docs: restore onboarding context and clarify runtime-impact gaps

docs: sync V2 status and process docs for issue #131
2026-02-16 12:29:54 +09:00 · 2026-02-16 11:58:49 +09:00
39 changed files with 852 additions and 6848 deletions
--- a/CLAUDE.md
+++ b/CLAUDE.md
@@ -15,9 +15,6 @@ pytest -v --cov=src

 # Run (paper trading)
 python -m src.main --mode=paper
-
-# Run with dashboard
-python -m src.main --mode=paper --dashboard
 ```

 ## Telegram Notifications (Optional)
@@ -46,10 +43,6 @@ Get real-time alerts for trades, circuit breakers, and system events via Telegra
 - ℹ️ Market open/close notifications
 - 📝 System startup/shutdown status

-### Interactive Commands
-
-With `TELEGRAM_COMMANDS_ENABLED=true` (default), the bot supports 9 bidirectional commands: `/help`, `/status`, `/positions`, `/report`, `/scenarios`, `/review`, `/dashboard`, `/stop`, `/resume`.
-
 **Fail-safe**: Notifications never crash the trading system. Missing credentials or API errors are logged but trading continues normally.

 ## Smart Volatility Scanner (Optional)
@@ -116,23 +109,17 @@ User requirements and feedback are tracked in [docs/requirements-log.md](docs/re
 ```
 src/
 ├── analysis/        # Technical analysis (RSI, volatility, smart scanner)
-├── backup/          # Disaster recovery (scheduler, cloud storage, health)
-├── brain/           # Gemini AI decision engine (prompt optimizer, context selector)
 ├── broker/          # KIS API client (domestic + overseas)
-├── context/         # L1-L7 hierarchical memory system
+├── brain/           # Gemini AI decision engine
 ├── core/            # Risk manager (READ-ONLY)
-├── dashboard/       # FastAPI read-only monitoring (8 API endpoints)
-├── data/            # External data integration (news, market data, calendar)
-├── evolution/       # Self-improvement (optimizer, daily review, scorecard)
-├── logging/         # Decision logger (audit trail)
+├── evolution/       # Self-improvement optimizer
 ├── markets/         # Market schedules and timezone handling
-├── notifications/   # Telegram alerts + bidirectional commands (9 commands)
-├── strategy/        # Pre-market planner, scenario engine, playbook store
+├── notifications/   # Telegram real-time alerts
 ├── db.py            # SQLite trade logging
 ├── main.py          # Trading loop orchestrator
 └── config.py        # Settings (from .env)

