: flex; gap: 4px; }
      .day-btn {
        background: none; border: 1px solid var(--border); color: var(--muted);
        padding: 3px 8px; border-radius: 4px; cursor: pointer; font-family: inherit; font-size: 11px;
      }
      .day-btn.active { border-color: var(--accent); color: var(--accent); background: rgba(60, 179, 113, 0.08); }
      /* Decisions panel */
      .decisions-panel {
        background: var(--panel);
        border: 1px solid var(--border);
        border-radius: 10px;
        padding: 16px;
      }
      .market-tabs { display: flex; gap: 6px; flex-wrap: wrap; }
      .tab-btn {
        background: none; border: 1px solid var(--border); color: var(--muted);
        padding: 4px 10px; border-radius: 6px; cursor: pointer; font-family: inherit; font-size: 11px;
      }
      .tab-btn.active { border-color: var(--accent); color: var(--accent); background: rgba(60, 179, 113, 0.08); }
      .decisions-table { width: 100%; border-collapse: collapse; margin-top: 14px; }
      .decisions-table th {
        text-align: left; color: var(--muted); font-size: 11px; font-weight: 600;
        padding: 6px 8px; border-bottom: 1px solid var(--border); white-space: nowrap;
      }
      .decisions-table td {
        padding: 8px 8px; border-bottom: 1px solid rgba(40, 69, 95, 0.5);
        vertical-align: middle; white-space: nowrap;
      }
      .decisions-table tr:last-child td { border-bottom: none; }
      .decisions-table tr:hover td { background: rgba(255,255,255,0.02); }
      .badge {
        display: inline-block; padding: 2px 7px; border-radius: 4px;
        font-size: 11px; font-weight: 700; letter-spacing: 0.5px;
      }
      .badge-buy { background: rgba(60, 179, 113, 0.15); color: var(--accent); }
      .badge-sell { background: rgba(224, 85, 85, 0.15); color: var(--red); }
      .badge-hold { background: rgba(159, 179, 200, 0.12); color: var(--muted); }
      .conf-bar-wrap { display: flex; align-items: center; gap: 6px; min-width: 90px; }
      .conf-bar { flex: 1; height: 6px; background: rgba(255,255,255,0.08); border-radius: 3px; overflow: hidden; }
      .conf-fill { height: 100%; border-radius: 3px; background: var(--accent); transition: width 0.3s; }
      .conf-val { color: var(--muted); font-size: 11px; min-width: 26px; text-align: right; }
      .rationale-cell { max-width: 200px; overflow: hidden; text-overflow: ellipsis; color: var(--muted); }
      .empty-row td { text-align: center; color: var(--muted); padding: 24px; }
      /* Positions panel */
      .positions-panel {
        background: var(--panel);
        border: 1px solid var(--border);
        border-radius: 10px;
        padding: 16px;
        margin-bottom: 20px;
      }
      .positions-table { width: 100%; border-collapse: collapse; margin-top: 14px; }
      .positions-table th {
        text-align: left; color: var(--muted); font-size: 11px; font-weight: 600;
        padding: 6px 8px; border-bottom: 1px solid var(--border); white-space: nowrap;
      }
      .positions-table td {
        padding: 8px 8px; border-bottom: 1px solid rgba(40, 69, 95, 0.5);
        vertical-align: middle; white-space: nowrap;
      }
      .positions-table tr:last-child td { border-bottom: none; }
      .positions-table tr:hover td { background: rgba(255,255,255,0.02); }
      .pos-empty { color: var(--muted); text-align: center; padding: 20px 0; font-size: 12px; }
      .pos-count {
        display: inline-block; background: rgba(60, 179, 113, 0.12);
        color: var(--accent); font-size: 11px; font-weight: 700;
        padding: 2px 8px; border-radius: 10px; margin-left: 8px;
      }
      /* Spinner */
      .spinner { display: inline-block; width: 12px; height: 12px; border: 2px solid var(--border); border-top-color: var(--accent); border-radius: 50%; animation: spin 0.8s linear infinite; }
      @keyframes spin { to { transform: rotate(360deg); } }
      /* Generic panel */
      .panel {
        background: var(--panel);
        border: 1px solid var(--border);
        border-radius: 10px;
        padding: 16px;
        margin-top: 20px;
      }
      /* Playbook panel - details/summary accordion */
      .playbook-panel details { border: 1px solid var(--border); border-radius: 4px; margin-bottom: 6px; }
      .playbook-panel summary { padding: 8px 12px; cursor: pointer; font-weight: 600; background: var(--bg); color: var(--fg); }
      .playbook-panel summary:hover { color: var(--accent); }
      .playbook-panel pre { margin: 0; padding: 12px; background: var(--bg); overflow-x: auto;
                            font-size: 11px; color: #a0c4ff; white-space: pre-wrap; }
      /* Scorecard KPI card grid */
      .scorecard-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(140px, 1fr)); gap: 10px; }
      .kpi-card { background: var(--bg); border: 1px solid var(--border); border-radius: 6px; padding: 12px; text-align: center; }
      .kpi-card .kpi-label { font-size: 11px; color: var(--muted); margin-bottom: 4px; }
      .kpi-card .kpi-value { font-size: 20px; font-weight: 700; color: var(--fg); }
      /* Scenarios table */
      .scenarios-table { width: 100%; border-collapse: collapse; font-size: 13px; }
      .scenarios-table th { background: var(--bg); padding: 8px; text-align: left; border-bottom: 1px solid var(--border);
                            color: var(--muted); font-size: 11px; font-weight: 600; white-space: nowrap; }
      .scenarios-table td { padding: 7px 8px; border-bottom: 1px solid rgba(40,69,95,0.5); }
      .scenarios-table tr:hover td { background: rgba(255,255,255,0.02); }
      /* Context table */
      .context-table { width: 100%; border-collapse: collapse; font-size: 12px; }
      .context-table th { background: var(--bg); padding: 8px; text-align: left; border-bottom: 1px solid var(--border);
                          color: var(--muted); font-size: 11px; font-weight: 600; white-space: nowrap; }
      .context-table td { padding: 6px 8px; border-bottom: 1px solid rgba(40,69,95,0.5); vertical-align: top; }
      .context-value { max-height: 60px; overflow-y: auto; color: #a0c4ff; word-break: break-all; }
      /* Common panel select controls */
      .panel-controls { display: flex; gap: 8px; align-items: center; flex-wrap: wrap; }
      .panel-controls select, .panel-controls input[type="number"] {
        background: var(--bg); color: var(--fg); border: 1px solid var(--border);
        border-radius: 4px; padding: 4px 8px; font-size: 13px; font-family: inherit;
      }
      .panel-date { color: var(--muted); font-size: 12px; }
      .empty-msg { color: var(--muted); text-align: center; padding: 20px 0; font-size: 12px; }
    </style>
  </head>
  <body>
    <div class="wrap">
-      <!-- Header -->
+      <div class="card">
-      <header>
+        <h1>The Ouroboros Dashboard API</h1>
-        <h1>&#x1F40D; The Ouroboros</h1>
+        <p>Use the following endpoints:</p>
-        <div class="header-right">
+        <ul>
-          <span class="mode-badge" id="mode-badge">--</span>
+          <li><code>/api/status</code></li>
-          <div class="cb-gauge-wrap" id="cb-gauge" title="Circuit Breaker">
+          <li><code>/api/playbook/{date}?market=KR</code></li>
-            <span class="cb-dot unknown" id="cb-dot"></span>
+          <li><code>/api/scorecard/{date}?market=KR</code></li>
-            <span id="cb-label">CB --</span>
+          <li><code>/api/performance?market=all</code></li>
-            <div class="cb-bar-wrap">
+          <li><code>/api/context/{layer}</code></li>
-              <div class="cb-bar-fill" id="cb-bar" style="width:0%;background:var(--accent)"></div>
+          <li><code>/api/decisions?market=KR</code></li>
-            </div>
+          <li><code>/api/scenarios/active?market=US</code></li>
-          </div>
+        </ul>
          <span id="last-updated">--</span>
          <button class="refresh-btn" onclick="refreshAll()">&#x21BA; 새로고침</button>
        </div>
      </header>
      <!-- Summary cards -->
      <div class="cards">
        <div class="card">
          <div class="card-label">오늘 거래</div>
          <div class="card-value neutral" id="card-trades">--</div>
          <div class="card-sub" id="card-trades-sub">거래 건수</div>
        </div>
        <div class="card">
          <div class="card-label">오늘 P&amp;L</div>
          <div class="card-value" id="card-pnl">--</div>
          <div class="card-sub" id="card-pnl-sub">실현 손익</div>
        </div>
        <div class="card">
          <div class="card-label">승률</div>
          <div class="card-value neutral" id="card-winrate">--</div>
          <div class="card-sub">전체 누적</div>
        </div>
        <div class="card">
          <div class="card-label">누적 거래</div>
          <div class="card-value neutral" id="card-total">--</div>
          <div class="card-sub">전체 기간</div>
        </div>
      </div>
      <!-- Open Positions -->
      <div class="positions-panel">
        <div class="panel-header">
          <span class="panel-title">
            현재 보유 포지션
            <span class="pos-count" id="positions-count">0</span>
          </span>
        </div>
        <table class="positions-table">
          <thead>
            <tr>
              <th>종목</th>
              <th>시장</th>
              <th>수량</th>
              <th>진입가</th>
              <th>보유 시간</th>
            </tr>
          </thead>
          <tbody id="positions-body">
            <tr><td colspan="5" class="pos-empty"><span class="spinner"></span></td></tr>
          </tbody>
        </table>
      </div>
      <!-- P&L Chart -->
      <div class="chart-panel">
        <div class="panel-header">
          <span class="panel-title">P&amp;L 추이</span>
          <div class="days-selector">
            <button class="day-btn active" data-days="7" onclick="selectDays(this)">7일</button>
            <button class="day-btn" data-days="30" onclick="selectDays(this)">30일</button>
            <button class="day-btn" data-days="90" onclick="selectDays(this)">90일</button>
          </div>
        </div>
        <div class="chart-container">
          <canvas id="pnl-chart"></canvas>
          <div class="chart-error" id="chart-error" style="display:none">데이터 없음</div>
        </div>
      </div>
      <!-- Decisions log -->
      <div class="decisions-panel">
        <div class="panel-header">
          <span class="panel-title">최근 결정 로그</span>
          <div class="market-tabs" id="market-tabs">
            <button class="tab-btn active" data-market="KR" onclick="selectMarket(this)">KR</button>
            <button class="tab-btn" data-market="US_NASDAQ" onclick="selectMarket(this)">US_NASDAQ</button>
            <button class="tab-btn" data-market="US_NYSE" onclick="selectMarket(this)">US_NYSE</button>
            <button class="tab-btn" data-market="JP" onclick="selectMarket(this)">JP</button>
            <button class="tab-btn" data-market="HK" onclick="selectMarket(this)">HK</button>
          </div>
        </div>
        <table class="decisions-table">
          <thead>
            <tr>
              <th>시각</th>
              <th>종목</th>
              <th>액션</th>
              <th>신뢰도</th>
              <th>사유</th>
            </tr>
          </thead>
          <tbody id="decisions-body">
            <tr class="empty-row"><td colspan="5"><span class="spinner"></span></td></tr>
          </tbody>
        </table>
      </div>
      <!-- playbook panel -->
      <div class="panel playbook-panel">
        <div class="panel-header">
          <span class="panel-title">&#x1F4CB; 프리마켓 플레이북</span>
          <div class="panel-controls">
            <select id="pb-market-select" onchange="fetchPlaybook()">
              <option value="KR">KR</option>
              <option value="US_NASDAQ">US_NASDAQ</option>
              <option value="US_NYSE">US_NYSE</option>
            </select>
            <span id="pb-date" class="panel-date"></span>
          </div>
        </div>
        <div id="playbook-content"><p class="empty-msg">데이터 없음</p></div>
      </div>
      <!-- scorecard panel -->
      <div class="panel">
        <div class="panel-header">
          <span class="panel-title">&#x1F4CA; 일간 스코어카드</span>
          <div class="panel-controls">
            <select id="sc-market-select" onchange="fetchScorecard()">
              <option value="KR">KR</option>
              <option value="US_NASDAQ">US_NASDAQ</option>
            </select>
            <span id="sc-date" class="panel-date"></span>
          </div>
        </div>
        <div id="scorecard-grid" class="scorecard-grid"><p class="empty-msg">데이터 없음</p></div>
      </div>
      <!-- scenarios panel -->
      <div class="panel">
        <div class="panel-header">
          <span class="panel-title">&#x1F3AF; 활성 시나리오 매칭</span>
          <div class="panel-controls">
            <select id="scen-market-select" onchange="fetchScenarios()">
              <option value="KR">KR</option>
              <option value="US_NASDAQ">US_NASDAQ</option>
            </select>
          </div>
        </div>
        <div id="scenarios-content"><p class="empty-msg">데이터 없음</p></div>
      </div>
      <!-- context layer panel -->
      <div class="panel">
        <div class="panel-header">
          <span class="panel-title">&#x1F9E0; 컨텍스트 트리</span>
          <div class="panel-controls">
            <select id="ctx-layer-select" onchange="fetchContext()">
              <option value="L7_REALTIME">L7_REALTIME</option>
              <option value="L6_DAILY">L6_DAILY</option>
              <option value="L5_WEEKLY">L5_WEEKLY</option>
              <option value="L4_MONTHLY">L4_MONTHLY</option>
              <option value="L3_QUARTERLY">L3_QUARTERLY</option>
              <option value="L2_YEARLY">L2_YEARLY</option>
              <option value="L1_LIFETIME">L1_LIFETIME</option>
            </select>
            <input id="ctx-limit" type="number" value="20" min="1" max="200"
                   style="width:60px;" onchange="fetchContext()">
          </div>
        </div>
        <div id="context-content"><p class="empty-msg">데이터 없음</p></div>
      </div>
    </div>
    <script>
      let pnlChart = null;
      let currentDays = 7;
      let currentMarket = 'KR';
      function fmt(dt) {
        try {
          const d = new Date(dt);
          return d.toLocaleTimeString('ko-KR', { hour: '2-digit', minute: '2-digit', hour12: false });
        } catch { return dt || '--'; }
      }
      function fmtPnl(v) {
        if (v === null || v === undefined) return '--';
        const n = parseFloat(v);
        const cls = n > 0 ? 'positive' : n < 0 ? 'negative' : 'neutral';
        const sign = n > 0 ? '+' : '';
        return `<span class="${cls}">${sign}${n.toFixed(2)}</span>`;
      }
      function badge(action) {
        const a = (action || '').toUpperCase();
        const cls = a === 'BUY' ? 'badge-buy' : a === 'SELL' ? 'badge-sell' : 'badge-hold';
        return `<span class="badge ${cls}">${a}</span>`;
      }
      function confBar(conf) {
        const pct = Math.min(Math.max(conf || 0, 0), 100);
        return `<div class="conf-bar-wrap">
          <div class="conf-bar"><div class="conf-fill" style="width:${pct}%"></div></div>
          <span class="conf-val">${pct}</span>
        </div>`;
      }
      function fmtPrice(v, market) {
        if (v === null || v === undefined) return '--';
        const n = parseFloat(v);
        const sym = market === 'KR' ? '₩' : market === 'JP' ? '¥' : market === 'HK' ? 'HK$' : '$';
        return sym + n.toLocaleString('en-US', { minimumFractionDigits: 0, maximumFractionDigits: 4 });
      }
      async function fetchPositions() {
        const tbody = document.getElementById('positions-body');
        const countEl = document.getElementById('positions-count');
        try {
          const r = await fetch('/api/positions');
          if (!r.ok) throw new Error('fetch failed');
          const d = await r.json();
          countEl.textContent = d.count ?? 0;
          if (!d.positions || d.positions.length === 0) {
            tbody.innerHTML = '<tr><td colspan="5" class="pos-empty">현재 보유 중인 포지션 없음</td></tr>';
            return;
          }
          tbody.innerHTML = d.positions.map(p => `
            <tr>
              <td><strong>${p.stock_code || '--'}</strong></td>
              <td><span style="color:var(--muted);font-size:11px">${p.market || '--'}</span></td>
              <td>${p.quantity ?? '--'}</td>
              <td>${fmtPrice(p.entry_price, p.market)}</td>
              <td style="color:var(--muted);font-size:11px">${p.held || '--'}</td>
            </tr>
          `).join('');
        } catch {
          tbody.innerHTML = '<tr><td colspan="5" class="pos-empty">데이터 로드 실패</td></tr>';
        }
      }
      function renderCbGauge(cb) {
        if (!cb) return;
        const dot = document.getElementById('cb-dot');
        const label = document.getElementById('cb-label');
        const bar = document.getElementById('cb-bar');
        const status = cb.status || 'unknown';
        const threshold = cb.threshold_pct ?? -3.0;
        const current = cb.current_pnl_pct;
        // dot color
        dot.className = `cb-dot ${status}`;
        // label
        if (current !== null && current !== undefined) {
          const sign = current > 0 ? '+' : '';
          label.textContent = `CB ${sign}${current.toFixed(2)}%`;
        } else {
          label.textContent = 'CB --';
        }
        // bar: fill = how much of the threshold has been consumed (0%=safe, 100%=tripped)
        const colorMap = { ok: 'var(--accent)', warning: 'var(--warn)', tripped: 'var(--red)', unknown: 'var(--border)' };
        bar.style.background = colorMap[status] || 'var(--border)';
        if (current !== null && current !== undefined && threshold < 0) {
          const fillPct = Math.min(Math.max((current / threshold) * 100, 0), 100);
          bar.style.width = `${fillPct}%`;
        } else {
          bar.style.width = '0%';
        }
      }
      async function fetchStatus() {
        try {
          const r = await fetch('/api/status');
          if (!r.ok) return;
          const d = await r.json();
          const t = d.totals || {};
          document.getElementById('card-trades').textContent = t.trade_count ?? '--';
          const pnlEl = document.getElementById('card-pnl');
          const pnlV = t.total_pnl;
          if (pnlV !== undefined) {
            const n = parseFloat(pnlV);
            const sign = n > 0 ? '+' : '';
            pnlEl.textContent = `${sign}${n.toFixed(2)}`;
            pnlEl.className = `card-value ${n > 0 ? 'positive' : n < 0 ? 'negative' : 'neutral'}`;