-tests/               # 551 tests across 25 files
+tests/               # 343 tests across 14 files
 docs/                # Extended documentation
 ```

@@ -144,7 +131,6 @@ ruff check src/ tests/           # Lint
 mypy src/ --strict               # Type check

 python -m src.main --mode=paper  # Paper trading
-python -m src.main --mode=paper --dashboard  # With dashboard
 python -m src.main --mode=live   # Live trading (⚠️ real money)

 # Gitea workflow (requires tea CLI)
--- a/README.md
+++ b/README.md
@@ -1,234 +1,126 @@
 # The Ouroboros — 자가 진화형 AI 투자 시스템

-KIS(한국투자증권) API로 매매하고, Google Gemini로 판단하며, 자체 전략 코드를 TDD 기반으로 진화시키는 자율 주식 트레이딩 에이전트.
+KIS API 기반 자동매매 + Gemini 기반 장전 전략 생성 + 장중 로컬 시나리오 실행 + 장후 리뷰/진화 루프를 결합한 시스템입니다.

-## 아키텍처
+## 현재 상태 (2026-02-16)

-```
-┌─────────────┐     ┌─────────────┐     ┌─────────────┐
-│  KIS Broker │◄───►│    Main     │◄───►│ Gemini Brain│
-│  (매매 실행) │     │ (거래 루프)  │     │  (의사결정)  │
-└─────────────┘     └──────┬──────┘     └─────────────┘
-                           │
-              ┌────────────┼────────────┐
-              │            │            │
-       ┌──────┴──────┐ ┌──┴───┐ ┌──────┴──────┐
-       │Risk Manager │ │  DB  │ │  Telegram   │
-       │  (안전장치)  │ │      │ │ (알림+명령)  │
-       └──────┬──────┘ └──────┘ └─────────────┘
-              │
-     ┌────────┼────────┐
-     │        │        │
-┌────┴────┐┌──┴──┐┌────┴─────┐
-│Strategy ││Ctx  ││Evolution │
-│(플레이북)││(메모리)││ (진화)   │
-└─────────┘└─────┘└──────────┘
-```
+- V2 계획 기준 완료: **18/20**
+- 부분 완료: **1/20** (`1-7` 일부 항목)
+- 미완료: **1/20** (`4-1` Telegram 확장 명령어)

-**v2 핵심**: "Plan Once, Execute Locally" — 장 시작 전 AI가 시나리오 플레이북을 1회 생성하고, 거래 시간에는 로컬 시나리오 매칭만 수행하여 API 비용과 지연 시간을 대폭 절감.
+핵심 전환은 이미 반영되었습니다.

-## 핵심 모듈
+- 기존: 장중 `brain.decide()` 실시간 의존
+- 현재: 장전 `DayPlaybook` 생성 + 장중 `ScenarioEngine` 로컬 매칭

-| 모듈 | 위치 | 설명 |
-|------|------|------|
-| 설정 | `src/config.py` | Pydantic 기반 환경변수 로딩 및 타입 검증 (35+ 변수) |
-| 브로커 | `src/broker/` | KIS API 비동기 래퍼 (국내 + 해외 9개 시장) |
-| 두뇌 | `src/brain/` | Gemini 프롬프트 구성, JSON 파싱, 토큰 최적화 |
-| 방패 | `src/core/risk_manager.py` | 서킷 브레이커 + 팻 핑거 체크 (READ-ONLY) |
-| 전략 | `src/strategy/` | Pre-Market Planner, Scenario Engine, Playbook Store |
-| 컨텍스트 | `src/context/` | L1-L7 계층형 메모리 시스템 |
-| 분석 | `src/analysis/` | RSI, ATR, Smart Volatility Scanner |
-| 알림 | `src/notifications/` | 텔레그램 양방향 (알림 + 9개 명령어) |
-| 대시보드 | `src/dashboard/` | FastAPI 읽기 전용 모니터링 (8개 API) |
-| 진화 | `src/evolution/` | 전략 진화 + Daily Review + Scorecard |
-| 의사결정 로그 | `src/logging/` | 전체 거래 결정 감사 추적 |
-| 데이터 | `src/data/` | 뉴스, 시장 데이터, 경제 캘린더 연동 |
-| 백업 | `src/backup/` | 자동 백업, S3 클라우드, 무결성 검증 |
-| DB | `src/db.py` | SQLite 거래 로그 (5개 테이블) |
+## 핵심 구성

-## 안전장치
+- `src/main.py`: 시장 루프, 플레이북 생성/적용, EOD 집계, 리뷰/진화 연결
+- `src/strategy/`: `models`, `pre_market_planner`, `scenario_engine`, `playbook_store`
+- `src/context/`: `store`, `aggregator`, `scheduler` (L1~L7)
+- `src/evolution/daily_review.py`: 시장별 scorecard/lessons 생성
+- `src/dashboard/app.py`: FastAPI 관측 API
+- `src/notifications/telegram_client.py`: 알림 및 명령 핸들러

-| 규칙 | 내용 |
-|------|------|
-| 서킷 브레이커 | 일일 손실률 -3.0% 초과 시 전체 매매 중단 (`SystemExit`) |
-| 팻 핑거 방지 | 주문 금액이 보유 현금의 30% 초과 시 주문 거부 |
-| 신뢰도 임계값 | Gemini 신뢰도 80 미만이면 강제 HOLD |
-| 레이트 리미터 | Leaky Bucket 알고리즘으로 API 호출 제한 |
-| 토큰 자동 갱신 | 만료 1분 전 자동으로 Access Token 재발급 |
-| 손절 모니터링 | 플레이북 시나리오 기반 실시간 포지션 보호 |
-
-## 빠른 시작
+## Quick Start

 ### 1. 환경 설정

 ```bash
 cp .env.example .env
-# .env 파일에 KIS API 키와 Gemini API 키 입력
 ```

+필수 값:
+
+- `KIS_APP_KEY`
+- `KIS_APP_SECRET`
+- `KIS_ACCOUNT_NO`
+- `GEMINI_API_KEY`
+
 ### 2. 의존성 설치

 ```bash
-pip install ".[dev]"
+pip install -e ".[dev]"
 ```

-### 3. 테스트 실행
+### 3. 테스트