          }
          document.getElementById('card-pnl-sub').textContent = `결정 ${t.decision_count ?? 0}건`;
          renderCbGauge(d.circuit_breaker);
          renderModeBadge(d.mode);
        } catch {}
      }
      function renderModeBadge(mode) {
        const el = document.getElementById('mode-badge');
        if (!el) return;
        if (mode === 'live') {
          el.textContent = '🔴 실전투자';
          el.className = 'mode-badge live';
        } else {
          el.textContent = '🟡 모의투자';
          el.className = 'mode-badge paper';
        }
      }
      async function fetchPerformance() {
        try {
          const r = await fetch('/api/performance?market=all');
          if (!r.ok) return;
          const d = await r.json();
          const c = d.combined || {};
          document.getElementById('card-winrate').textContent = c.win_rate !== undefined ? `${c.win_rate}%` : '--';
          document.getElementById('card-total').textContent = c.total_trades ?? '--';
        } catch {}
      }
      async function fetchPnlHistory(days) {
        try {
          const r = await fetch(`/api/pnl/history?days=${days}`);
          if (!r.ok) throw new Error('fetch failed');
          const d = await r.json();
          renderChart(d);
        } catch {
          document.getElementById('chart-error').style.display = 'block';
        }
      }
      function renderChart(data) {
        const errEl = document.getElementById('chart-error');
        if (!data.labels || data.labels.length === 0) {
          errEl.style.display = 'block';
          return;
        }
        errEl.style.display = 'none';
        const colors = data.pnl.map(v => v >= 0 ? 'rgba(60,179,113,0.75)' : 'rgba(224,85,85,0.75)');
        const borderColors = data.pnl.map(v => v >= 0 ? '#3cb371' : '#e05555');
        if (pnlChart) { pnlChart.destroy(); pnlChart = null; }
        const ctx = document.getElementById('pnl-chart').getContext('2d');
        pnlChart = new Chart(ctx, {
          type: 'bar',
          data: {
            labels: data.labels,
            datasets: [{
              label: 'Daily P&L',
              data: data.pnl,
              backgroundColor: colors,
              borderColor: borderColors,
              borderWidth: 1,
              borderRadius: 3,
            }]
          },
          options: {
            responsive: true,
            maintainAspectRatio: false,
            plugins: {
              legend: { display: false },
              tooltip: {
                callbacks: {
                  label: ctx => {
                    const v = ctx.parsed.y;
                    const sign = v >= 0 ? '+' : '';
                    const trades = data.trades[ctx.dataIndex];
                    return [`P&L: ${sign}${v.toFixed(2)}`, `거래: ${trades}건`];
                  }
                }
              }
            },
            scales: {
              x: {
                ticks: { color: '#9fb3c8', font: { size: 10 }, maxRotation: 0 },
                grid: { color: 'rgba(40,69,95,0.4)' }
              },
              y: {
                ticks: { color: '#9fb3c8', font: { size: 10 } },
                grid: { color: 'rgba(40,69,95,0.4)' }
              }
            }
          }
        });
      }
      async function fetchDecisions(market) {
        const tbody = document.getElementById('decisions-body');
        tbody.innerHTML = '<tr class="empty-row"><td colspan="5"><span class="spinner"></span></td></tr>';
        try {
          const r = await fetch(`/api/decisions?market=${market}&limit=50`);
          if (!r.ok) throw new Error('fetch failed');
          const d = await r.json();
          if (!d.decisions || d.decisions.length === 0) {
            tbody.innerHTML = '<tr class="empty-row"><td colspan="5">결정 로그 없음</td></tr>';
            return;
          }
          tbody.innerHTML = d.decisions.map(dec => `
            <tr>
              <td>${fmt(dec.timestamp)}</td>
              <td>${dec.stock_code || '--'}</td>
              <td>${badge(dec.action)}</td>
              <td>${confBar(dec.confidence)}</td>
              <td class="rationale-cell" title="${(dec.rationale || '').replace(/"/g, '&quot;')}">${dec.rationale || '--'}</td>
            </tr>
          `).join('');
        } catch {
          tbody.innerHTML = '<tr class="empty-row"><td colspan="5">데이터 로드 실패</td></tr>';
        }
      }
      function selectDays(btn) {
        document.querySelectorAll('.day-btn').forEach(b => b.classList.remove('active'));
        btn.classList.add('active');
        currentDays = parseInt(btn.dataset.days, 10);
        fetchPnlHistory(currentDays);
      }
      function selectMarket(btn) {
        document.querySelectorAll('.tab-btn').forEach(b => b.classList.remove('active'));
        btn.classList.add('active');
        currentMarket = btn.dataset.market;
        fetchDecisions(currentMarket);
      }
      function todayStr() {
        return new Date().toISOString().slice(0, 10);
      }
      function esc(s) {
        return String(s ?? '').replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;');
      }
      async function fetchJSON(url) {
        const r = await fetch(url);
        if (!r.ok) throw new Error(`HTTP ${r.status}`);
        return r.json();
      }
      async function fetchPlaybook() {
        const market = document.getElementById('pb-market-select').value;
        const date = todayStr();
        document.getElementById('pb-date').textContent = date;
        const el = document.getElementById('playbook-content');
        try {
          const data = await fetchJSON(`/api/playbook/${date}?market=${market}`);
          const stocks = data.stock_playbooks ?? [];
          if (stocks.length === 0) {
            el.innerHTML = '<p class="empty-msg">오늘 플레이북 없음</p>';
            return;
          }
          el.innerHTML = stocks.map(sp =>
            `<details><summary>${esc(sp.stock_code ?? '?')} — ${esc(sp.signal ?? '')}</summary>` +
            `<pre>${esc(JSON.stringify(sp, null, 2))}</pre></details>`
          ).join('');
        } catch {
          el.innerHTML = '<p class="empty-msg">플레이북 없음 (오늘 미생성 또는 API 오류)</p>';
        }
      }
      async function fetchScorecard() {
        const market = document.getElementById('sc-market-select').value;
        const date = todayStr();
        document.getElementById('sc-date').textContent = date;
        const el = document.getElementById('scorecard-grid');
        try {
          const data = await fetchJSON(`/api/scorecard/${date}?market=${market}`);
          const sc = data.scorecard ?? {};
          const entries = Object.entries(sc);
          if (entries.length === 0) {
            el.innerHTML = '<p class="empty-msg">스코어카드 없음</p>';
            return;
          }
          el.className = 'scorecard-grid';
          el.innerHTML = entries.map(([k, v]) => `
            <div class="kpi-card">
              <div class="kpi-label">${esc(k)}</div>
              <div class="kpi-value">${typeof v === 'number' ? v.toFixed(2) : esc(String(v))}</div>
            </div>`).join('');
        } catch {
          el.innerHTML = '<p class="empty-msg">스코어카드 없음 (오늘 미생성 또는 API 오류)</p>';
        }
      }
      async function fetchScenarios() {
        const market = document.getElementById('scen-market-select').value;
        const date = todayStr();
        const el = document.getElementById('scenarios-content');
        try {
          const data = await fetchJSON(`/api/scenarios/active?market=${market}&date_str=${date}&limit=50`);
          const matches = data.matches ?? [];
          if (matches.length === 0) {
            el.innerHTML = '<p class="empty-msg">활성 시나리오 없음</p>';
            return;
          }
          el.innerHTML = `<table class="scenarios-table">
            <thead><tr><th>종목</th><th>신호</th><th>신뢰도</th><th>매칭 조건</th></tr></thead>
            <tbody>${matches.map(m => `
              <tr>
                <td>${esc(m.stock_code)}</td>
                <td>${esc(m.signal ?? '-')}</td>
                <td>${esc(m.confidence ?? '-')}</td>
                <td><code style="font-size:11px">${esc(JSON.stringify(m.scenario_match ?? {}))}</code></td>
              </tr>`).join('')}
            </tbody></table>`;
        } catch {
          el.innerHTML = '<p class="empty-msg">데이터 없음</p>';
        }
      }
      async function fetchContext() {
        const layer = document.getElementById('ctx-layer-select').value;
        const limit = Math.min(Math.max(parseInt(document.getElementById('ctx-limit').value, 10) || 20, 1), 200);
        const el = document.getElementById('context-content');
        try {
          const data = await fetchJSON(`/api/context/${layer}?limit=${limit}`);
          const entries = data.entries ?? [];
          if (entries.length === 0) {
            el.innerHTML = '<p class="empty-msg">컨텍스트 없음</p>';
            return;
          }
          el.innerHTML = `<table class="context-table">
            <thead><tr><th>timeframe</th><th>key</th><th>value</th><th>updated</th></tr></thead>
            <tbody>${entries.map(e => `
              <tr>
                <td>${esc(e.timeframe)}</td>
                <td>${esc(e.key)}</td>
                <td><div class="context-value">${esc(JSON.stringify(e.value ?? e.raw_value))}</div></td>
                <td style="font-size:11px;color:var(--muted)">${esc((e.updated_at ?? '').slice(0, 16))}</td>
              </tr>`).join('')}
            </tbody></table>`;
        } catch {
          el.innerHTML = '<p class="empty-msg">데이터 없음</p>';
        }
      }
      async function refreshAll() {
        document.getElementById('last-updated').textContent = '업데이트 중...';
        await Promise.all([
          fetchStatus(),
          fetchPerformance(),
          fetchPositions(),
          fetchPnlHistory(currentDays),
          fetchDecisions(currentMarket),
          fetchPlaybook(),
          fetchScorecard(),
          fetchScenarios(),
          fetchContext(),
        ]);
        const now = new Date();
        const timeStr = now.toLocaleTimeString('ko-KR', { hour: '2-digit', minute: '2-digit', second: '2-digit', hour12: false });
        document.getElementById('last-updated').textContent = `마지막 업데이트: ${timeStr}`;
      }
      // Initial load
      refreshAll();
      // Auto-refresh every 30 seconds
      setInterval(refreshAll, 30000);
    </script>
  </body>
 </html>
--- a/src/db.py
+++ b/src/db.py
@@ -14,11 +14,6 @@ def init_db(db_path: str) -> sqlite3.Connection:
    if db_path != ":memory:":
        Path(db_path).parent.mkdir(parents=True, exist_ok=True)
    conn = sqlite3.connect(db_path)
    # Enable WAL mode for concurrent read/write (dashboard + trading loop).
    # WAL does not apply to in-memory databases.
    if db_path != ":memory:":
        conn.execute("PRAGMA journal_mode=WAL")
        conn.execute("PRAGMA busy_timeout=5000")
    conn.execute(
        """
        CREATE TABLE IF NOT EXISTS trades (
@@ -33,13 +28,12 @@ def init_db(db_path: str) -> sqlite3.Connection:
            pnl REAL DEFAULT 0.0,
            market TEXT DEFAULT 'KR',
            exchange_code TEXT DEFAULT 'KRX',
-            decision_id TEXT,
+            decision_id TEXT
            mode TEXT DEFAULT 'paper'
        )
        """
    )
-    # Migration: Add columns if they don't exist (backward-compatible schema upgrades)
+    # Migration: Add market and exchange_code columns if they don't exist
    cursor = conn.execute("PRAGMA table_info(trades)")
    columns = {row[1] for row in cursor.fetchall()}
@@ -51,8 +45,6 @@ def init_db(db_path: str) -> sqlite3.Connection:
        conn.execute("ALTER TABLE trades ADD COLUMN selection_context TEXT")
    if "decision_id" not in columns:
        conn.execute("ALTER TABLE trades ADD COLUMN decision_id TEXT")
    if "mode" not in columns:
        conn.execute("ALTER TABLE trades ADD COLUMN mode TEXT DEFAULT 'paper'")
    # Context tree tables for multi-layered memory management
    conn.execute(
@@ -139,25 +131,6 @@ def init_db(db_path: str) -> sqlite3.Connection:
    conn.execute(
        "CREATE INDEX IF NOT EXISTS idx_decision_logs_confidence ON decision_logs(confidence)"
    )
    # Index for open-position queries (partition by stock_code, market, ordered by timestamp)
    conn.execute(
        "CREATE INDEX IF NOT EXISTS idx_trades_stock_market_ts"
        " ON trades (stock_code, market, timestamp DESC)"
    )
    # Lightweight key-value store for trading system runtime metrics (dashboard use only)
    # Intentionally separate from the AI context tree to preserve separation of concerns.
    conn.execute(
        """
        CREATE TABLE IF NOT EXISTS system_metrics (
            key        TEXT PRIMARY KEY,
            value      TEXT NOT NULL,
            updated_at TEXT NOT NULL
        )
        """
    )
    conn.commit()
    return conn
@@ -175,7 +148,6 @@ def log_trade(
    exchange_code: str = "KRX",
    selection_context: dict[str, any] | None = None,
    decision_id: str | None = None,
    mode: str = "paper",
 ) -> None:
    """Insert a trade record into the database.
@@ -191,8 +163,6 @@ def log_trade(
        market: Market code
        exchange_code: Exchange code
        selection_context: Scanner selection data (RSI, volume_ratio, signal, score)
        decision_id: Unique decision identifier for audit linking
        mode: Trading mode ('paper' or 'live') for data separation
    """
    # Serialize selection context to JSON
    context_json = json.dumps(selection_context) if selection_context else None
@@ -201,10 +171,9 @@ def log_trade(
        """
        INSERT INTO trades (
            timestamp, stock_code, action, confidence, rationale,
-            quantity, price, pnl, market, exchange_code, selection_context, decision_id,
+            quantity, price, pnl, market, exchange_code, selection_context, decision_id
            mode
        )
-        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (
            datetime.now(UTC).isoformat(),
@@ -219,7 +188,6 @@ def log_trade(
            exchange_code,
            context_json,
            decision_id,
            mode,
        ),
    )
    conn.commit()
@@ -254,11 +222,10 @@ def get_open_position(
    """Return open position if latest trade is BUY, else None."""
    cursor = conn.execute(
        """
-        SELECT action, decision_id, price, quantity, timestamp
+        SELECT action, decision_id, price, quantity
        FROM trades
        WHERE stock_code = ?
          AND market = ?
          AND action IN ('BUY', 'SELL')
        ORDER BY timestamp DESC
        LIMIT 1
        """,
@@ -267,7 +234,7 @@ def get_open_position(
    row = cursor.fetchone()
    if not row or row[0] != "BUY":
        return None
-    return {"decision_id": row[1], "price": row[2], "quantity": row[3], "timestamp": row[4]}
+    return {"decision_id": row[1], "price": row[2], "quantity": row[3]}
 def get_recent_symbols(
--- a/src/main.py
+++ b/src/main.py
--- a/src/notifications/telegram_client.py
+++ b/src/notifications/telegram_client.py
@@ -4,9 +4,8 @@ import asyncio
 import logging
 import time
 from collections.abc import Awaitable, Callable
-from dataclasses import dataclass, fields
+from dataclasses import dataclass
 from enum import Enum
 from typing import ClassVar
 import aiohttp
@@ -59,45 +58,6 @@ class LeakyBucket:
                self._tokens -= 1.0
@dataclass
 class NotificationFilter:
    """Granular on/off flags for each notification type.
    circuit_breaker is intentionally omitted — it is always sent regardless.
    """
    # Maps user-facing command keys to dataclass field names
    KEYS: ClassVar[dict[str, str]] = {
        "trades": "trades",
        "market": "market_open_close",
        "fatfinger": "fat_finger",
        "system": "system_events",
        "playbook": "playbook",
        "scenario": "scenario_match",
        "errors": "errors",
    }
    trades: bool = True
    market_open_close: bool = True
    fat_finger: bool = True
    system_events: bool = True
    playbook: bool = True
    scenario_match: bool = True
    errors: bool = True
    def set_flag(self, key: str, value: bool) -> bool:
        """Set a filter flag by user-facing key. Returns False if key is unknown."""
        field = self.KEYS.get(key.lower())
        if field is None:
            return False
        setattr(self, field, value)
        return True
    def as_dict(self) -> dict[str, bool]:
        """Return {user_key: current_value} for display."""
        return {k: getattr(self, field) for k, field in self.KEYS.items()}
@dataclass
 class NotificationMessage:
    """Internal notification message structure."""
@@ -119,7 +79,6 @@ class TelegramClient:
        chat_id: str | None = None,
        enabled: bool = True,
        rate_limit: float = DEFAULT_RATE,
        notification_filter: NotificationFilter | None = None,
    ) -> None:
        """
        Initialize Telegram client.
@@ -129,14 +88,12 @@ class TelegramClient:
            chat_id: Target chat ID (user or group)
            enabled: Enable/disable notifications globally
            rate_limit: Maximum messages per second
            notification_filter: Granular per-type on/off flags
        """
        self._bot_token = bot_token
        self._chat_id = chat_id
        self._enabled = enabled
        self._rate_limiter = LeakyBucket(rate=rate_limit)
        self._session: aiohttp.ClientSession | None = None
        self._filter = notification_filter if notification_filter is not None else NotificationFilter()
        if not enabled:
            logger.info("Telegram notifications disabled via configuration")
@@ -161,26 +118,6 @@ class TelegramClient:
        if self._session is not None and not self._session.closed:
            await self._session.close()
    def set_notification(self, key: str, value: bool) -> bool:
        """Toggle a notification type by user-facing key at runtime.
        Args:
            key: User-facing key (e.g. "scenario", "market", "all")
            value: True to enable, False to disable
        Returns:
            True if key was valid, False if unknown.
        """
        if key == "all":
            for k in NotificationFilter.KEYS:
                self._filter.set_flag(k, value)
            return True
        return self._filter.set_flag(key, value)
    def filter_status(self) -> dict[str, bool]:
        """Return current per-type filter state keyed by user-facing names."""
        return self._filter.as_dict()
    async def send_message(self, text: str, parse_mode: str = "HTML") -> bool:
        """
        Send a generic text message to Telegram.
@@ -256,8 +193,6 @@ class TelegramClient:
            price: Execution price
            confidence: AI confidence level (0-100)
        """
        if not self._filter.trades:
            return
        emoji = "🟢" if action == "BUY" else "🔴"
        message = (
            f"<b>{emoji} {action}</b>\n"
@@ -277,8 +212,6 @@ class TelegramClient:
        Args:
            market_name: Name of the market (e.g., "Korea", "United States")
        """
        if not self._filter.market_open_close:
            return
        message = f"<b>Market Open</b>\n{market_name} trading session started"
        await self._send_notification(
            NotificationMessage(priority=NotificationPriority.LOW, message=message)
@@ -292,8 +225,6 @@ class TelegramClient:
            market_name: Name of the market
            pnl_pct: Final P&L percentage for the session
        """
        if not self._filter.market_open_close:
            return
        pnl_sign = "+" if pnl_pct >= 0 else ""
        pnl_emoji = "📈" if pnl_pct >= 0 else "📉"
        message = (
@@ -340,8 +271,6 @@ class TelegramClient:
            total_cash: Total available cash
            max_pct: Maximum allowed percentage
        """
        if not self._filter.fat_finger:
            return
        attempted_pct = (order_amount / total_cash) * 100 if total_cash > 0 else 0
        message = (
            f"<b>Fat-Finger Protection</b>\n"
@@ -364,8 +293,6 @@ class TelegramClient:
            mode: Trading mode ("paper" or "live")
            enabled_markets: List of enabled market codes
        """
        if not self._filter.system_events:
            return
        mode_emoji = "📝" if mode == "paper" else "💰"
        markets_str = ", ".join(enabled_markets)
        message = (
@@ -393,8 +320,6 @@ class TelegramClient:
            scenario_count: Total number of scenarios
            token_count: Gemini token usage for the playbook
        """
        if not self._filter.playbook:
            return
        message = (
            f"<b>Playbook Generated</b>\n"
            f"Market: {market}\n"
@@ -422,8 +347,6 @@ class TelegramClient:
            condition_summary: Short summary of the matched condition
            confidence: Scenario confidence (0-100)
        """
        if not self._filter.scenario_match:
            return
        message = (
            f"<b>Scenario Matched</b>\n"
            f"Symbol: <code>{stock_code}</code>\n"
@@ -443,8 +366,6 @@ class TelegramClient:
            market: Market code (e.g., "KR", "US")
            reason: Failure reason summary
        """
        if not self._filter.playbook:
            return
        message = (
            f"<b>Playbook Failed</b>\n"
            f"Market: {market}\n"
@@ -461,8 +382,6 @@ class TelegramClient:
        Args:
            reason: Reason for shutdown (e.g., "Normal shutdown", "Circuit breaker")
        """
        if not self._filter.system_events:
            return
        message = f"<b>System Shutdown</b>\n{reason}"
        priority = (
            NotificationPriority.CRITICAL
@@ -473,48 +392,6 @@ class TelegramClient:
            NotificationMessage(priority=priority, message=message)
        )
    async def notify_unfilled_order(
        self,
        stock_code: str,
        market: str,
        action: str,
        quantity: int,
        outcome: str,
        new_price: float | None = None,
    ) -> None:
        """Notify about an unfilled overseas order that was cancelled or resubmitted.
        Args:
            stock_code: Stock ticker symbol.
            market: Exchange/market code (e.g., "NASD", "SEHK").
            action: "BUY" or "SELL".
            quantity: Unfilled quantity.
            outcome: "cancelled" or "resubmitted".
            new_price: New order price if resubmitted (None if only cancelled).
        """
        if not self._filter.trades:
            return
        # SELL resubmit is high priority — position liquidation at risk.
        # BUY cancel is medium priority — only cash is freed.
        priority = (
            NotificationPriority.HIGH
            if action == "SELL"
            else NotificationPriority.MEDIUM
        )
        outcome_emoji = "🔄" if outcome == "resubmitted" else "❌"
        outcome_label = "재주문" if outcome == "resubmitted" else "취소됨"
        action_emoji = "🔴" if action == "SELL" else "🟢"
        lines = [
            f"<b>{outcome_emoji} 미체결 주문 {outcome_label}</b>",
            f"Symbol: <code>{stock_code}</code> ({market})",
            f"Action: {action_emoji} {action}",
            f"Quantity: {quantity:,} shares",
        ]
        if new_price is not None:
            lines.append(f"New Price: {new_price:.4f}")
        message = "\n".join(lines)
        await self._send_notification(NotificationMessage(priority=priority, message=message))
    async def notify_error(
        self, error_type: str, error_msg: str, context: str
    ) -> None:
@@ -526,8 +403,6 @@ class TelegramClient:
            error_msg: Error message
            context: Error context (e.g., stock code, market)
        """
        if not self._filter.errors:
            return
        message = (
            f"<b>Error: {error_type}</b>\n"
            f"Context: {context}\n"
@@ -554,7 +429,6 @@ class TelegramCommandHandler:
        self._client = client
        self._polling_interval = polling_interval
        self._commands: dict[str, Callable[[], Awaitable[None]]] = {}
        self._commands_with_args: dict[str, Callable[[list[str]], Awaitable[None]]] = {}
        self._last_update_id = 0
        self._polling_task: asyncio.Task[None] | None = None
        self._running = False
@@ -563,7 +437,7 @@ class TelegramCommandHandler:
        self, command: str, handler: Callable[[], Awaitable[None]]
    ) -> None:
        """
-        Register a command handler (no arguments).
+        Register a command handler.
        Args:
            command: Command name (without leading slash, e.g., "start")
@@ -572,19 +446,6 @@ class TelegramCommandHandler:
        self._commands[command] = handler
        logger.debug("Registered command handler: /%s", command)
    def register_command_with_args(
        self, command: str, handler: Callable[[list[str]], Awaitable[None]]
    ) -> None:
        """
        Register a command handler that receives trailing arguments.
        Args:
            command: Command name (without leading slash, e.g., "notify")
            handler: Async function receiving list of argument tokens
        """
        self._commands_with_args[command] = handler
        logger.debug("Registered command handler (with args): /%s", command)
    async def start_polling(self) -> None:
        """Start long polling for commands."""
        if self._running:
@@ -646,19 +507,9 @@ class TelegramCommandHandler:
            async with session.post(url, json=payload) as resp:
                if resp.status != 200:
                    error_text = await resp.text()
-                    if resp.status == 409:
+                    logger.error(
-                        # Another bot instance is already polling — stop this poller entirely.
+                        "getUpdates API error (status=%d): %s", resp.status, error_text
-                        # Retrying would keep conflicting with the other instance.
+                    )
                        self._running = False
                        logger.warning(
                            "Telegram conflict (409): another instance is already polling. "
                            "Disabling Telegram commands for this process. "
                            "Ensure only one instance of The Ouroboros is running at a time.",
                        )
                    else:
                        logger.error(
                            "getUpdates API error (status=%d): %s", resp.status, error_text
                        )
                    return []
                data = await resp.json()
@@ -715,14 +566,11 @@ class TelegramCommandHandler:
            # Remove @botname suffix if present (for group chats)
            command_name = command_parts[0].split("@")[0]
-            # Execute handler (args-aware handlers take priority)
+            # Execute handler
-            args_handler = self._commands_with_args.get(command_name)
+            handler = self._commands.get(command_name)
-            if args_handler:
+            if handler:
                logger.info("Executing command: /%s %s", command_name, command_parts[1:])
                await args_handler(command_parts[1:])
            elif command_name in self._commands:
                logger.info("Executing command: /%s", command_name)
-                await self._commands[command_name]()
+                await handler()
            else:
                logger.debug("Unknown command: /%s", command_name)
                await self._client.send_message(
--- a/src/strategy/models.py
+++ b/src/strategy/models.py
@@ -46,18 +46,6 @@ class StockCondition(BaseModel):
    The ScenarioEngine evaluates all non-None fields as AND conditions.
    A condition matches only if ALL specified fields are satisfied.
    Technical indicator fields:
        rsi_below / rsi_above — RSI threshold
        volume_ratio_above / volume_ratio_below — volume vs previous day
        price_above / price_below — absolute price level
        price_change_pct_above / price_change_pct_below — intraday % change
    Position-aware fields (require market_data enrichment from open position):
        unrealized_pnl_pct_above — matches if unrealized P&L > threshold (e.g. 3.0 → +3%)
        unrealized_pnl_pct_below — matches if unrealized P&L < threshold (e.g. -2.0 → -2%)
        holding_days_above — matches if position held for more than N days
        holding_days_below — matches if position held for fewer than N days
    """
    rsi_below: float | None = None
@@ -68,10 +56,6 @@ class StockCondition(BaseModel):
    price_below: float | None = None
    price_change_pct_above: float | None = None
    price_change_pct_below: float | None = None
    unrealized_pnl_pct_above: float | None = None
    unrealized_pnl_pct_below: float | None = None
    holding_days_above: int | None = None
    holding_days_below: int | None = None
    def has_any_condition(self) -> bool:
        """Check if at least one condition field is set."""
@@ -86,10 +70,6 @@ class StockCondition(BaseModel):
                self.price_below,
                self.price_change_pct_above,
                self.price_change_pct_below,
                self.unrealized_pnl_pct_above,
                self.unrealized_pnl_pct_below,
                self.holding_days_above,
                self.holding_days_below,
            )
        )
--- a/src/strategy/pre_market_planner.py
+++ b/src/strategy/pre_market_planner.py
@@ -1,8 +1,7 @@
 """Pre-market planner — generates DayPlaybook via Gemini before market open.
 One Gemini API call per market per day. Candidates come from SmartVolatilityScanner.
-On failure, returns a smart rule-based fallback playbook that uses scanner signals
+On failure, returns a defensive playbook (all HOLD, no trades).
 (momentum/oversold) to generate BUY conditions, avoiding the all-HOLD problem.
 """
 from __future__ import annotations
@@ -75,7 +74,6 @@ class PreMarketPlanner:
        market: str,
        candidates: list[ScanCandidate],
        today: date | None = None,
        current_holdings: list[dict] | None = None,
    ) -> DayPlaybook:
        """Generate a DayPlaybook for a market using Gemini.
@@ -83,10 +81,6 @@ class PreMarketPlanner:
            market: Market code ("KR" or "US")
            candidates: Stock candidates from SmartVolatilityScanner
            today: Override date (defaults to date.today()). Use market-local date.
            current_holdings: Currently held positions with entry_price and unrealized_pnl_pct.
                Each dict: {"stock_code": str, "name": str, "qty": int,
                            "entry_price": float, "unrealized_pnl_pct": float,
                            "holding_days": int}
        Returns:
            DayPlaybook with scenarios. Empty/defensive if no candidates or failure.
@@ -111,7 +105,6 @@ class PreMarketPlanner:
                context_data,
                self_market_scorecard,
                cross_market,
                current_holdings=current_holdings,
            )
            # 3. Call Gemini
@@ -124,8 +117,7 @@ class PreMarketPlanner:
            # 4. Parse response
            playbook = self._parse_response(
-                decision.rationale, today, market, candidates, cross_market,
+                decision.rationale, today, market, candidates, cross_market
                current_holdings=current_holdings,
            )
            playbook_with_tokens = playbook.model_copy(
                update={"token_count": decision.token_count}
@@ -142,7 +134,7 @@ class PreMarketPlanner:
        except Exception:
            logger.exception("Playbook generation failed for %s", market)
            if self._settings.DEFENSIVE_PLAYBOOK_ON_FAILURE:
-                return self._smart_fallback_playbook(today, market, candidates, self._settings)
+                return self._defensive_playbook(today, market, candidates)
            return self._empty_playbook(today, market)
    def build_cross_market_context(
@@ -237,7 +229,6 @@ class PreMarketPlanner:
        context_data: dict[str, Any],
        self_market_scorecard: dict[str, Any] | None,
        cross_market: CrossMarketContext | None,
        current_holdings: list[dict] | None = None,
    ) -> str:
        """Build a structured prompt for Gemini to generate scenario JSON."""
        max_scenarios = self._settings.MAX_SCENARIOS_PER_STOCK
@@ -249,26 +240,6 @@ class PreMarketPlanner:
            for c in candidates
        )
        holdings_text = ""
        if current_holdings:
            lines = []
            for h in current_holdings:
                code = h.get("stock_code", "")
                name = h.get("name", "")
                qty = h.get("qty", 0)
                entry_price = h.get("entry_price", 0.0)
                pnl_pct = h.get("unrealized_pnl_pct", 0.0)
                holding_days = h.get("holding_days", 0)
                lines.append(
                    f"  - {code} ({name}): {qty}주 @ {entry_price:,.0f}, "
                    f"미실현손익 {pnl_pct:+.2f}%, 보유 {holding_days}일"
                )
            holdings_text = (
                "\n## Current Holdings (보유 중 — SELL/HOLD 전략 고려 필요)\n"
                + "\n".join(lines)
                + "\n"
            )
        cross_market_text = ""
        if cross_market:
            cross_market_text = (
@@ -301,20 +272,10 @@ class PreMarketPlanner:
                    for key, value in list(layer_data.items())[:5]:
                        context_text += f"  - {key}: {value}\n"
        holdings_instruction = ""
        if current_holdings:
            holding_codes = [h.get("stock_code", "") for h in current_holdings]
            holdings_instruction = (
                f"- Also include SELL/HOLD scenarios for held stocks: "
                f"{', '.join(holding_codes)} "
                f"(even if not in candidates list)\n"
            )
        return (
            f"You are a pre-market trading strategist for the {market} market.\n"
            f"Generate structured trading scenarios for today.\n\n"
            f"## Candidates (from volatility scanner)\n{candidates_text}\n"
            f"{holdings_text}"
            f"{self_market_text}"
            f"{cross_market_text}"
            f"{context_text}\n"
@@ -332,8 +293,7 @@ class PreMarketPlanner:
            f'      "stock_code": "...",\n'
            f'      "scenarios": [\n'
            f'        {{\n'
-            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0,'
+            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0}},\n'
            f' "unrealized_pnl_pct_above": 3.0, "holding_days_above": 5}},\n'
            f'          "action": "BUY|SELL|HOLD",\n'
            f'          "confidence": 85,\n'
            f'          "allocation_pct": 10.0,\n'
@@ -347,8 +307,7 @@ class PreMarketPlanner:
            f'}}\n\n'
            f"Rules:\n"
            f"- Max {max_scenarios} scenarios per stock\n"
-            f"- Candidates list is the primary source for BUY candidates\n"
+            f"- Only use stocks from the candidates list\n"
            f"{holdings_instruction}"
            f"- Confidence 0-100 (80+ for actionable trades)\n"
            f"- stop_loss_pct must be <= 0, take_profit_pct must be >= 0\n"
            f"- Return ONLY the JSON, no markdown fences or explanation\n"
@@ -361,19 +320,12 @@ class PreMarketPlanner:
        market: str,
        candidates: list[ScanCandidate],
        cross_market: CrossMarketContext | None,
        current_holdings: list[dict] | None = None,
    ) -> DayPlaybook:
        """Parse Gemini's JSON response into a validated DayPlaybook."""
        cleaned = self._extract_json(response_text)
        data = json.loads(cleaned)
        valid_codes = {c.stock_code for c in candidates}
        # Holdings are also valid — AI may generate SELL/HOLD scenarios for them
        if current_holdings:
            for h in current_holdings:
                code = h.get("stock_code", "")
                if code:
                    valid_codes.add(code)
        # Parse market outlook
        outlook_str = data.get("market_outlook", "neutral")
@@ -437,10 +389,6 @@ class PreMarketPlanner:
                price_below=cond_data.get("price_below"),
                price_change_pct_above=cond_data.get("price_change_pct_above"),
                price_change_pct_below=cond_data.get("price_change_pct_below"),
                unrealized_pnl_pct_above=cond_data.get("unrealized_pnl_pct_above"),
                unrealized_pnl_pct_below=cond_data.get("unrealized_pnl_pct_below"),
                holding_days_above=cond_data.get("holding_days_above"),
                holding_days_below=cond_data.get("holding_days_below"),
            )
            if not condition.has_any_condition():
@@ -522,99 +470,3 @@ class PreMarketPlanner:
                ),
            ],
        )
    @staticmethod
    def _smart_fallback_playbook(
        today: date,
        market: str,
        candidates: list[ScanCandidate],
        settings: Settings,
    ) -> DayPlaybook:
        """Rule-based fallback playbook when Gemini is unavailable.
        Uses scanner signals (RSI, volume_ratio) to generate meaningful BUY
        conditions instead of the all-SELL defensive playbook.  Candidates are
        already pre-qualified by SmartVolatilityScanner, so we trust their
        signals and build actionable scenarios from them.