 ```bash
-pytest -v --cov=src --cov-report=term-missing
+pytest -v --cov=src
+ruff check src/ tests/
+mypy src/ --strict
 ```

-### 4. 실행 (모의투자)
+## 실행
+
+### 기본 실행

 ```bash
-# 기본 실행
 python -m src.main --mode=paper
+```

-# 대시보드 활성화
+### 대시보드 포함 실행
+
+```bash
 python -m src.main --mode=paper --dashboard
 ```

-### 5. Docker 실행
+또는 환경변수:

 ```bash
-docker compose up -d ouroboros
+DASHBOARD_ENABLED=true
+DASHBOARD_HOST=127.0.0.1
+DASHBOARD_PORT=8080
 ```

-## 지원 시장
+## 주요 API/기능

-| 국가 | 거래소 | 코드 |
-|------|--------|------|
-| 🇰🇷 한국 | KRX | KR |
-| 🇺🇸 미국 | NASDAQ, NYSE, AMEX | US_NASDAQ, US_NYSE, US_AMEX |
-| 🇯🇵 일본 | TSE | JP |
-| 🇭🇰 홍콩 | SEHK | HK |
-| 🇨🇳 중국 | 상하이, 선전 | CN_SHA, CN_SZA |
-| 🇻🇳 베트남 | 하노이, 호치민 | VN_HNX, VN_HSX |
+- 플레이북 저장: `playbooks` 테이블 (`date + market` UNIQUE)
+- 의사결정/결과 연결: `trades.decision_id` + `DecisionLogger.update_outcome()`
+- 시장별 scorecard 컨텍스트: `scorecard_KR`, `scorecard_US`
+- 컨텍스트 스케줄러: weekly/monthly/quarterly/annual/legacy + cleanup
+- 대시보드 API:
+- `/api/status`
+- `/api/playbook/{date}?market=KR`
+- `/api/scorecard/{date}?market=KR`
+- `/api/performance?market=all`
+- `/api/context/{layer}`
+- `/api/decisions?market=KR`
+- `/api/scenarios/active?market=US`

-`ENABLED_MARKETS` 환경변수로 활성 시장 선택 (기본: `KR,US`).
+## 현재 갭 (코드 기준)

-## 텔레그램 (선택사항)
-
-거래 실행, 서킷 브레이커 발동, 시스템 상태 등을 텔레그램으로 실시간 알림 받을 수 있습니다.
-
-### 빠른 설정
-
-1. **봇 생성**: 텔레그램에서 [@BotFather](https://t.me/BotFather) 메시지 → `/newbot` 명령
-2. **채팅 ID 확인**: [@userinfobot](https://t.me/userinfobot) 메시지 → `/start` 명령
-3. **환경변수 설정**: `.env` 파일에 추가
-   ```bash
-   TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
-   TELEGRAM_CHAT_ID=123456789
-   TELEGRAM_ENABLED=true
-   ```
-4. **테스트**: 봇과 대화 시작 (`/start` 전송) 후 에이전트 실행
-
-**상세 문서**: [src/notifications/README.md](src/notifications/README.md)
-
-### 알림 종류
-
- 🟢 거래 체결 알림 (BUY/SELL + 신뢰도)
- 🚨 서킷 브레이커 발동 (자동 거래 중단)
- ⚠️ 팻 핑거 차단 (과도한 주문 차단)
- ℹ️ 장 시작/종료 알림
- 📝 시스템 시작/종료 상태
-
-### 양방향 명령어
-
-`TELEGRAM_COMMANDS_ENABLED=true` (기본값) 설정 시 9개 대화형 명령어 지원:
-
-| 명령어 | 설명 |
-|--------|------|
-| `/help` | 사용 가능한 명령어 목록 |
-| `/status` | 거래 상태 (모드, 시장, P&L) |
-| `/positions` | 계좌 요약 (잔고, 현금, P&L) |
-| `/report` | 일일 요약 (거래 수, P&L, 승률) |
-| `/scenarios` | 오늘의 플레이북 시나리오 |
-| `/review` | 최근 스코어카드 (L6_DAILY) |
-| `/dashboard` | 대시보드 URL 표시 |
-| `/stop` | 거래 일시 정지 |
-| `/resume` | 거래 재개 |
-
-**안전장치**: 알림 실패해도 거래는 계속 진행됩니다.
+- `Issue 4-1` 미구현: `/report`, `/scenarios`, `/review`, `/dashboard` Telegram 명령 미등록
+- `Issue 1-7` 일부 미완:
+- `price_change_pct` 정규화 어댑터 명시 구현 없음
+- 영향: `price_change_pct_above/below` 조건을 사용하는 시나리오는 사실상 매칭 불가(dead path)
+- HOLD 시 별도 손절 모니터링 플래그 처리 분리 미흡
+- 시장 코드 정합성 이슈:
+- 설정 기본값은 `ENABLED_MARKETS="KR,US"`
+- 스케줄 정의는 `US_NASDAQ`, `US_NYSE` 중심
+- 영향: `get_open_markets(["KR", "US"])`에서 `US` 미정의로 US 시장이 누락될 수 있음(런타임 영향)

 ## 테스트

-551개 테스트가 25개 파일에 걸쳐 구현되어 있습니다. 최소 커버리지 80%.
+로컬 수집 기준:

-```
-tests/test_scenario_engine.py    — 시나리오 매칭 (44개)
-tests/test_data_integration.py   — 외부 데이터 연동 (38개)
-tests/test_pre_market_planner.py — 플레이북 생성 (37개)
-tests/test_main.py               — 거래 루프 통합 (37개)
-tests/test_token_efficiency.py   — 토큰 최적화 (34개)
-tests/test_strategy_models.py    — 전략 모델 검증 (33개)
-tests/test_telegram_commands.py  — 텔레그램 명령어 (31개)
-tests/test_latency_control.py    — 지연시간 제어 (30개)
-tests/test_telegram.py           — 텔레그램 알림 (25개)
-... 외 16개 파일
+```bash
+pytest --collect-only -q
+# 538 tests collected
 ```