        Scenario logic per candidate:
        - momentum signal: BUY when volume_ratio exceeds scanner threshold
        - oversold signal: BUY when RSI is below oversold threshold
        - always: SELL stop-loss at -3.0% as guard
        """
        stock_playbooks = []
        for c in candidates:
            scenarios: list[StockScenario] = []
            if c.signal == "momentum":
                scenarios.append(
                    StockScenario(
                        condition=StockCondition(
                            volume_ratio_above=settings.VOL_MULTIPLIER,
                        ),
                        action=ScenarioAction.BUY,
                        confidence=80,
                        allocation_pct=10.0,
                        stop_loss_pct=-3.0,
                        take_profit_pct=5.0,
                        rationale=(
                            f"Rule-based BUY: momentum signal, "
                            f"volume={c.volume_ratio:.1f}x (fallback planner)"
                        ),
                    )
                )
            elif c.signal == "oversold":
                scenarios.append(
                    StockScenario(
                        condition=StockCondition(
                            rsi_below=settings.RSI_OVERSOLD_THRESHOLD,
                        ),
                        action=ScenarioAction.BUY,
                        confidence=80,
                        allocation_pct=10.0,
                        stop_loss_pct=-3.0,
                        take_profit_pct=5.0,
                        rationale=(
                            f"Rule-based BUY: oversold signal, "
                            f"RSI={c.rsi:.0f} (fallback planner)"
                        ),
                    )
                )
            # Always add stop-loss guard
            scenarios.append(
                StockScenario(
                    condition=StockCondition(price_change_pct_below=-3.0),
                    action=ScenarioAction.SELL,
                    confidence=90,
                    stop_loss_pct=-3.0,
                    rationale="Rule-based stop-loss (fallback planner)",
                )
            )
            stock_playbooks.append(
                StockPlaybook(
                    stock_code=c.stock_code,
                    scenarios=scenarios,
                )
            )
        logger.info(
            "Smart fallback playbook for %s: %d stocks with rule-based BUY/SELL conditions",
            market,
            len(stock_playbooks),
        )
        return DayPlaybook(
            date=today,
            market=market,
            market_outlook=MarketOutlook.NEUTRAL,
            default_action=ScenarioAction.HOLD,
            stock_playbooks=stock_playbooks,
            global_rules=[
                GlobalRule(
                    condition="portfolio_pnl_pct < -2.0",
                    action=ScenarioAction.REDUCE_ALL,
                    rationale="Defensive: reduce on loss threshold",
                ),
            ],
        )
--- a/src/strategy/scenario_engine.py
+++ b/src/strategy/scenario_engine.py
@@ -206,37 +206,6 @@ class ScenarioEngine:
        if condition.price_change_pct_below is not None:
            checks.append(price_change_pct is not None and price_change_pct < condition.price_change_pct_below)
        # Position-aware conditions
        unrealized_pnl_pct = self._safe_float(market_data.get("unrealized_pnl_pct"))
        if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
            if "unrealized_pnl_pct" not in market_data:
                self._warn_missing_key("unrealized_pnl_pct")
        if condition.unrealized_pnl_pct_above is not None:
            checks.append(
                unrealized_pnl_pct is not None
                and unrealized_pnl_pct > condition.unrealized_pnl_pct_above
            )
        if condition.unrealized_pnl_pct_below is not None:
            checks.append(
                unrealized_pnl_pct is not None
                and unrealized_pnl_pct < condition.unrealized_pnl_pct_below
            )
        holding_days = self._safe_float(market_data.get("holding_days"))
        if condition.holding_days_above is not None or condition.holding_days_below is not None:
            if "holding_days" not in market_data:
                self._warn_missing_key("holding_days")
        if condition.holding_days_above is not None:
            checks.append(
                holding_days is not None
                and holding_days > condition.holding_days_above
            )
        if condition.holding_days_below is not None:
            checks.append(
                holding_days is not None
                and holding_days < condition.holding_days_below
            )
        return len(checks) > 0 and all(checks)
    def _evaluate_global_condition(
@@ -297,9 +266,5 @@ class ScenarioEngine:
            details["current_price"] = self._safe_float(market_data.get("current_price"))
        if condition.price_change_pct_above is not None or condition.price_change_pct_below is not None:
            details["price_change_pct"] = self._safe_float(market_data.get("price_change_pct"))
        if condition.unrealized_pnl_pct_above is not None or condition.unrealized_pnl_pct_below is not None:
            details["unrealized_pnl_pct"] = self._safe_float(market_data.get("unrealized_pnl_pct"))
        if condition.holding_days_above is not None or condition.holding_days_below is not None:
            details["holding_days"] = self._safe_float(market_data.get("holding_days"))
        return details
--- a/tests/test_backup.py
+++ b/tests/test_backup.py
@@ -3,11 +3,9 @@
 from __future__ import annotations
 import sqlite3
 import sys
 import tempfile
 from datetime import UTC, datetime, timedelta
 from pathlib import Path
 from unittest.mock import MagicMock, patch
 import pytest
@@ -365,435 +363,3 @@ class TestHealthMonitor:
        assert "timestamp" in report
        assert "checks" in report
        assert len(report["checks"]) == 3
 # ---------------------------------------------------------------------------
 # BackupExporter — additional coverage for previously uncovered branches
 # ---------------------------------------------------------------------------
@pytest.fixture
 def empty_db(tmp_path: Path) -> Path:
    """Create a temporary database with NO trade records."""
    db_path = tmp_path / "empty_trades.db"
    conn = sqlite3.connect(str(db_path))
    conn.execute(
        """CREATE TABLE trades (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            timestamp TEXT NOT NULL,
            stock_code TEXT NOT NULL,
            action TEXT NOT NULL,
            quantity INTEGER NOT NULL,
            price REAL NOT NULL,
            confidence INTEGER NOT NULL,
            rationale TEXT,
            pnl REAL DEFAULT 0.0
        )"""
    )
    conn.commit()
    conn.close()
    return db_path
 class TestBackupExporterAdditional:
    """Cover branches missed in the original TestBackupExporter suite."""
    def test_export_all_default_formats(self, temp_db: Path, tmp_path: Path) -> None:
        """export_all with formats=None must default to JSON+CSV+Parquet path."""
        exporter = BackupExporter(str(temp_db))
        # formats=None triggers the default list assignment (line 62)
        results = exporter.export_all(tmp_path / "out", formats=None, compress=False)
        # JSON and CSV must always succeed; Parquet needs pyarrow
        assert ExportFormat.JSON in results
        assert ExportFormat.CSV in results
    def test_export_all_logs_error_on_failure(
        self, temp_db: Path, tmp_path: Path
    ) -> None:
        """export_all must log an error and continue when one format fails."""
        exporter = BackupExporter(str(temp_db))
        # Patch _export_format to raise on JSON, succeed on CSV
        original = exporter._export_format
        def failing_export(fmt, *args, **kwargs):  # type: ignore[no-untyped-def]
            if fmt == ExportFormat.JSON:
                raise RuntimeError("simulated failure")
            return original(fmt, *args, **kwargs)
        exporter._export_format = failing_export  # type: ignore[method-assign]
        results = exporter.export_all(
            tmp_path / "out",
            formats=[ExportFormat.JSON, ExportFormat.CSV],
            compress=False,
        )
        # JSON failed → not in results; CSV succeeded → in results
        assert ExportFormat.JSON not in results
        assert ExportFormat.CSV in results
    def test_export_csv_empty_trades_no_compress(
        self, empty_db: Path, tmp_path: Path
    ) -> None:
        """CSV export with no trades and compress=False must write header row only."""
        exporter = BackupExporter(str(empty_db))
        results = exporter.export_all(
            tmp_path / "out",
            formats=[ExportFormat.CSV],
            compress=False,
        )
        assert ExportFormat.CSV in results
        out = results[ExportFormat.CSV]
        assert out.exists()
        content = out.read_text()
        assert "timestamp" in content
    def test_export_csv_empty_trades_compressed(
        self, empty_db: Path, tmp_path: Path
    ) -> None:
        """CSV export with no trades and compress=True must write gzipped header."""
        import gzip
        exporter = BackupExporter(str(empty_db))
        results = exporter.export_all(
            tmp_path / "out",
            formats=[ExportFormat.CSV],
            compress=True,
        )
        assert ExportFormat.CSV in results
        out = results[ExportFormat.CSV]
        assert out.suffix == ".gz"
        with gzip.open(out, "rt", encoding="utf-8") as f:
            content = f.read()
        assert "timestamp" in content
    def test_export_csv_with_data_compressed(
        self, temp_db: Path, tmp_path: Path
    ) -> None:
        """CSV export with data and compress=True must write gzipped rows."""
        import gzip
        exporter = BackupExporter(str(temp_db))
        results = exporter.export_all(
            tmp_path / "out",
            formats=[ExportFormat.CSV],
            compress=True,
        )
        assert ExportFormat.CSV in results
        out = results[ExportFormat.CSV]
        with gzip.open(out, "rt", encoding="utf-8") as f:
            lines = f.readlines()
        # Header + 3 data rows
        assert len(lines) == 4
    def test_export_parquet_raises_import_error_without_pyarrow(
        self, temp_db: Path, tmp_path: Path
    ) -> None:
        """Parquet export must raise ImportError when pyarrow is not installed."""
        exporter = BackupExporter(str(temp_db))
        with patch.dict(sys.modules, {"pyarrow": None, "pyarrow.parquet": None}):
            try:
                import pyarrow  # noqa: F401
                pytest.skip("pyarrow is installed; cannot test ImportError path")
            except ImportError:
                pass
            results = exporter.export_all(
                tmp_path / "out",
                formats=[ExportFormat.PARQUET],
                compress=False,
            )
            # Parquet export fails gracefully; result dict should not contain it
            assert ExportFormat.PARQUET not in results
 # ---------------------------------------------------------------------------
 # CloudStorage — mocked boto3 tests
 # ---------------------------------------------------------------------------
@pytest.fixture
 def mock_boto3_module():
    """Inject a fake boto3 into sys.modules for the duration of the test."""
    mock = MagicMock()
    with patch.dict(sys.modules, {"boto3": mock}):
        yield mock
@pytest.fixture
 def s3_config():
    """Minimal S3Config for tests."""
    from src.backup.cloud_storage import S3Config
    return S3Config(
        endpoint_url="http://localhost:9000",
        access_key="minioadmin",
        secret_key="minioadmin",
        bucket_name="test-bucket",
        region="us-east-1",
    )
 class TestCloudStorage:
    """Test CloudStorage using mocked boto3."""
    def test_init_creates_s3_client(self, mock_boto3_module, s3_config) -> None:
        """CloudStorage.__init__ must call boto3.client with the correct args."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        mock_boto3_module.client.assert_called_once()
        call_kwargs = mock_boto3_module.client.call_args[1]
        assert call_kwargs["aws_access_key_id"] == "minioadmin"
        assert call_kwargs["aws_secret_access_key"] == "minioadmin"
        assert storage.config == s3_config
    def test_init_raises_if_boto3_missing(self, s3_config) -> None:
        """CloudStorage.__init__ must raise ImportError when boto3 is absent."""
        with patch.dict(sys.modules, {"boto3": None}):  # type: ignore[dict-item]
            with pytest.raises((ImportError, TypeError)):
                # Re-import to trigger the try/except inside __init__
                import importlib
                import src.backup.cloud_storage as m
                importlib.reload(m)
                m.CloudStorage(s3_config)
    def test_upload_file_success(
        self, mock_boto3_module, s3_config, tmp_path: Path
    ) -> None:
        """upload_file must call client.upload_file and return the object key."""
        from src.backup.cloud_storage import CloudStorage
        test_file = tmp_path / "backup.json.gz"
        test_file.write_bytes(b"data")
        storage = CloudStorage(s3_config)
        key = storage.upload_file(test_file, object_key="backups/backup.json.gz")
        assert key == "backups/backup.json.gz"
        storage.client.upload_file.assert_called_once()
    def test_upload_file_default_key(
        self, mock_boto3_module, s3_config, tmp_path: Path
    ) -> None:
        """upload_file without object_key must use the filename as key."""
        from src.backup.cloud_storage import CloudStorage
        test_file = tmp_path / "myfile.gz"
        test_file.write_bytes(b"data")
        storage = CloudStorage(s3_config)
        key = storage.upload_file(test_file)
        assert key == "myfile.gz"
    def test_upload_file_not_found(
        self, mock_boto3_module, s3_config, tmp_path: Path
    ) -> None:
        """upload_file must raise FileNotFoundError for missing files."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        with pytest.raises(FileNotFoundError):
            storage.upload_file(tmp_path / "nonexistent.gz")
    def test_upload_file_propagates_client_error(
        self, mock_boto3_module, s3_config, tmp_path: Path
    ) -> None:
        """upload_file must re-raise exceptions from the boto3 client."""
        from src.backup.cloud_storage import CloudStorage
        test_file = tmp_path / "backup.gz"
        test_file.write_bytes(b"data")
        storage = CloudStorage(s3_config)
        storage.client.upload_file.side_effect = RuntimeError("network error")
        with pytest.raises(RuntimeError, match="network error"):
            storage.upload_file(test_file)
    def test_download_file_success(
        self, mock_boto3_module, s3_config, tmp_path: Path
    ) -> None:
        """download_file must call client.download_file and return local path."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        dest = tmp_path / "downloads" / "backup.gz"
        result = storage.download_file("backups/backup.gz", dest)
        assert result == dest
        storage.client.download_file.assert_called_once()
    def test_download_file_propagates_error(
        self, mock_boto3_module, s3_config, tmp_path: Path
    ) -> None:
        """download_file must re-raise exceptions from the boto3 client."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.download_file.side_effect = RuntimeError("timeout")
        with pytest.raises(RuntimeError, match="timeout"):
            storage.download_file("key", tmp_path / "dest.gz")
    def test_list_files_returns_objects(
        self, mock_boto3_module, s3_config
    ) -> None:
        """list_files must return parsed file metadata from S3 response."""
        from datetime import timezone
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.list_objects_v2.return_value = {
            "Contents": [
                {
                    "Key": "backups/a.gz",
                    "Size": 1024,
                    "LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
                    "ETag": '"abc123"',
                }
            ]
        }
        files = storage.list_files(prefix="backups/")
        assert len(files) == 1
        assert files[0]["key"] == "backups/a.gz"
        assert files[0]["size_bytes"] == 1024
    def test_list_files_empty_bucket(
        self, mock_boto3_module, s3_config
    ) -> None:
        """list_files must return empty list when bucket has no objects."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.list_objects_v2.return_value = {}
        files = storage.list_files()
        assert files == []
    def test_list_files_propagates_error(
        self, mock_boto3_module, s3_config
    ) -> None:
        """list_files must re-raise exceptions from the boto3 client."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.list_objects_v2.side_effect = RuntimeError("auth error")
        with pytest.raises(RuntimeError):
            storage.list_files()
    def test_delete_file_success(
        self, mock_boto3_module, s3_config
    ) -> None:
        """delete_file must call client.delete_object with the correct key."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.delete_file("backups/old.gz")
        storage.client.delete_object.assert_called_once_with(
            Bucket="test-bucket", Key="backups/old.gz"
        )
    def test_delete_file_propagates_error(
        self, mock_boto3_module, s3_config
    ) -> None:
        """delete_file must re-raise exceptions from the boto3 client."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.delete_object.side_effect = RuntimeError("permission denied")
        with pytest.raises(RuntimeError):
            storage.delete_file("backups/old.gz")
    def test_get_storage_stats_success(
        self, mock_boto3_module, s3_config
    ) -> None:
        """get_storage_stats must aggregate file sizes correctly."""
        from datetime import timezone
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.list_objects_v2.return_value = {
            "Contents": [
                {
                    "Key": "a.gz",
                    "Size": 1024 * 1024,
                    "LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
                    "ETag": '"x"',
                },
                {
                    "Key": "b.gz",
                    "Size": 1024 * 1024,
                    "LastModified": datetime(2026, 1, 2, tzinfo=timezone.utc),
                    "ETag": '"y"',
                },
            ]
        }
        stats = storage.get_storage_stats()
        assert stats["total_files"] == 2
        assert stats["total_size_bytes"] == 2 * 1024 * 1024
        assert stats["total_size_mb"] == pytest.approx(2.0)
    def test_get_storage_stats_on_error(
        self, mock_boto3_module, s3_config
    ) -> None:
        """get_storage_stats must return error dict without raising on failure."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.list_objects_v2.side_effect = RuntimeError("no connection")
        stats = storage.get_storage_stats()
        assert "error" in stats
        assert stats["total_files"] == 0
    def test_verify_connection_success(
        self, mock_boto3_module, s3_config
    ) -> None:
        """verify_connection must return True when head_bucket succeeds."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        result = storage.verify_connection()
        assert result is True
    def test_verify_connection_failure(
        self, mock_boto3_module, s3_config
    ) -> None:
        """verify_connection must return False when head_bucket raises."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.head_bucket.side_effect = RuntimeError("no such bucket")
        result = storage.verify_connection()
        assert result is False
    def test_enable_versioning(
        self, mock_boto3_module, s3_config
    ) -> None:
        """enable_versioning must call put_bucket_versioning."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.enable_versioning()
        storage.client.put_bucket_versioning.assert_called_once()
    def test_enable_versioning_propagates_error(
        self, mock_boto3_module, s3_config
    ) -> None:
        """enable_versioning must re-raise exceptions from the boto3 client."""
        from src.backup.cloud_storage import CloudStorage
        storage = CloudStorage(s3_config)
        storage.client.put_bucket_versioning.side_effect = RuntimeError("denied")
        with pytest.raises(RuntimeError):
            storage.enable_versioning()
--- a/tests/test_brain.py
+++ b/tests/test_brain.py
@@ -2,10 +2,6 @@
 from __future__ import annotations
 from unittest.mock import AsyncMock, MagicMock, patch
 import pytest
 from src.brain.gemini_client import GeminiClient
 # ---------------------------------------------------------------------------
@@ -93,21 +89,9 @@ class TestMalformedJsonHandling:
    def test_json_with_missing_fields_returns_hold(self, settings):
        client = GeminiClient(settings)
-        raw = '{"action": "BUY"}'
+        decision = client.parse_response('{"action": "BUY"}')
        decision = client.parse_response(raw)
        assert decision.action == "HOLD"
        assert decision.confidence == 0
        # rationale preserves raw so prompt_override callers (e.g. pre_market_planner)
        # can extract non-TradeDecision JSON from decision.rationale (#245)
        assert decision.rationale == raw
    def test_non_trade_decision_json_preserves_raw_in_rationale(self, settings):
        """Playbook JSON (no action/confidence/rationale) must be preserved for planner."""
        client = GeminiClient(settings)
        playbook_json = '{"market_outlook": "neutral", "stocks": []}'
        decision = client.parse_response(playbook_json)
        assert decision.action == "HOLD"
        assert decision.rationale == playbook_json
    def test_json_with_invalid_action_returns_hold(self, settings):
        client = GeminiClient(settings)
@@ -286,132 +270,3 @@ class TestBatchDecisionParsing:
        assert decisions["AAPL"].action == "HOLD"
        assert decisions["AAPL"].confidence == 0
 # ---------------------------------------------------------------------------
 # Prompt Override (used by pre_market_planner)
 # ---------------------------------------------------------------------------
 class TestPromptOverride:
    """decide() must use prompt_override when present in market_data."""
    @pytest.mark.asyncio
    async def test_prompt_override_is_sent_to_gemini(self, settings):
        """When prompt_override is in market_data, it should be used as the prompt."""
        client = GeminiClient(settings)
        custom_prompt = "You are a playbook generator. Return JSON with scenarios."
        playbook_json = '{"market_outlook": "neutral", "stocks": []}'
        mock_response = MagicMock()
        mock_response.text = playbook_json
        with patch.object(
            client._client.aio.models,
            "generate_content",
            new_callable=AsyncMock,
            return_value=mock_response,
        ) as mock_generate:
            market_data = {
                "stock_code": "PLANNER",
                "current_price": 0,
                "prompt_override": custom_prompt,
            }
            decision = await client.decide(market_data)
            # Verify the custom prompt was sent, not a built prompt
            mock_generate.assert_called_once()
            actual_prompt = mock_generate.call_args[1].get(
                "contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
            )
            assert actual_prompt == custom_prompt
            # Raw response preserved in rationale without parse_response (#247)
            assert decision.rationale == playbook_json
    @pytest.mark.asyncio
    async def test_prompt_override_skips_parse_response(self, settings):
        """prompt_override bypasses parse_response — no Missing fields warning, raw preserved."""
        client = GeminiClient(settings)
        client._enable_optimization = True
        custom_prompt = "Custom playbook prompt"
        playbook_json = '{"market_outlook": "bullish", "stocks": [{"stock_code": "AAPL"}]}'
        mock_response = MagicMock()
        mock_response.text = playbook_json
        with patch.object(
            client._client.aio.models,
            "generate_content",
            new_callable=AsyncMock,
            return_value=mock_response,
        ):
            with patch.object(client, "parse_response") as mock_parse:
                market_data = {
                    "stock_code": "PLANNER",
                    "current_price": 0,
                    "prompt_override": custom_prompt,
                }
                decision = await client.decide(market_data)
                # parse_response must NOT be called for prompt_override
                mock_parse.assert_not_called()
                # Raw playbook JSON preserved in rationale
                assert decision.rationale == playbook_json
    @pytest.mark.asyncio
    async def test_prompt_override_takes_priority_over_optimization(self, settings):
        """prompt_override must win over enable_optimization=True."""
        client = GeminiClient(settings)
        client._enable_optimization = True
        custom_prompt = "Explicit playbook prompt"
        mock_response = MagicMock()
        mock_response.text = '{"market_outlook": "neutral", "stocks": []}'
        with patch.object(
            client._client.aio.models,
            "generate_content",
            new_callable=AsyncMock,
            return_value=mock_response,
        ) as mock_generate:
            market_data = {
                "stock_code": "PLANNER",
                "current_price": 0,
                "prompt_override": custom_prompt,
            }
            await client.decide(market_data)
            actual_prompt = mock_generate.call_args[1].get(
                "contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
            )
            # The custom prompt must be used, not the compressed prompt
            assert actual_prompt == custom_prompt
    @pytest.mark.asyncio
    async def test_without_prompt_override_uses_build_prompt(self, settings):
        """Without prompt_override, decide() should use build_prompt as before."""
        client = GeminiClient(settings)
        mock_response = MagicMock()
        mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "ok"}'
        with patch.object(
            client._client.aio.models,
            "generate_content",
            new_callable=AsyncMock,
            return_value=mock_response,
        ) as mock_generate:
            market_data = {
                "stock_code": "005930",
                "current_price": 72000,
            }
            await client.decide(market_data)
            actual_prompt = mock_generate.call_args[1].get(
                "contents", mock_generate.call_args[0][1] if len(mock_generate.call_args[0]) > 1 else None
            )
            # Should contain stock code from build_prompt, not be a custom override
            assert "005930" in actual_prompt
--- a/tests/test_broker.py
+++ b/tests/test_broker.py
@@ -3,7 +3,7 @@
 from __future__ import annotations
 import asyncio
-from unittest.mock import AsyncMock, MagicMock, patch
+from unittest.mock import AsyncMock, patch
 import pytest
@@ -90,12 +90,12 @@ class TestTokenManagement:
        await broker.close()
    @pytest.mark.asyncio
-    async def test_token_refresh_cooldown_waits_then_retries(self, settings):
+    async def test_token_refresh_cooldown_prevents_rapid_retries(self, settings):
-        """Token refresh should wait out cooldown then retry (issue #54)."""
+        """Token refresh should enforce cooldown after failure (issue #54)."""
        broker = KISBroker(settings)
-        broker._refresh_cooldown = 0.1  # Short cooldown for testing
+        broker._refresh_cooldown = 2.0  # Short cooldown for testing
-        # All attempts fail with 403 (EGW00133)
+        # First refresh attempt fails with 403 (EGW00133)
        mock_resp_403 = AsyncMock()
        mock_resp_403.status = 403
        mock_resp_403.text = AsyncMock(
@@ -109,8 +109,8 @@ class TestTokenManagement:
            with pytest.raises(ConnectionError, match="Token refresh failed"):
                await broker._ensure_token()
-            # Second attempt within cooldown should wait then retry (and still get 403)
+            # Second attempt within cooldown should fail with cooldown error
-            with pytest.raises(ConnectionError, match="Token refresh failed"):
+            with pytest.raises(ConnectionError, match="Token refresh on cooldown"):
                await broker._ensure_token()
        await broker.close()
@@ -296,647 +296,3 @@ class TestHashKey:
                mock_acquire.assert_called_once()
        await broker.close()
 # ---------------------------------------------------------------------------
 # fetch_market_rankings — TR_ID, path, params (issue #155)
 # ---------------------------------------------------------------------------
 def _make_ranking_mock(items: list[dict]) -> AsyncMock:
    """Build a mock HTTP response returning ranking items."""
    mock_resp = AsyncMock()
    mock_resp.status = 200
    mock_resp.json = AsyncMock(return_value={"output": items})
    mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
    mock_resp.__aexit__ = AsyncMock(return_value=False)
    return mock_resp
 class TestFetchMarketRankings:
    """Verify correct TR_ID, API path, and params per ranking_type (issue #155)."""
    @pytest.fixture
    def broker(self, settings) -> KISBroker:
        b = KISBroker(settings)
        b._access_token = "tok"
        b._token_expires_at = float("inf")
        b._rate_limiter.acquire = AsyncMock()
        return b
    @pytest.mark.asyncio
    async def test_volume_uses_correct_tr_id_and_path(self, broker: KISBroker) -> None:
        mock_resp = _make_ranking_mock([])
        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
            await broker.fetch_market_rankings(ranking_type="volume")
        call_kwargs = mock_get.call_args
        url = call_kwargs[0][0] if call_kwargs[0] else call_kwargs[1].get("url", "")
        headers = call_kwargs[1].get("headers", {})
        params = call_kwargs[1].get("params", {})
        assert "volume-rank" in url
        assert headers.get("tr_id") == "FHPST01710000"
        assert params.get("FID_COND_SCR_DIV_CODE") == "20171"
        assert params.get("FID_TRGT_EXLS_CLS_CODE") == "0000000000"
    @pytest.mark.asyncio
    async def test_fluctuation_uses_correct_tr_id_and_path(self, broker: KISBroker) -> None:
        mock_resp = _make_ranking_mock([])
        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
            await broker.fetch_market_rankings(ranking_type="fluctuation")
        call_kwargs = mock_get.call_args
        url = call_kwargs[0][0] if call_kwargs[0] else call_kwargs[1].get("url", "")
        headers = call_kwargs[1].get("headers", {})
        params = call_kwargs[1].get("params", {})
        assert "ranking/fluctuation" in url
        assert headers.get("tr_id") == "FHPST01700000"
        assert params.get("fid_cond_scr_div_code") == "20170"
        # 실전 API는 4자리("0000") 거부 — 1자리("0")여야 한다 (#240)
        assert params.get("fid_rank_sort_cls_code") == "0"
    @pytest.mark.asyncio
    async def test_volume_returns_parsed_rows(self, broker: KISBroker) -> None:
        items = [
            {
                "mksc_shrn_iscd": "005930",
                "hts_kor_isnm": "삼성전자",
                "stck_prpr": "75000",
                "acml_vol": "10000000",
                "prdy_ctrt": "2.5",
                "vol_inrt": "150",
            }
        ]
        mock_resp = _make_ranking_mock(items)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp):
            result = await broker.fetch_market_rankings(ranking_type="volume")
        assert len(result) == 1
        assert result[0]["stock_code"] == "005930"
        assert result[0]["price"] == 75000.0
        assert result[0]["change_rate"] == 2.5
    @pytest.mark.asyncio
    async def test_fluctuation_parses_stck_shrn_iscd(self, broker: KISBroker) -> None:
        """실전 API는 mksc_shrn_iscd 대신 stck_shrn_iscd를 반환한다 (#240)."""
        items = [
            {
                "stck_shrn_iscd": "015260",
                "hts_kor_isnm": "에이엔피",
                "stck_prpr": "794",
                "acml_vol": "4896196",
                "prdy_ctrt": "29.74",
                "vol_inrt": "0",
            }
        ]
        mock_resp = _make_ranking_mock(items)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp):
            result = await broker.fetch_market_rankings(ranking_type="fluctuation")
        assert len(result) == 1
        assert result[0]["stock_code"] == "015260"
        assert result[0]["change_rate"] == 29.74
 # ---------------------------------------------------------------------------
 # KRX tick unit / round-down helpers (issue #157)
 # ---------------------------------------------------------------------------
 from src.broker.kis_api import kr_tick_unit, kr_round_down  # noqa: E402
 class TestKrTickUnit:
    """kr_tick_unit and kr_round_down must implement KRX price tick rules."""
    @pytest.mark.parametrize(
        "price, expected_tick",
        [
            (1999, 1),
            (2000, 5),
            (4999, 5),
            (5000, 10),
            (19999, 10),
            (20000, 50),
            (49999, 50),
            (50000, 100),
            (199999, 100),
            (200000, 500),
            (499999, 500),
            (500000, 1000),
            (1000000, 1000),
        ],
    )
    def test_tick_unit_boundaries(self, price: int, expected_tick: int) -> None:
        assert kr_tick_unit(price) == expected_tick
    @pytest.mark.parametrize(
        "price, expected_rounded",
        [
            (188150, 188100),   # 100원 단위, 50원 잔여 → 내림
            (188100, 188100),   # 이미 정렬됨
            (75050, 75000),     # 100원 단위, 50원 잔여 → 내림
            (49950, 49950),     # 50원 단위 정렬됨
            (49960, 49950),     # 50원 단위, 10원 잔여 → 내림
            (1999, 1999),       # 1원 단위 → 그대로
            (5003, 5000),       # 10원 단위, 3원 잔여 → 내림
        ],
    )
    def test_round_down_to_tick(self, price: int, expected_rounded: int) -> None:
        assert kr_round_down(price) == expected_rounded
 # ---------------------------------------------------------------------------
 # get_current_price (issue #157)
 # ---------------------------------------------------------------------------
 class TestGetCurrentPrice:
    """get_current_price must use inquire-price API and return (price, change, foreigner)."""
    @pytest.fixture
    def broker(self, settings) -> KISBroker:
        b = KISBroker(settings)
        b._access_token = "tok"
        b._token_expires_at = float("inf")
        b._rate_limiter.acquire = AsyncMock()
        return b
    @pytest.mark.asyncio
    async def test_returns_correct_fields(self, broker: KISBroker) -> None:
        mock_resp = AsyncMock()
        mock_resp.status = 200
        mock_resp.json = AsyncMock(
            return_value={
                "rt_cd": "0",
                "output": {
                    "stck_prpr": "188600",
                    "prdy_ctrt": "3.97",
                    "frgn_ntby_qty": "12345",
                },
            }
        )
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
            price, change_pct, foreigner = await broker.get_current_price("005930")
        assert price == 188600.0
        assert change_pct == 3.97
        assert foreigner == 12345.0
        call_kwargs = mock_get.call_args
        url = call_kwargs[0][0] if call_kwargs[0] else call_kwargs[1].get("url", "")
        headers = call_kwargs[1].get("headers", {})
        assert "inquire-price" in url
        assert headers.get("tr_id") == "FHKST01010100"
    @pytest.mark.asyncio
    async def test_http_error_raises_connection_error(self, broker: KISBroker) -> None:
        mock_resp = AsyncMock()
        mock_resp.status = 500
        mock_resp.text = AsyncMock(return_value="Internal Server Error")
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp):
            with pytest.raises(ConnectionError, match="get_current_price failed"):
                await broker.get_current_price("005930")
 # ---------------------------------------------------------------------------
 # send_order tick rounding and ORD_DVSN (issue #157)
 # ---------------------------------------------------------------------------
 class TestSendOrderTickRounding:
    """send_order must apply KRX tick rounding and correct ORD_DVSN codes."""
    @pytest.fixture
    def broker(self, settings) -> KISBroker:
        b = KISBroker(settings)
        b._access_token = "tok"
        b._token_expires_at = float("inf")
        b._rate_limiter.acquire = AsyncMock()
        return b
    @pytest.mark.asyncio
    async def test_limit_order_rounds_down_to_tick(self, broker: KISBroker) -> None:
        """Price 188150 (not on 100-won tick) must be rounded to 188100."""
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "BUY", 1, price=188150)
        order_call = mock_post.call_args_list[1]
        body = order_call[1].get("json", {})
        assert body["ORD_UNPR"] == "188100"  # rounded down
        assert body["ORD_DVSN"] == "00"       # 지정가
    @pytest.mark.asyncio
    async def test_limit_order_ord_dvsn_is_00(self, broker: KISBroker) -> None:
        """send_order with price>0 must use ORD_DVSN='00' (지정가)."""
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "BUY", 1, price=50000)
        order_call = mock_post.call_args_list[1]
        body = order_call[1].get("json", {})
        assert body["ORD_DVSN"] == "00"
    @pytest.mark.asyncio
    async def test_market_order_ord_dvsn_is_01(self, broker: KISBroker) -> None:
        """send_order with price=0 must use ORD_DVSN='01' (시장가)."""
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "SELL", 1, price=0)
        order_call = mock_post.call_args_list[1]
        body = order_call[1].get("json", {})
        assert body["ORD_DVSN"] == "01"
 # ---------------------------------------------------------------------------
 # TR_ID live/paper branching (issues #201, #202, #203)
 # ---------------------------------------------------------------------------
 class TestTRIDBranchingDomestic:
    """get_balance and send_order must use correct TR_ID for live vs paper mode."""
    def _make_broker(self, settings, mode: str) -> KISBroker:
        from src.config import Settings
        s = Settings(
            KIS_APP_KEY=settings.KIS_APP_KEY,
            KIS_APP_SECRET=settings.KIS_APP_SECRET,
            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
            GEMINI_API_KEY=settings.GEMINI_API_KEY,
            DB_PATH=":memory:",
            ENABLED_MARKETS="KR",
            MODE=mode,
        )
        b = KISBroker(s)
        b._access_token = "tok"
        b._token_expires_at = float("inf")
        b._rate_limiter.acquire = AsyncMock()
        return b
    @pytest.mark.asyncio
    async def test_get_balance_paper_uses_vttc8434r(self, settings) -> None:
        broker = self._make_broker(settings, "paper")
        mock_resp = AsyncMock()
        mock_resp.status = 200
        mock_resp.json = AsyncMock(
            return_value={"output1": [], "output2": {}}
        )
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
            await broker.get_balance()
        headers = mock_get.call_args[1].get("headers", {})
        assert headers["tr_id"] == "VTTC8434R"
    @pytest.mark.asyncio
    async def test_get_balance_live_uses_tttc8434r(self, settings) -> None:
        broker = self._make_broker(settings, "live")
        mock_resp = AsyncMock()
        mock_resp.status = 200
        mock_resp.json = AsyncMock(
            return_value={"output1": [], "output2": {}}
        )
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
            await broker.get_balance()
        headers = mock_get.call_args[1].get("headers", {})
        assert headers["tr_id"] == "TTTC8434R"
    @pytest.mark.asyncio
    async def test_send_order_buy_paper_uses_vttc0012u(self, settings) -> None:
        broker = self._make_broker(settings, "paper")
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "BUY", 1)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert order_headers["tr_id"] == "VTTC0012U"
    @pytest.mark.asyncio
    async def test_send_order_buy_live_uses_tttc0012u(self, settings) -> None:
        broker = self._make_broker(settings, "live")
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "BUY", 1)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert order_headers["tr_id"] == "TTTC0012U"
    @pytest.mark.asyncio
    async def test_send_order_sell_paper_uses_vttc0011u(self, settings) -> None:
        broker = self._make_broker(settings, "paper")
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "SELL", 1)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert order_headers["tr_id"] == "VTTC0011U"
    @pytest.mark.asyncio
    async def test_send_order_sell_live_uses_tttc0011u(self, settings) -> None:
        broker = self._make_broker(settings, "live")
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.send_order("005930", "SELL", 1)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert order_headers["tr_id"] == "TTTC0011U"
 # ---------------------------------------------------------------------------
 # Domestic Pending Orders (get_domestic_pending_orders)
 # ---------------------------------------------------------------------------
 class TestGetDomesticPendingOrders:
    """get_domestic_pending_orders must return [] in paper mode and call TTTC0084R in live."""
    def _make_broker(self, settings, mode: str) -> KISBroker:
        from src.config import Settings
        s = Settings(
            KIS_APP_KEY=settings.KIS_APP_KEY,
            KIS_APP_SECRET=settings.KIS_APP_SECRET,
            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
            GEMINI_API_KEY=settings.GEMINI_API_KEY,
            DB_PATH=":memory:",
            ENABLED_MARKETS="KR",
            MODE=mode,
        )
        b = KISBroker(s)
        b._access_token = "tok"
        b._token_expires_at = float("inf")
        b._rate_limiter.acquire = AsyncMock()
        return b
    @pytest.mark.asyncio
    async def test_paper_mode_returns_empty(self, settings) -> None:
        """Paper mode must return [] immediately without any API call."""
        broker = self._make_broker(settings, "paper")
        with patch("aiohttp.ClientSession.get") as mock_get:
            result = await broker.get_domestic_pending_orders()
        assert result == []
        mock_get.assert_not_called()
    @pytest.mark.asyncio
    async def test_live_mode_calls_tttc0084r_with_correct_params(
        self, settings
    ) -> None:
        """Live mode must call TTTC0084R with INQR_DVSN_1/2 and paging params."""
        broker = self._make_broker(settings, "live")
        pending = [{"odno": "001", "pdno": "005930", "psbl_qty": "10"}]
        mock_resp = AsyncMock()
        mock_resp.status = 200
        mock_resp.json = AsyncMock(return_value={"output": pending})
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
            result = await broker.get_domestic_pending_orders()
        assert result == pending
        headers = mock_get.call_args[1].get("headers", {})
        assert headers["tr_id"] == "TTTC0084R"
        params = mock_get.call_args[1].get("params", {})
        assert params["INQR_DVSN_1"] == "0"
        assert params["INQR_DVSN_2"] == "0"
    @pytest.mark.asyncio
    async def test_live_mode_connection_error(self, settings) -> None:
        """Network error must raise ConnectionError."""
        import aiohttp as _aiohttp
        broker = self._make_broker(settings, "live")
        with patch(
            "aiohttp.ClientSession.get",
            side_effect=_aiohttp.ClientError("timeout"),
        ):
            with pytest.raises(ConnectionError):
                await broker.get_domestic_pending_orders()
 # ---------------------------------------------------------------------------
 # Domestic Order Cancellation (cancel_domestic_order)
 # ---------------------------------------------------------------------------
 class TestCancelDomesticOrder:
    """cancel_domestic_order must use correct TR_ID and build body correctly."""
    def _make_broker(self, settings, mode: str) -> KISBroker:
        from src.config import Settings
        s = Settings(
            KIS_APP_KEY=settings.KIS_APP_KEY,
            KIS_APP_SECRET=settings.KIS_APP_SECRET,
            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
            GEMINI_API_KEY=settings.GEMINI_API_KEY,
            DB_PATH=":memory:",
            ENABLED_MARKETS="KR",
            MODE=mode,
        )
        b = KISBroker(s)
        b._access_token = "tok"
        b._token_expires_at = float("inf")
        b._rate_limiter.acquire = AsyncMock()
        return b
    def _make_post_mocks(self, order_payload: dict) -> tuple:
        mock_hash = AsyncMock()
        mock_hash.status = 200
        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
        mock_hash.__aexit__ = AsyncMock(return_value=False)
        mock_order = AsyncMock()
        mock_order.status = 200
        mock_order.json = AsyncMock(return_value=order_payload)
        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
        mock_order.__aexit__ = AsyncMock(return_value=False)
        return mock_hash, mock_order
    @pytest.mark.asyncio
    async def test_live_uses_tttc0013u(self, settings) -> None:
        """Live mode must use TR_ID TTTC0013U."""