-**상세**: [docs/testing.md](docs/testing.md)
+권장 검증:

-## 기술 스택
-
- **언어**: Python 3.11+ (asyncio 기반)
- **브로커**: KIS Open API (REST, 국내+해외)
- **AI**: Google Gemini Pro
- **DB**: SQLite (5개 테이블: trades, contexts, decision_logs, playbooks, context_metadata)
- **대시보드**: FastAPI + uvicorn
- **검증**: pytest + coverage (551 tests)
- **CI/CD**: GitHub Actions
- **배포**: Docker + Docker Compose
-
-## 프로젝트 구조
-
-```
-The-Ouroboros/
-├── docs/
-│   ├── architecture.md          # 시스템 아키텍처
-│   ├── testing.md               # 테스트 가이드
-│   ├── commands.md              # 명령어 레퍼런스
-│   ├── context-tree.md          # L1-L7 메모리 시스템
-│   ├── workflow.md              # Git 워크플로우
-│   ├── agents.md                # 에이전트 정책
-│   ├── skills.md                # 도구 목록
-│   ├── disaster_recovery.md     # 백업/복구
-│   └── requirements-log.md      # 요구사항 기록
-├── src/
-│   ├── analysis/                # 기술적 분석 (RSI, ATR, Smart Scanner)
-│   ├── backup/                  # 백업 (스케줄러, S3, 무결성 검증)
-│   ├── brain/                   # Gemini 의사결정 (프롬프트 최적화, 컨텍스트 선택)
-│   ├── broker/                  # KIS API (국내 + 해외)
-│   ├── context/                 # L1-L7 계층 메모리
-│   ├── core/                    # 리스크 관리 (READ-ONLY)
-│   ├── dashboard/               # FastAPI 모니터링 대시보드
-│   ├── data/                    # 외부 데이터 연동
-│   ├── evolution/               # 전략 진화 + Daily Review
-│   ├── logging/                 # 의사결정 감사 추적
-│   ├── markets/                 # 시장 스케줄 + 타임존
-│   ├── notifications/           # 텔레그램 알림 + 명령어
-│   ├── strategy/                # 플레이북 (Planner, Scenario Engine)
-│   ├── config.py                # Pydantic 설정
-│   ├── db.py                    # SQLite 데이터베이스
-│   └── main.py                  # 비동기 거래 루프
-├── tests/                       # 551개 테스트 (25개 파일)
-├── Dockerfile                   # 멀티스테이지 빌드
-├── docker-compose.yml           # 서비스 오케스트레이션
-└── pyproject.toml               # 의존성 및 도구 설정
+```bash
+pytest -v --cov=src
+ruff check src/ tests/
+mypy src/ --strict
 ```

 ## 문서

- **[아키텍처](docs/architecture.md)** — 시스템 설계, 컴포넌트, 데이터 흐름
- **[테스트](docs/testing.md)** — 테스트 구조, 커버리지, 작성 가이드
- **[명령어](docs/commands.md)** — CLI, Dashboard, Telegram 명령어
- **[컨텍스트 트리](docs/context-tree.md)** — L1-L7 계층 메모리
- **[워크플로우](docs/workflow.md)** — Git 워크플로우 정책
- **[에이전트 정책](docs/agents.md)** — 안전 제약, 금지 행위
- **[백업/복구](docs/disaster_recovery.md)** — 재해 복구 절차
- **[요구사항](docs/requirements-log.md)** — 사용자 요구사항 추적
-
-## 라이선스
-
-이 프로젝트의 라이선스는 [LICENSE](LICENSE) 파일을 참조하세요.
+- 아키텍처: `docs/architecture.md`
+- 컨텍스트 트리: `docs/context-tree.md`
+- 워크플로우: `docs/workflow.md`
+- 요구사항 로그: `docs/requirements-log.md`
+- 명령 레퍼런스: `docs/commands.md`
--- a/docs/architecture.md
+++ b/docs/architecture.md
@@ -2,642 +2,140 @@

 ## Overview

-Self-evolving AI trading agent for global stock markets via KIS (Korea Investment & Securities) API. The main loop in `src/main.py` orchestrates components across multiple markets with two trading modes: daily (batch API calls) or realtime (per-stock decisions).