        broker = self._make_broker(settings, "live")
        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 5)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert order_headers["tr_id"] == "TTTC0013U"
    @pytest.mark.asyncio
    async def test_paper_uses_vttc0013u(self, settings) -> None:
        """Paper mode must use TR_ID VTTC0013U."""
        broker = self._make_broker(settings, "paper")
        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 5)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert order_headers["tr_id"] == "VTTC0013U"
    @pytest.mark.asyncio
    async def test_cancel_sets_rvse_cncl_dvsn_cd_02(self, settings) -> None:
        """Body must have RVSE_CNCL_DVSN_CD='02' (취소) and QTY_ALL_ORD_YN='Y'."""
        broker = self._make_broker(settings, "live")
        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 5)
        body = mock_post.call_args_list[1][1].get("json", {})
        assert body["RVSE_CNCL_DVSN_CD"] == "02"
        assert body["QTY_ALL_ORD_YN"] == "Y"
        assert body["ORD_UNPR"] == "0"
    @pytest.mark.asyncio
    async def test_cancel_sets_krx_fwdg_ord_orgno_in_body(self, settings) -> None:
        """Body must include KRX_FWDG_ORD_ORGNO and ORGN_ODNO from arguments."""
        broker = self._make_broker(settings, "live")
        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.cancel_domestic_order("005930", "ORD123", "BRN456", 3)
        body = mock_post.call_args_list[1][1].get("json", {})
        assert body["KRX_FWDG_ORD_ORGNO"] == "BRN456"
        assert body["ORGN_ODNO"] == "ORD123"
        assert body["ORD_QTY"] == "3"
    @pytest.mark.asyncio
    async def test_cancel_sets_hashkey_header(self, settings) -> None:
        """Request must include hashkey header (same pattern as send_order)."""
        broker = self._make_broker(settings, "live")
        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
        with patch(
            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
        ) as mock_post:
            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 2)
        order_headers = mock_post.call_args_list[1][1].get("headers", {})
        assert "hashkey" in order_headers
        assert order_headers["hashkey"] == "h"
--- a/tests/test_context.py
+++ b/tests/test_context.py
@@ -10,7 +10,6 @@ import pytest
 from src.context.aggregator import ContextAggregator
 from src.context.layer import LAYER_CONFIG, ContextLayer
 from src.context.store import ContextStore
 from src.context.summarizer import ContextSummarizer
 from src.db import init_db, log_trade
@@ -371,259 +370,3 @@ class TestLayerMetadata:
        # L1 aggregates from L2
        assert LAYER_CONFIG[ContextLayer.L1_LEGACY].aggregation_source == ContextLayer.L2_ANNUAL
 # ---------------------------------------------------------------------------
 # ContextSummarizer tests
 # ---------------------------------------------------------------------------
@pytest.fixture
 def summarizer(db_conn: sqlite3.Connection) -> ContextSummarizer:
    """Provide a ContextSummarizer backed by an in-memory store."""
    return ContextSummarizer(ContextStore(db_conn))
 class TestContextSummarizer:
    """Test suite for ContextSummarizer."""
    # ------------------------------------------------------------------
    # summarize_numeric_values
    # ------------------------------------------------------------------
    def test_summarize_empty_values(self, summarizer: ContextSummarizer) -> None:
        """Empty list must return SummaryStats with count=0 and no other fields."""
        stats = summarizer.summarize_numeric_values([])
        assert stats.count == 0
        assert stats.mean is None
        assert stats.min is None
        assert stats.max is None
    def test_summarize_single_value(self, summarizer: ContextSummarizer) -> None:
        """Single-element list must return correct stats with std=0 and trend=flat."""
        stats = summarizer.summarize_numeric_values([42.0])
        assert stats.count == 1
        assert stats.mean == 42.0
        assert stats.std == 0.0
        assert stats.trend == "flat"
    def test_summarize_upward_trend(self, summarizer: ContextSummarizer) -> None:
        """Increasing values must produce trend='up'."""
        values = [1.0, 2.0, 3.0, 10.0, 20.0, 30.0]
        stats = summarizer.summarize_numeric_values(values)
        assert stats.trend == "up"
    def test_summarize_downward_trend(self, summarizer: ContextSummarizer) -> None:
        """Decreasing values must produce trend='down'."""
        values = [30.0, 20.0, 10.0, 3.0, 2.0, 1.0]
        stats = summarizer.summarize_numeric_values(values)
        assert stats.trend == "down"
    def test_summarize_flat_trend(self, summarizer: ContextSummarizer) -> None:
        """Stable values must produce trend='flat'."""
        values = [100.0, 100.1, 99.9, 100.0, 100.2, 99.8]
        stats = summarizer.summarize_numeric_values(values)
        assert stats.trend == "flat"
    # ------------------------------------------------------------------
    # summarize_layer
    # ------------------------------------------------------------------
    def test_summarize_layer_no_data(
        self, summarizer: ContextSummarizer
    ) -> None:
        """summarize_layer with no data must return the 'No data' sentinel."""
        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
        assert result["count"] == 0
        assert "No data" in result["summary"]
    def test_summarize_layer_numeric(
        self, summarizer: ContextSummarizer, db_conn: sqlite3.Connection
    ) -> None:
        """summarize_layer must collect numeric values and produce stats."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "total_pnl", 100.0)
        store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "total_pnl", 200.0)
        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
        assert "total_entries" in result
    def test_summarize_layer_with_dict_values(
        self, summarizer: ContextSummarizer
    ) -> None:
        """summarize_layer must handle dict values by extracting numeric subkeys."""
        store = summarizer.store
        # set_context serialises the value as JSON, so passing a dict works
        store.set_context(
            ContextLayer.L6_DAILY, "2026-02-01", "metrics",
            {"win_rate": 65.0, "label": "good"}
        )
        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
        assert "total_entries" in result
        # numeric subkey "win_rate" should appear as "metrics.win_rate"
        assert "metrics.win_rate" in result
    def test_summarize_layer_with_string_values(
        self, summarizer: ContextSummarizer
    ) -> None:
        """summarize_layer must count string values separately."""
        store = summarizer.store
        # set_context stores string values as JSON-encoded strings
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "outlook", "BULLISH")
        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
        # String fields contribute a `<key>_count` entry
        assert "outlook_count" in result
    # ------------------------------------------------------------------
    # rolling_window_summary
    # ------------------------------------------------------------------
    def test_rolling_window_summary_basic(
        self, summarizer: ContextSummarizer
    ) -> None:
        """rolling_window_summary must return the expected structure."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 500.0)
        result = summarizer.rolling_window_summary(ContextLayer.L6_DAILY)
        assert "window_days" in result
        assert "recent_data" in result
        assert "historical_summary" in result
    def test_rolling_window_summary_no_older_data(
        self, summarizer: ContextSummarizer
    ) -> None:
        """rolling_window_summary with summarize_older=False skips history."""
        result = summarizer.rolling_window_summary(
            ContextLayer.L6_DAILY, summarize_older=False
        )
        assert result["historical_summary"] == {}
    # ------------------------------------------------------------------
    # aggregate_to_higher_layer
    # ------------------------------------------------------------------
    def test_aggregate_to_higher_layer_mean(
        self, summarizer: ContextSummarizer
    ) -> None:
        """aggregate_to_higher_layer with 'mean' via dict subkeys returns average."""
        store = summarizer.store
        # Use different outer keys but same inner metric key so get_all_contexts
        # returns multiple rows with the target subkey.
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
        result = summarizer.aggregate_to_higher_layer(
            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "mean"
        )
        assert result == pytest.approx(150.0)
    def test_aggregate_to_higher_layer_sum(
        self, summarizer: ContextSummarizer
    ) -> None:
        """aggregate_to_higher_layer with 'sum' must return the total."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
        result = summarizer.aggregate_to_higher_layer(
            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "sum"
        )
        assert result == pytest.approx(300.0)
    def test_aggregate_to_higher_layer_max(
        self, summarizer: ContextSummarizer
    ) -> None:
        """aggregate_to_higher_layer with 'max' must return the maximum."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
        result = summarizer.aggregate_to_higher_layer(
            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "max"
        )
        assert result == pytest.approx(200.0)
    def test_aggregate_to_higher_layer_min(
        self, summarizer: ContextSummarizer
    ) -> None:
        """aggregate_to_higher_layer with 'min' must return the minimum."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
        result = summarizer.aggregate_to_higher_layer(
            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "min"
        )
        assert result == pytest.approx(100.0)
    def test_aggregate_to_higher_layer_no_data(
        self, summarizer: ContextSummarizer
    ) -> None:
        """aggregate_to_higher_layer with no matching key must return None."""
        result = summarizer.aggregate_to_higher_layer(
            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "nonexistent", "mean"
        )
        assert result is None
    def test_aggregate_to_higher_layer_unknown_func_defaults_to_mean(
        self, summarizer: ContextSummarizer
    ) -> None:
        """Unknown aggregation function must fall back to mean."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
        result = summarizer.aggregate_to_higher_layer(
            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "unknown_func"
        )
        assert result == pytest.approx(150.0)
    # ------------------------------------------------------------------
    # create_compact_summary + format_summary_for_prompt
    # ------------------------------------------------------------------
    def test_create_compact_summary(
        self, summarizer: ContextSummarizer
    ) -> None:
        """create_compact_summary must produce a dict keyed by layer value."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
        result = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
        assert ContextLayer.L6_DAILY.value in result
    def test_format_summary_for_prompt_with_numeric_metrics(
        self, summarizer: ContextSummarizer
    ) -> None:
        """format_summary_for_prompt must render avg/trend fields."""
        store = summarizer.store
        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
        store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "pnl", 200.0)
        compact = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
        text = summarizer.format_summary_for_prompt(compact)
        assert isinstance(text, str)
    def test_format_summary_for_prompt_skips_empty_layers(
        self, summarizer: ContextSummarizer
    ) -> None:
        """format_summary_for_prompt must skip layers with no metrics."""
        summary = {ContextLayer.L6_DAILY.value: {}}
        text = summarizer.format_summary_for_prompt(summary)
        assert text == ""
    def test_format_summary_non_dict_value(
        self, summarizer: ContextSummarizer
    ) -> None:
        """format_summary_for_prompt must render non-dict values as plain text."""
        summary = {
            "daily": {
                "plain_count": 42,
            }
        }
        text = summarizer.format_summary_for_prompt(summary)
        assert "plain_count" in text
        assert "42" in text
--- a/tests/test_dashboard.py
+++ b/tests/test_dashboard.py
@@ -296,156 +296,3 @@ def test_scenarios_active_empty_when_no_matches(tmp_path: Path) -> None:
    get_active_scenarios = _endpoint(app, "/api/scenarios/active")
    body = get_active_scenarios(market="US", date_str="2026-02-14", limit=50)
    assert body["count"] == 0
 def test_pnl_history_all_markets(tmp_path: Path) -> None:
    app = _app(tmp_path)
    get_pnl_history = _endpoint(app, "/api/pnl/history")
    body = get_pnl_history(days=30, market="all")
    assert body["market"] == "all"
    assert isinstance(body["labels"], list)
    assert isinstance(body["pnl"], list)
    assert len(body["labels"]) == len(body["pnl"])
 def test_pnl_history_market_filter(tmp_path: Path) -> None:
    app = _app(tmp_path)
    get_pnl_history = _endpoint(app, "/api/pnl/history")
    body = get_pnl_history(days=30, market="KR")
    assert body["market"] == "KR"
    # KR has 1 trade with pnl=2.0
    assert len(body["labels"]) >= 1
    assert body["pnl"][0] == 2.0
 def test_positions_returns_open_buy(tmp_path: Path) -> None:
    """BUY가 마지막 거래인 종목은 포지션으로 반환되어야 한다."""
    app = _app(tmp_path)
    get_positions = _endpoint(app, "/api/positions")
    body = get_positions()
    # seed_db: 005930은 BUY (오픈), AAPL은 SELL (마지막)
    assert body["count"] == 1
    pos = body["positions"][0]
    assert pos["stock_code"] == "005930"
    assert pos["market"] == "KR"
    assert pos["quantity"] == 1
    assert pos["entry_price"] == 70000
 def test_positions_excludes_closed_sell(tmp_path: Path) -> None:
    """마지막 거래가 SELL인 종목은 포지션에 나타나지 않아야 한다."""
    app = _app(tmp_path)
    get_positions = _endpoint(app, "/api/positions")
    body = get_positions()
    codes = [p["stock_code"] for p in body["positions"]]
    assert "AAPL" not in codes
 def test_positions_empty_when_no_trades(tmp_path: Path) -> None:
    """거래 내역이 없으면 빈 포지션 목록을 반환해야 한다."""
    db_path = tmp_path / "empty.db"
    conn = init_db(str(db_path))
    conn.close()
    app = create_dashboard_app(str(db_path))
    get_positions = _endpoint(app, "/api/positions")
    body = get_positions()
    assert body["count"] == 0
    assert body["positions"] == []
 def _seed_cb_context(conn: sqlite3.Connection, pnl_pct: float, market: str = "KR") -> None:
    import json as _json
    conn.execute(
        "INSERT OR REPLACE INTO system_metrics (key, value, updated_at) VALUES (?, ?, ?)",
        (
            f"portfolio_pnl_pct_{market}",
            _json.dumps({"pnl_pct": pnl_pct}),
            "2026-02-22T10:00:00+00:00",
        ),
    )
    conn.commit()
 def test_status_circuit_breaker_ok(tmp_path: Path) -> None:
    """pnl_pct가 -2.0%보다 높으면 status=ok를 반환해야 한다."""
    db_path = tmp_path / "cb_ok.db"
    conn = init_db(str(db_path))
    _seed_cb_context(conn, -1.0)
    conn.close()
    app = create_dashboard_app(str(db_path))
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    cb = body["circuit_breaker"]
    assert cb["status"] == "ok"
    assert cb["current_pnl_pct"] == -1.0
    assert cb["threshold_pct"] == -3.0
 def test_status_circuit_breaker_warning(tmp_path: Path) -> None:
    """pnl_pct가 -2.0% 이하이면 status=warning을 반환해야 한다."""
    db_path = tmp_path / "cb_warn.db"
    conn = init_db(str(db_path))
    _seed_cb_context(conn, -2.5)
    conn.close()
    app = create_dashboard_app(str(db_path))
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    assert body["circuit_breaker"]["status"] == "warning"
 def test_status_circuit_breaker_tripped(tmp_path: Path) -> None:
    """pnl_pct가 임계값(-3.0%) 이하이면 status=tripped를 반환해야 한다."""
    db_path = tmp_path / "cb_tripped.db"
    conn = init_db(str(db_path))
    _seed_cb_context(conn, -3.5)
    conn.close()
    app = create_dashboard_app(str(db_path))
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    assert body["circuit_breaker"]["status"] == "tripped"
 def test_status_circuit_breaker_unknown_when_no_data(tmp_path: Path) -> None:
    """L7 context에 pnl_pct 데이터가 없으면 status=unknown을 반환해야 한다."""
    app = _app(tmp_path)  # seed_db에는 portfolio_pnl_pct 없음
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    cb = body["circuit_breaker"]
    assert cb["status"] == "unknown"
    assert cb["current_pnl_pct"] is None
 def test_status_mode_paper(tmp_path: Path) -> None:
    """mode=paper로 생성하면 status 응답에 mode=paper가 포함돼야 한다."""
    db_path = tmp_path / "dashboard_test.db"
    conn = init_db(str(db_path))
    _seed_db(conn)
    conn.close()
    app = create_dashboard_app(str(db_path), mode="paper")
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    assert body["mode"] == "paper"
 def test_status_mode_live(tmp_path: Path) -> None:
    """mode=live로 생성하면 status 응답에 mode=live가 포함돼야 한다."""
    db_path = tmp_path / "dashboard_test.db"
    conn = init_db(str(db_path))
    _seed_db(conn)
    conn.close()
    app = create_dashboard_app(str(db_path), mode="live")
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    assert body["mode"] == "live"
 def test_status_mode_default_paper(tmp_path: Path) -> None:
    """mode 파라미터 미전달 시 기본값은 paper여야 한다."""
    db_path = tmp_path / "dashboard_test.db"
    conn = init_db(str(db_path))
    _seed_db(conn)
    conn.close()
    app = create_dashboard_app(str(db_path))
    get_status = _endpoint(app, "/api/status")
    body = get_status()
    assert body["mode"] == "paper"
--- a/tests/test_db.py
+++ b/tests/test_db.py
@@ -1,8 +1,5 @@
 """Tests for database helper functions."""
 import tempfile
 import os
 from src.db import get_open_position, init_db, log_trade
@@ -61,135 +58,3 @@ def test_get_open_position_returns_none_when_latest_is_sell() -> None:
 def test_get_open_position_returns_none_when_no_trades() -> None:
    conn = init_db(":memory:")
    assert get_open_position(conn, "AAPL", "US_NASDAQ") is None
 # ---------------------------------------------------------------------------
 # WAL mode tests (issue #210)
 # ---------------------------------------------------------------------------
 def test_wal_mode_applied_to_file_db() -> None:
    """File-based DB must use WAL journal mode for dashboard concurrent reads."""
    with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
        db_path = f.name
    try:
        conn = init_db(db_path)
        cursor = conn.execute("PRAGMA journal_mode")
        mode = cursor.fetchone()[0]
        assert mode == "wal", f"Expected WAL mode, got {mode}"
        conn.close()
    finally:
        os.unlink(db_path)
        # Clean up WAL auxiliary files if they exist
        for ext in ("-wal", "-shm"):
            path = db_path + ext
            if os.path.exists(path):
                os.unlink(path)
 def test_wal_mode_not_applied_to_memory_db() -> None:
    """:memory: DB must not apply WAL (SQLite does not support WAL for in-memory)."""
    conn = init_db(":memory:")
    cursor = conn.execute("PRAGMA journal_mode")
    mode = cursor.fetchone()[0]
    # In-memory DBs default to 'memory' journal mode
    assert mode != "wal", "WAL should not be set on in-memory database"
    conn.close()
 # ---------------------------------------------------------------------------
 # mode column tests (issue #212)
 # ---------------------------------------------------------------------------
 def test_log_trade_stores_mode_paper() -> None:
    """log_trade must persist mode='paper' in the trades table."""
    conn = init_db(":memory:")
    log_trade(
        conn=conn,
        stock_code="005930",
        action="BUY",
        confidence=85,
        rationale="test",
        mode="paper",
    )
    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
    assert row is not None
    assert row[0] == "paper"
 def test_log_trade_stores_mode_live() -> None:
    """log_trade must persist mode='live' in the trades table."""
    conn = init_db(":memory:")
    log_trade(
        conn=conn,
        stock_code="005930",
        action="BUY",
        confidence=85,
        rationale="test",
        mode="live",
    )
    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
    assert row is not None
    assert row[0] == "live"
 def test_log_trade_default_mode_is_paper() -> None:
    """log_trade without explicit mode must default to 'paper'."""
    conn = init_db(":memory:")
    log_trade(
        conn=conn,
        stock_code="005930",
        action="HOLD",
        confidence=50,
        rationale="test",
    )
    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
    assert row is not None
    assert row[0] == "paper"
 def test_mode_column_exists_in_schema() -> None:
    """trades table must have a mode column after init_db."""
    conn = init_db(":memory:")
    cursor = conn.execute("PRAGMA table_info(trades)")
    columns = {row[1] for row in cursor.fetchall()}
    assert "mode" in columns
 def test_mode_migration_adds_column_to_existing_db() -> None:
    """init_db must add mode column to existing DBs that lack it (migration)."""
    import sqlite3
    with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
        db_path = f.name
    try:
        # Create DB without mode column (simulate old schema)
        old_conn = sqlite3.connect(db_path)
        old_conn.execute(
            """CREATE TABLE trades (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                timestamp TEXT NOT NULL,
                stock_code TEXT NOT NULL,
                action TEXT NOT NULL,
                confidence INTEGER NOT NULL,
                rationale TEXT,
                quantity INTEGER,
                price REAL,
                pnl REAL DEFAULT 0.0,
                market TEXT DEFAULT 'KR',
                exchange_code TEXT DEFAULT 'KRX',
                decision_id TEXT
            )"""
        )
        old_conn.commit()
        old_conn.close()
        # Run init_db — should add mode column via migration
        conn = init_db(db_path)
        cursor = conn.execute("PRAGMA table_info(trades)")
        columns = {row[1] for row in cursor.fetchall()}
        assert "mode" in columns
        conn.close()
    finally:
        os.unlink(db_path)
--- a/tests/test_logging_config.py
+++ b/tests/test_logging_config.py
@@ -1,117 +0,0 @@
 """Tests for JSON structured logging configuration."""
 from __future__ import annotations
 import json
 import logging
 import sys
 from src.logging_config import JSONFormatter, setup_logging
 class TestJSONFormatter:
    """Test JSONFormatter output."""
    def test_basic_log_record(self) -> None:
        """JSONFormatter must emit valid JSON with required fields."""
        formatter = JSONFormatter()
        record = logging.LogRecord(
            name="test.logger",
            level=logging.INFO,
            pathname="",
            lineno=0,
            msg="Hello %s",
            args=("world",),
            exc_info=None,
        )
        output = formatter.format(record)
        data = json.loads(output)
        assert data["level"] == "INFO"
        assert data["logger"] == "test.logger"
        assert data["message"] == "Hello world"
        assert "timestamp" in data
    def test_includes_exception_info(self) -> None:
        """JSONFormatter must include exception info when present."""
        formatter = JSONFormatter()
        try:
            raise ValueError("test error")
        except ValueError:
            exc_info = sys.exc_info()
        record = logging.LogRecord(
            name="test",
            level=logging.ERROR,
            pathname="",
            lineno=0,
            msg="oops",
            args=(),
            exc_info=exc_info,
        )
        output = formatter.format(record)
        data = json.loads(output)
        assert "exception" in data
        assert "ValueError" in data["exception"]
    def test_extra_trading_fields_included(self) -> None:
        """Extra trading fields attached to the record must appear in JSON."""
        formatter = JSONFormatter()
        record = logging.LogRecord(
            name="test",
            level=logging.INFO,
            pathname="",
            lineno=0,
            msg="trade",
            args=(),
            exc_info=None,
        )
        record.stock_code = "005930"  # type: ignore[attr-defined]
        record.action = "BUY"  # type: ignore[attr-defined]
        record.confidence = 85  # type: ignore[attr-defined]
        record.pnl_pct = -1.5  # type: ignore[attr-defined]
        record.order_amount = 1_000_000  # type: ignore[attr-defined]
        output = formatter.format(record)
        data = json.loads(output)
        assert data["stock_code"] == "005930"
        assert data["action"] == "BUY"
        assert data["confidence"] == 85
        assert data["pnl_pct"] == -1.5
        assert data["order_amount"] == 1_000_000
    def test_none_extra_fields_excluded(self) -> None:
        """Extra fields that are None must not appear in JSON output."""
        formatter = JSONFormatter()
        record = logging.LogRecord(
            name="test",
            level=logging.INFO,
            pathname="",
            lineno=0,
            msg="no extras",
            args=(),
            exc_info=None,
        )
        output = formatter.format(record)
        data = json.loads(output)
        assert "stock_code" not in data
        assert "action" not in data
        assert "confidence" not in data
 class TestSetupLogging:
    """Test setup_logging function."""
    def test_configures_root_logger(self) -> None:
        """setup_logging must attach a JSON handler to the root logger."""
        setup_logging(level=logging.DEBUG)
        root = logging.getLogger()
        json_handlers = [
            h for h in root.handlers if isinstance(h.formatter, JSONFormatter)
        ]
        assert len(json_handlers) == 1
        assert root.level == logging.DEBUG
    def test_avoids_duplicate_handlers(self) -> None:
        """Calling setup_logging twice must not add duplicate handlers."""
        setup_logging()
        setup_logging()
        root = logging.getLogger()
        assert len(root.handlers) == 1
--- a/tests/test_main.py
+++ b/tests/test_main.py
--- a/tests/test_overseas_broker.py
+++ b/tests/test_overseas_broker.py
--- a/tests/test_pre_market_planner.py
+++ b/tests/test_pre_market_planner.py
@@ -164,23 +164,18 @@ class TestGeneratePlaybook:
        assert pb.market_outlook == MarketOutlook.NEUTRAL
    @pytest.mark.asyncio
-    async def test_gemini_failure_returns_smart_fallback(self) -> None:
+    async def test_gemini_failure_returns_defensive(self) -> None:
        planner = _make_planner()
        planner._gemini.decide = AsyncMock(side_effect=RuntimeError("API timeout"))
        # oversold candidate (signal="oversold", rsi=28.5)
        candidates = [_candidate()]
        pb = await planner.generate_playbook("KR", candidates, today=date(2026, 2, 8))
        assert pb.default_action == ScenarioAction.HOLD
-        # Smart fallback uses NEUTRAL outlook (not NEUTRAL_TO_BEARISH)
+        assert pb.market_outlook == MarketOutlook.NEUTRAL_TO_BEARISH
        assert pb.market_outlook == MarketOutlook.NEUTRAL
        assert pb.stock_count == 1
-        # Oversold candidate → first scenario is BUY, second is SELL stop-loss
+        # Defensive playbook has stop-loss scenarios
-        scenarios = pb.stock_playbooks[0].scenarios
+        assert pb.stock_playbooks[0].scenarios[0].action == ScenarioAction.SELL
        assert scenarios[0].action == ScenarioAction.BUY
        assert scenarios[0].condition.rsi_below == 30
        assert scenarios[1].action == ScenarioAction.SELL
    @pytest.mark.asyncio
    async def test_gemini_failure_empty_when_defensive_disabled(self) -> None:
@@ -662,339 +657,3 @@ class TestDefensivePlaybook:
        assert pb.stock_count == 0
        assert pb.market == "US"
        assert pb.market_outlook == MarketOutlook.NEUTRAL
 # ---------------------------------------------------------------------------
 # Smart fallback playbook
 # ---------------------------------------------------------------------------
 class TestSmartFallbackPlaybook:
    """Tests for _smart_fallback_playbook — rule-based BUY/SELL on Gemini failure."""
    def _make_settings(self) -> Settings:
        return Settings(
            KIS_APP_KEY="test",
            KIS_APP_SECRET="test",
            KIS_ACCOUNT_NO="12345678-01",
            GEMINI_API_KEY="test",
            RSI_OVERSOLD_THRESHOLD=30,
            VOL_MULTIPLIER=2.0,
        )
    def test_momentum_candidate_gets_buy_on_volume(self) -> None:
        candidates = [
            _candidate(code="CHOW", signal="momentum", volume_ratio=13.64, rsi=100.0)
        ]
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_AMEX", candidates, settings
        )
        assert pb.stock_count == 1
        sp = pb.stock_playbooks[0]
        assert sp.stock_code == "CHOW"
        # First scenario: BUY with volume_ratio_above
        buy_sc = sp.scenarios[0]
        assert buy_sc.action == ScenarioAction.BUY
        assert buy_sc.condition.volume_ratio_above == 2.0
        assert buy_sc.condition.rsi_below is None
        assert buy_sc.confidence == 80
        # Second scenario: stop-loss SELL
        sell_sc = sp.scenarios[1]
        assert sell_sc.action == ScenarioAction.SELL
        assert sell_sc.condition.price_change_pct_below == -3.0
    def test_oversold_candidate_gets_buy_on_rsi(self) -> None:
        candidates = [
            _candidate(code="005930", signal="oversold", rsi=22.0, volume_ratio=3.5)
        ]
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "KR", candidates, settings
        )
        sp = pb.stock_playbooks[0]
        buy_sc = sp.scenarios[0]
        assert buy_sc.action == ScenarioAction.BUY
        assert buy_sc.condition.rsi_below == 30
        assert buy_sc.condition.volume_ratio_above is None
    def test_all_candidates_have_stop_loss_sell(self) -> None:
        candidates = [
            _candidate(code="AAA", signal="momentum", volume_ratio=5.0),
            _candidate(code="BBB", signal="oversold", rsi=25.0),
        ]
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_NASDAQ", candidates, settings
        )
        assert pb.stock_count == 2
        for sp in pb.stock_playbooks:
            sell_scenarios = [s for s in sp.scenarios if s.action == ScenarioAction.SELL]
            assert len(sell_scenarios) == 1
            assert sell_scenarios[0].condition.price_change_pct_below == -3.0
            assert sell_scenarios[0].condition.price_change_pct_below == -3.0
    def test_market_outlook_is_neutral(self) -> None:
        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_AMEX", candidates, settings
        )
        assert pb.market_outlook == MarketOutlook.NEUTRAL
    def test_default_action_is_hold(self) -> None:
        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_AMEX", candidates, settings
        )
        assert pb.default_action == ScenarioAction.HOLD
    def test_has_global_reduce_all_rule(self) -> None:
        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_AMEX", candidates, settings
        )
        assert len(pb.global_rules) == 1
        rule = pb.global_rules[0]
        assert rule.action == ScenarioAction.REDUCE_ALL
        assert "portfolio_pnl_pct" in rule.condition
    def test_empty_candidates_returns_empty_playbook(self) -> None:
        settings = self._make_settings()
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_AMEX", [], settings
        )
        assert pb.stock_count == 0
    def test_vol_multiplier_applied_from_settings(self) -> None:
        """VOL_MULTIPLIER=3.0 should set volume_ratio_above=3.0 for momentum."""
        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
        settings = self._make_settings()
        settings = settings.model_copy(update={"VOL_MULTIPLIER": 3.0})
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "US_AMEX", candidates, settings
        )
        buy_sc = pb.stock_playbooks[0].scenarios[0]
        assert buy_sc.condition.volume_ratio_above == 3.0
    def test_rsi_oversold_threshold_applied_from_settings(self) -> None:
        """RSI_OVERSOLD_THRESHOLD=25 should set rsi_below=25 for oversold."""
        candidates = [_candidate(signal="oversold", rsi=22.0)]
        settings = self._make_settings()
        settings = settings.model_copy(update={"RSI_OVERSOLD_THRESHOLD": 25})
        pb = PreMarketPlanner._smart_fallback_playbook(
            date(2026, 2, 17), "KR", candidates, settings
        )
        buy_sc = pb.stock_playbooks[0].scenarios[0]
        assert buy_sc.condition.rsi_below == 25
    @pytest.mark.asyncio
    async def test_generate_playbook_uses_smart_fallback_on_gemini_error(self) -> None:
        """generate_playbook() should use smart fallback (not defensive) on API failure."""
        planner = _make_planner()
        planner._gemini.decide = AsyncMock(side_effect=ConnectionError("429 quota exceeded"))
        # momentum candidate
        candidates = [
            _candidate(code="CHOW", signal="momentum", volume_ratio=13.64, rsi=100.0)
        ]
        pb = await planner.generate_playbook(
            "US_AMEX", candidates, today=date(2026, 2, 18)
        )
        # Should NOT be all-SELL defensive; should have BUY for momentum
        assert pb.stock_count == 1
        buy_scenarios = [
            s for s in pb.stock_playbooks[0].scenarios
            if s.action == ScenarioAction.BUY
        ]
        assert len(buy_scenarios) == 1
        assert buy_scenarios[0].condition.volume_ratio_above == 2.0  # VOL_MULTIPLIER default
 # ---------------------------------------------------------------------------
 # Holdings in prompt (#170)
 # ---------------------------------------------------------------------------
 class TestHoldingsInPrompt:
    """Tests for current_holdings parameter in generate_playbook / _build_prompt."""
    def _make_holdings(self) -> list[dict]:
        return [
            {
                "stock_code": "005930",
                "name": "Samsung",
                "qty": 10,
                "entry_price": 71000.0,
                "unrealized_pnl_pct": 2.3,
                "holding_days": 3,
            }
        ]
    def test_build_prompt_includes_holdings_section(self) -> None:
        """Prompt should contain a Current Holdings section when holdings are given."""
        planner = _make_planner()
        candidates = [_candidate()]
        holdings = self._make_holdings()
        prompt = planner._build_prompt(
            "KR",
            candidates,
            context_data={},
            self_market_scorecard=None,
            cross_market=None,
            current_holdings=holdings,
        )
        assert "## Current Holdings" in prompt
        assert "005930" in prompt
        assert "+2.30%" in prompt
        assert "보유 3일" in prompt
    def test_build_prompt_no_holdings_omits_section(self) -> None:
        """Prompt should NOT contain a Current Holdings section when holdings=None."""
        planner = _make_planner()
        candidates = [_candidate()]
        prompt = planner._build_prompt(
            "KR",
            candidates,
            context_data={},
            self_market_scorecard=None,
            cross_market=None,
            current_holdings=None,
        )
        assert "## Current Holdings" not in prompt
    def test_build_prompt_empty_holdings_omits_section(self) -> None:
        """Empty list should also omit the holdings section."""
        planner = _make_planner()
        candidates = [_candidate()]
        prompt = planner._build_prompt(
            "KR",
            candidates,
            context_data={},
            self_market_scorecard=None,
            cross_market=None,
            current_holdings=[],
        )
        assert "## Current Holdings" not in prompt
    def test_build_prompt_holdings_instruction_included(self) -> None:
        """Prompt should include instruction to generate scenarios for held stocks."""
        planner = _make_planner()
        candidates = [_candidate()]
        holdings = self._make_holdings()
        prompt = planner._build_prompt(
            "KR",
            candidates,
            context_data={},
            self_market_scorecard=None,
            cross_market=None,
            current_holdings=holdings,
        )
        assert "005930" in prompt
        assert "SELL/HOLD" in prompt
    @pytest.mark.asyncio
    async def test_generate_playbook_passes_holdings_to_prompt(self) -> None:
        """generate_playbook should pass current_holdings through to the prompt."""
        planner = _make_planner()
        candidates = [_candidate()]
        holdings = self._make_holdings()
        # Capture the actual prompt sent to Gemini
        captured_prompts: list[str] = []
        original_decide = planner._gemini.decide
        async def capture_and_call(data: dict) -> TradeDecision:
            captured_prompts.append(data.get("prompt_override", ""))
            return await original_decide(data)
        planner._gemini.decide = capture_and_call  # type: ignore[method-assign]
        await planner.generate_playbook(
            "KR", candidates, today=date(2026, 2, 8), current_holdings=holdings
        )
        assert len(captured_prompts) == 1
        assert "## Current Holdings" in captured_prompts[0]
        assert "005930" in captured_prompts[0]
    @pytest.mark.asyncio
    async def test_holdings_stock_allowed_in_parse_response(self) -> None:
        """Holdings stocks not in candidates list should be accepted in the response."""
        holding_code = "000660"  # Not in candidates
        stocks = [
            {
                "stock_code": "005930",  # candidate
                "scenarios": [
                    {
                        "condition": {"rsi_below": 30},
                        "action": "BUY",
                        "confidence": 85,
                        "rationale": "oversold",
                    }
                ],
            },
            {
                "stock_code": holding_code,  # holding only
                "scenarios": [
                    {
                        "condition": {"price_change_pct_below": -2.0},
                        "action": "SELL",
                        "confidence": 90,
                        "rationale": "stop-loss",
                    }
                ],
            },
        ]
        planner = _make_planner(gemini_response=_gemini_response_json(stocks=stocks))
        candidates = [_candidate()]  # only 005930
        holdings = [
            {
                "stock_code": holding_code,
                "name": "SK Hynix",
                "qty": 5,
                "entry_price": 180000.0,
                "unrealized_pnl_pct": -1.5,
                "holding_days": 7,
            }
        ]
        pb = await planner.generate_playbook(
            "KR",
            candidates,
            today=date(2026, 2, 8),
            current_holdings=holdings,
        )
        codes = [sp.stock_code for sp in pb.stock_playbooks]
        assert "005930" in codes
        assert holding_code in codes
--- a/tests/test_scenario_engine.py
+++ b/tests/test_scenario_engine.py
@@ -440,135 +440,3 @@ class TestEvaluate:
        assert result.action == ScenarioAction.BUY
        assert result.match_details["rsi"] == 25.0
        assert isinstance(result.match_details["rsi"], float)
 # ---------------------------------------------------------------------------
 # Position-aware condition tests (#171)
 # ---------------------------------------------------------------------------
 class TestPositionAwareConditions:
    """Tests for unrealized_pnl_pct and holding_days condition fields."""