+The Ouroboros V2는 `Proactive` 구조를 중심으로 동작합니다.

-**v2 Proactive Playbook Architecture**: The system uses a "plan once, execute locally" approach. Pre-market, the AI generates a playbook of scenarios (one Gemini API call per market per day). During trading hours, a local scenario engine matches live market data against these pre-computed scenarios — no additional AI calls needed. This dramatically reduces API costs and latency.
+- 장전: Gemini 1회 호출로 시장별 `DayPlaybook` 생성
+- 장중: `ScenarioEngine`이 로컬 조건 매칭으로 의사결정
+- 장후: `ContextAggregator` + `DailyReviewer`로 성과 집계/교훈 생성

-## Trading Modes
+`main.py`가 아래 컴포넌트를 오케스트레이션합니다.

-The system supports two trading frequency modes controlled by the `TRADE_MODE` environment variable:
+- `KISBroker` / `OverseasBroker`
+- `PreMarketPlanner` / `ScenarioEngine` / `PlaybookStore`
+- `ContextStore` / `ContextAggregator` / `ContextScheduler`
+- `DailyReviewer` / `EvolutionOptimizer`
+- `TelegramClient` / `TelegramCommandHandler`

-### Daily Mode (default)
+안전/운영 컴포넌트도 핵심입니다.

-Optimized for Gemini Free tier API limits (20 calls/day):
+- `RiskManager`: circuit breaker, fat-finger 검증
+- `PriorityTaskQueue` + `CriticalityAssessor`: 우선순위/지연 제어

- **Batch decisions**: 1 API call per market per session
- **Fixed schedule**: 4 sessions per day at 6-hour intervals (configurable)
- **API efficiency**: Processes all stocks in a market simultaneously
- **Use case**: Free tier users, cost-conscious deployments
- **Configuration**:
-  ```bash
-  TRADE_MODE=daily
-  DAILY_SESSIONS=4        # Sessions per day (1-10)
-  SESSION_INTERVAL_HOURS=6  # Hours between sessions (1-24)
-  ```
+## Market Scope

-**Example**: With 2 markets (US, KR) and 4 sessions/day = 8 API calls/day (within 20 call limit)
+V2 기본 설정은 `ENABLED_MARKETS="KR,US"` 입니다.

-### Realtime Mode
+현재 코드 기준 주의점(런타임 영향):

-High-frequency trading with individual stock analysis:
+- 설정은 `KR,US`를 기본값으로 사용
+- 스케줄 레이어(`src/markets/schedule.py`)는 `US_NASDAQ`, `US_NYSE` 구조를 아직 유지
+- `US` 코드가 스케줄에 직접 정의되지 않아 US 시장 누락 가능성이 있음

- **Per-stock decisions**: 1 API call per stock per cycle
- **60-second interval**: Continuous monitoring
- **Use case**: Production deployments with Gemini paid tier
- **Configuration**:
-  ```bash
-  TRADE_MODE=realtime
-  ```
+## Decision Flow

-**Note**: Realtime mode requires Gemini API subscription due to high call volume.
+### 1) Pre-market

-## Core Components
+1. `SmartVolatilityScanner.scan()`으로 후보 종목 수집
+2. `PreMarketPlanner.generate_playbook(market, candidates)` 호출
+3. 결과를 `PlaybookStore.save()`로 DB 저장
+4. 실패 시 empty/defensive playbook 사용

-### 1. Broker (`src/broker/`)
+### 2) In-market

-**KISBroker** (`kis_api.py`) — Async KIS API client for domestic Korean market
+1. 시장 데이터 + 스캐너 메트릭(`rsi`, `volume_ratio`) 구성
+2. `ScenarioEngine.evaluate(playbook, stock_code, market_data, portfolio_data)`