    def test_evaluate_condition_unrealized_pnl_above_matches(
        self, engine: ScenarioEngine
    ) -> None:
        """unrealized_pnl_pct_above should match when P&L exceeds threshold."""
        condition = StockCondition(unrealized_pnl_pct_above=3.0)
        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": 5.0}) is True
    def test_evaluate_condition_unrealized_pnl_above_no_match(
        self, engine: ScenarioEngine
    ) -> None:
        """unrealized_pnl_pct_above should NOT match when P&L is below threshold."""
        condition = StockCondition(unrealized_pnl_pct_above=3.0)
        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": 2.0}) is False
    def test_evaluate_condition_unrealized_pnl_below_matches(
        self, engine: ScenarioEngine
    ) -> None:
        """unrealized_pnl_pct_below should match when P&L is under threshold."""
        condition = StockCondition(unrealized_pnl_pct_below=-2.0)
        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": -3.5}) is True
    def test_evaluate_condition_unrealized_pnl_below_no_match(
        self, engine: ScenarioEngine
    ) -> None:
        """unrealized_pnl_pct_below should NOT match when P&L is above threshold."""
        condition = StockCondition(unrealized_pnl_pct_below=-2.0)
        assert engine.evaluate_condition(condition, {"unrealized_pnl_pct": -1.0}) is False
    def test_evaluate_condition_holding_days_above_matches(
        self, engine: ScenarioEngine
    ) -> None:
        """holding_days_above should match when position held longer than threshold."""
        condition = StockCondition(holding_days_above=5)
        assert engine.evaluate_condition(condition, {"holding_days": 7}) is True
    def test_evaluate_condition_holding_days_above_no_match(
        self, engine: ScenarioEngine
    ) -> None:
        """holding_days_above should NOT match when position held shorter."""
        condition = StockCondition(holding_days_above=5)
        assert engine.evaluate_condition(condition, {"holding_days": 3}) is False
    def test_evaluate_condition_holding_days_below_matches(
        self, engine: ScenarioEngine
    ) -> None:
        """holding_days_below should match when position held fewer days."""
        condition = StockCondition(holding_days_below=3)
        assert engine.evaluate_condition(condition, {"holding_days": 1}) is True
    def test_evaluate_condition_holding_days_below_no_match(
        self, engine: ScenarioEngine
    ) -> None:
        """holding_days_below should NOT match when held more days."""
        condition = StockCondition(holding_days_below=3)
        assert engine.evaluate_condition(condition, {"holding_days": 5}) is False
    def test_combined_pnl_and_holding_days(self, engine: ScenarioEngine) -> None:
        """Combined position-aware conditions should AND-evaluate correctly."""
        condition = StockCondition(
            unrealized_pnl_pct_above=3.0,
            holding_days_above=5,
        )
        # Both met → match
        assert engine.evaluate_condition(
            condition,
            {"unrealized_pnl_pct": 4.5, "holding_days": 7},
        ) is True
        # Only pnl met → no match
        assert engine.evaluate_condition(
            condition,
            {"unrealized_pnl_pct": 4.5, "holding_days": 3},
        ) is False
    def test_missing_unrealized_pnl_does_not_match(
        self, engine: ScenarioEngine
    ) -> None:
        """Missing unrealized_pnl_pct key should not match the condition."""
        condition = StockCondition(unrealized_pnl_pct_above=3.0)
        assert engine.evaluate_condition(condition, {}) is False
    def test_missing_holding_days_does_not_match(
        self, engine: ScenarioEngine
    ) -> None:
        """Missing holding_days key should not match the condition."""
        condition = StockCondition(holding_days_above=5)
        assert engine.evaluate_condition(condition, {}) is False
    def test_match_details_includes_position_fields(
        self, engine: ScenarioEngine
    ) -> None:
        """match_details should include position fields when condition specifies them."""
        pb = _playbook(
            scenarios=[
                StockScenario(
                    condition=StockCondition(unrealized_pnl_pct_above=3.0),
                    action=ScenarioAction.SELL,
                    confidence=90,
                    rationale="Take profit",
                )
            ]
        )
        result = engine.evaluate(
            pb,
            "005930",
            {"unrealized_pnl_pct": 5.0},
            {},
        )
        assert result.action == ScenarioAction.SELL
        assert "unrealized_pnl_pct" in result.match_details
        assert result.match_details["unrealized_pnl_pct"] == 5.0
    def test_position_conditions_parse_from_planner(self) -> None:
        """StockCondition should accept and store new fields from JSON parsing."""
        condition = StockCondition(
            unrealized_pnl_pct_above=3.0,
            unrealized_pnl_pct_below=None,
            holding_days_above=5,
            holding_days_below=None,
        )
        assert condition.unrealized_pnl_pct_above == 3.0
        assert condition.holding_days_above == 5
        assert condition.has_any_condition() is True
--- a/tests/test_smart_scanner.py
+++ b/tests/test_smart_scanner.py
@@ -350,42 +350,6 @@ class TestSmartVolatilityScanner:
        assert [c.stock_code for c in candidates] == ["ABCD"]
 class TestImpliedRSIFormula:
    """Test the implied_rsi formula in SmartVolatilityScanner (issue #181)."""
    def test_neutral_change_gives_neutral_rsi(self) -> None:
        """0% change → implied_rsi = 50 (neutral)."""
        # formula: 50 + (change_rate * 2.0)
        rsi = max(0.0, min(100.0, 50.0 + (0.0 * 2.0)))
        assert rsi == 50.0
    def test_10pct_change_gives_rsi_70(self) -> None:
        """10% upward change → implied_rsi = 70 (momentum signal)."""
        rsi = max(0.0, min(100.0, 50.0 + (10.0 * 2.0)))
        assert rsi == 70.0
    def test_minus_10pct_gives_rsi_30(self) -> None:
        """-10% change → implied_rsi = 30 (oversold signal)."""
        rsi = max(0.0, min(100.0, 50.0 + (-10.0 * 2.0)))
        assert rsi == 30.0
    def test_saturation_at_25pct(self) -> None:
        """Saturation occurs at >=25% change (not 12.5% as with old coefficient 4.0)."""
        rsi_12pct = max(0.0, min(100.0, 50.0 + (12.5 * 2.0)))
        rsi_25pct = max(0.0, min(100.0, 50.0 + (25.0 * 2.0)))
        rsi_30pct = max(0.0, min(100.0, 50.0 + (30.0 * 2.0)))
        # At 12.5% change: RSI = 75 (not 100, unlike old formula)
        assert rsi_12pct == 75.0
        # At 25%+ saturation
        assert rsi_25pct == 100.0
        assert rsi_30pct == 100.0  # Capped
    def test_negative_saturation(self) -> None:
        """Saturation at -25% gives RSI = 0."""
        rsi = max(0.0, min(100.0, 50.0 + (-25.0 * 2.0)))
        assert rsi == 0.0
 class TestRSICalculation:
    """Test RSI calculation in VolatilityAnalyzer."""
--- a/tests/test_strategies_base.py
+++ b/tests/test_strategies_base.py
@@ -1,32 +0,0 @@
 """Tests for BaseStrategy abstract class."""
 from __future__ import annotations
 from typing import Any
 import pytest
 from src.strategies.base import BaseStrategy
 class ConcreteStrategy(BaseStrategy):
    """Minimal concrete strategy for testing."""
    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
        return {"action": "HOLD", "confidence": 50, "rationale": "test"}
 def test_base_strategy_cannot_be_instantiated() -> None:
    """BaseStrategy cannot be instantiated directly (it's abstract)."""
    with pytest.raises(TypeError):
        BaseStrategy()  # type: ignore[abstract]
 def test_concrete_strategy_evaluate_returns_decision() -> None:
    """Concrete subclass must implement evaluate and return a dict."""
    strategy = ConcreteStrategy()
    result = strategy.evaluate({"close": [100.0, 101.0]})
    assert isinstance(result, dict)
    assert result["action"] == "HOLD"
    assert result["confidence"] == 50
    assert "rationale" in result
--- a/tests/test_telegram.py
+++ b/tests/test_telegram.py
@@ -5,7 +5,7 @@ from unittest.mock import AsyncMock, patch
 import aiohttp
 import pytest
-from src.notifications.telegram_client import NotificationFilter, NotificationPriority, TelegramClient
+from src.notifications.telegram_client import NotificationPriority, TelegramClient
 class TestTelegramClientInit:
@@ -481,187 +481,3 @@ class TestClientCleanup:
        # Should not raise exception
        await client.close()
 class TestNotificationFilter:
    """Test granular notification filter behavior."""
    def test_default_filter_allows_all(self) -> None:
        """Default NotificationFilter has all flags enabled."""
        f = NotificationFilter()
        assert f.trades is True
        assert f.market_open_close is True
        assert f.fat_finger is True
        assert f.system_events is True
        assert f.playbook is True
        assert f.scenario_match is True
        assert f.errors is True
    def test_client_uses_default_filter_when_none_given(self) -> None:
        """TelegramClient creates a default NotificationFilter when none provided."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        assert isinstance(client._filter, NotificationFilter)
        assert client._filter.scenario_match is True
    def test_client_stores_provided_filter(self) -> None:
        """TelegramClient stores a custom NotificationFilter."""
        nf = NotificationFilter(scenario_match=False, trades=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        assert client._filter.scenario_match is False
        assert client._filter.trades is False
        assert client._filter.market_open_close is True  # default still True
    @pytest.mark.asyncio
    async def test_scenario_match_filtered_does_not_send(self) -> None:
        """notify_scenario_matched skips send when scenario_match=False."""
        nf = NotificationFilter(scenario_match=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        with patch("aiohttp.ClientSession.post") as mock_post:
            await client.notify_scenario_matched(
                stock_code="005930", action="BUY", condition_summary="rsi<30", confidence=85.0
            )
            mock_post.assert_not_called()
    @pytest.mark.asyncio
    async def test_trades_filtered_does_not_send(self) -> None:
        """notify_trade_execution skips send when trades=False."""
        nf = NotificationFilter(trades=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        with patch("aiohttp.ClientSession.post") as mock_post:
            await client.notify_trade_execution(
                stock_code="005930", market="KR", action="BUY",
                quantity=10, price=70000.0, confidence=85.0
            )
            mock_post.assert_not_called()
    @pytest.mark.asyncio
    async def test_market_open_close_filtered_does_not_send(self) -> None:
        """notify_market_open/close skip send when market_open_close=False."""
        nf = NotificationFilter(market_open_close=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        with patch("aiohttp.ClientSession.post") as mock_post:
            await client.notify_market_open("Korea")
            await client.notify_market_close("Korea", pnl_pct=1.5)
            mock_post.assert_not_called()
    @pytest.mark.asyncio
    async def test_circuit_breaker_always_sends_regardless_of_filter(self) -> None:
        """notify_circuit_breaker always sends (no filter flag)."""
        nf = NotificationFilter(
            trades=False, market_open_close=False, fat_finger=False,
            system_events=False, playbook=False, scenario_match=False, errors=False,
        )
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        mock_resp = AsyncMock()
        mock_resp.status = 200
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
            await client.notify_circuit_breaker(pnl_pct=-3.5, threshold=-3.0)
            assert mock_post.call_count == 1
    @pytest.mark.asyncio
    async def test_errors_filtered_does_not_send(self) -> None:
        """notify_error skips send when errors=False."""
        nf = NotificationFilter(errors=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        with patch("aiohttp.ClientSession.post") as mock_post:
            await client.notify_error("TestError", "something went wrong", "KR")
            mock_post.assert_not_called()
    @pytest.mark.asyncio
    async def test_playbook_filtered_does_not_send(self) -> None:
        """notify_playbook_generated/failed skip send when playbook=False."""
        nf = NotificationFilter(playbook=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        with patch("aiohttp.ClientSession.post") as mock_post:
            await client.notify_playbook_generated("KR", 3, 10, 1200)
            await client.notify_playbook_failed("KR", "timeout")
            mock_post.assert_not_called()
    @pytest.mark.asyncio
    async def test_system_events_filtered_does_not_send(self) -> None:
        """notify_system_start/shutdown skip send when system_events=False."""
        nf = NotificationFilter(system_events=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        with patch("aiohttp.ClientSession.post") as mock_post:
            await client.notify_system_start("paper", ["KR"])
            await client.notify_system_shutdown("Normal shutdown")
            mock_post.assert_not_called()
    def test_set_flag_valid_key(self) -> None:
        """set_flag returns True and updates field for a known key."""
        nf = NotificationFilter()
        assert nf.set_flag("scenario", False) is True
        assert nf.scenario_match is False
    def test_set_flag_invalid_key(self) -> None:
        """set_flag returns False for an unknown key."""
        nf = NotificationFilter()
        assert nf.set_flag("unknown_key", False) is False
    def test_as_dict_keys_match_KEYS(self) -> None:
        """as_dict() returns every key defined in KEYS."""
        nf = NotificationFilter()
        d = nf.as_dict()
        assert set(d.keys()) == set(NotificationFilter.KEYS.keys())
    def test_set_notification_valid_key(self) -> None:
        """TelegramClient.set_notification toggles filter at runtime."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        assert client._filter.scenario_match is True
        assert client.set_notification("scenario", False) is True
        assert client._filter.scenario_match is False
    def test_set_notification_all_off(self) -> None:
        """set_notification('all', False) disables every filter flag."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        assert client.set_notification("all", False) is True
        for v in client.filter_status().values():
            assert v is False
    def test_set_notification_all_on(self) -> None:
        """set_notification('all', True) enables every filter flag."""
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True,
            notification_filter=NotificationFilter(
                trades=False, market_open_close=False, scenario_match=False,
                fat_finger=False, system_events=False, playbook=False, errors=False,
            ),
        )
        assert client.set_notification("all", True) is True
        for v in client.filter_status().values():
            assert v is True
    def test_set_notification_unknown_key(self) -> None:
        """set_notification returns False for an unknown key."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        assert client.set_notification("unknown", False) is False
    def test_filter_status_reflects_current_state(self) -> None:
        """filter_status() matches the current NotificationFilter state."""
        nf = NotificationFilter(trades=False, scenario_match=False)
        client = TelegramClient(
            bot_token="123:abc", chat_id="456", enabled=True, notification_filter=nf
        )
        status = client.filter_status()
        assert status["trades"] is False
        assert status["scenario"] is False
        assert status["market"] is True
--- a/tests/test_telegram_commands.py
+++ b/tests/test_telegram_commands.py
@@ -875,139 +875,3 @@ class TestGetUpdates:
            updates = await handler._get_updates()
            assert updates == []
    @pytest.mark.asyncio
    async def test_get_updates_409_stops_polling(self) -> None:
        """409 Conflict response stops the poller (_running = False) and returns empty list."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        handler = TelegramCommandHandler(client)
        handler._running = True  # simulate active poller
        mock_resp = AsyncMock()
        mock_resp.status = 409
        mock_resp.text = AsyncMock(
            return_value='{"ok":false,"error_code":409,"description":"Conflict"}'
        )
        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
        mock_resp.__aexit__ = AsyncMock(return_value=False)
        with patch("aiohttp.ClientSession.post", return_value=mock_resp):
            updates = await handler._get_updates()
        assert updates == []
        assert handler._running is False  # poller stopped
    @pytest.mark.asyncio
    async def test_poll_loop_exits_after_409(self) -> None:
        """_poll_loop exits naturally after _running is set to False by a 409 response."""
        import asyncio as _asyncio
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        handler = TelegramCommandHandler(client)
        call_count = 0
        async def mock_get_updates_409() -> list[dict]:
            nonlocal call_count
            call_count += 1
            # Simulate 409 stopping the poller
            handler._running = False
            return []
        handler._get_updates = mock_get_updates_409  # type: ignore[method-assign]
        handler._running = True
        task = _asyncio.create_task(handler._poll_loop())
        await _asyncio.wait_for(task, timeout=2.0)
        # _get_updates called exactly once, then loop exited
        assert call_count == 1
        assert handler._running is False
 class TestCommandWithArgs:
    """Test register_command_with_args and argument dispatch."""
    def test_register_command_with_args_stored(self) -> None:
        """register_command_with_args stores handler in _commands_with_args."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        handler = TelegramCommandHandler(client)
        async def my_handler(args: list[str]) -> None:
            pass
        handler.register_command_with_args("notify", my_handler)
        assert "notify" in handler._commands_with_args
        assert handler._commands_with_args["notify"] is my_handler
    @pytest.mark.asyncio
    async def test_args_handler_receives_arguments(self) -> None:
        """Args handler is called with the trailing tokens."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        handler = TelegramCommandHandler(client)
        received: list[list[str]] = []
        async def capture(args: list[str]) -> None:
            received.append(args)
        handler.register_command_with_args("notify", capture)
        update = {
            "message": {
                "chat": {"id": "456"},
                "text": "/notify scenario off",
            }
        }
        await handler._handle_update(update)
        assert received == [["scenario", "off"]]
    @pytest.mark.asyncio
    async def test_args_handler_takes_priority_over_no_args_handler(self) -> None:
        """When both handlers exist for same command, args handler wins."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        handler = TelegramCommandHandler(client)
        no_args_called = []
        args_called = []
        async def no_args_handler() -> None:
            no_args_called.append(True)
        async def args_handler(args: list[str]) -> None:
            args_called.append(args)
        handler.register_command("notify", no_args_handler)
        handler.register_command_with_args("notify", args_handler)
        update = {
            "message": {
                "chat": {"id": "456"},
                "text": "/notify all off",
            }
        }
        await handler._handle_update(update)
        assert args_called == [["all", "off"]]
        assert no_args_called == []
    @pytest.mark.asyncio
    async def test_args_handler_with_no_trailing_args(self) -> None:
        """/notify with no args still dispatches to args handler with empty list."""
        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
        handler = TelegramCommandHandler(client)
        received: list[list[str]] = []
        async def capture(args: list[str]) -> None:
            received.append(args)
        handler.register_command_with_args("notify", capture)
        update = {
            "message": {
                "chat": {"id": "456"},
                "text": "/notify",
            }
        }
        await handler._handle_update(update)
        assert received == [[]]
--- a/tests/test_token_efficiency.py
+++ b/tests/test_token_efficiency.py
@@ -124,10 +124,6 @@ class TestPromptOptimizer:
        assert len(prompt) < 300
        assert "005930" in prompt
        assert "75000" in prompt
        # Keys must match parse_response expectations (#242)
        assert '"action"' in prompt
        assert '"confidence"' in prompt
        assert '"rationale"' in prompt
    def test_build_compressed_prompt_no_instructions(self):
        """Test compressed prompt without instructions."""