+3. `TradeDecision` 변환 후 주문/로그/알림 처리
+4. `decision_logs`와 `trades`를 `decision_id`로 연결

- Automatic OAuth token refresh (valid for 24 hours)
- Leaky-bucket rate limiter (configurable RPS, default 2.0)
- POST body hash-key signing for order authentication
- Custom SSL context with disabled hostname verification for VTS (virtual trading) endpoint due to known certificate mismatch
- `fetch_market_rankings()` — Fetch volume surge rankings from KIS API
- `get_daily_prices()` — Fetch OHLCV history for technical analysis
+### 3) End-of-day

-**OverseasBroker** (`overseas.py`) — KIS overseas stock API wrapper
+1. `ContextAggregator.aggregate_daily_from_trades(date, market)`
+2. `DailyReviewer.generate_scorecard(date, market)`
+3. `store_scorecard_in_context()`로 `scorecard_{market}` 저장
+4. `generate_lessons()`로 장후 교훈 생성
+5. (US 종료 시) `EvolutionOptimizer.evolve()` 실행

- Reuses KISBroker infrastructure (session, token, rate limiter) via composition
- Supports 9 global markets: US (NASDAQ/NYSE/AMEX), Japan, Hong Kong, China (Shanghai/Shenzhen), Vietnam (Hanoi/HCM)
- Different API endpoints for overseas price/balance/order operations
+## Risk Policy

-**Market Schedule** (`src/markets/schedule.py`) — Timezone-aware market management
+- `RiskManager`는 주문 전 검증을 강제합니다.
+- circuit breaker: 손실 임계치 하회 시 거래 중단
+- fat-finger: 주문 금액 과대 시 주문 차단
+- 실패 시 알림은 보내되, 예외 처리로 루프 안정성 유지

- `MarketInfo` dataclass with timezone, trading hours, lunch breaks
- Automatic DST handling via `zoneinfo.ZoneInfo`
- `is_market_open()` checks weekends, trading hours, lunch breaks
- `get_open_markets()` returns currently active markets
- `get_next_market_open()` finds next market to open and when
- 10 global markets defined (KR, US_NASDAQ, US_NYSE, US_AMEX, JP, HK, CN_SHA, CN_SZA, VN_HNX, VN_HSX)
+## Error Handling Strategy

-**Overseas Ranking API Methods** (added in v0.10.x):
- `fetch_overseas_rankings()` — Fetch overseas ranking universe (fluctuation / volume)
- Ranking endpoint paths and TR_IDs are configurable via environment variables
+- API 호출 실패: 재시도(지수 백오프) 후 종목/사이클 스킵
+- 시나리오/플래너 실패: empty 또는 defensive playbook으로 안전 폴백
+- Telegram 실패: warning 로깅 후 거래 루프 지속
+- 대시보드 스레드 실패: warning 로깅 후 메인 트레이딩 루프와 분리 유지

-### 2. Analysis (`src/analysis/`)
+## Configuration Reference

-**VolatilityAnalyzer** (`volatility.py`) — Technical indicator calculations
+상세 설정은 `src/config.py`를 기준으로 합니다.

- ATR (Average True Range) for volatility measurement
- RSI (Relative Strength Index) using Wilder's smoothing method
- Price change percentages across multiple timeframes
- Volume surge ratios and price-volume divergence
- Momentum scoring (0-100 scale)
- Breakout/breakdown pattern detection
+- 거래 모드: `TRADE_MODE`, `DAILY_SESSIONS`, `SESSION_INTERVAL_HOURS`
+- 전략: `PRE_MARKET_MINUTES`, `MAX_SCENARIOS_PER_STOCK`, `RESCAN_INTERVAL_SECONDS`
+- 시장: `ENABLED_MARKETS`
+- 대시보드: `DASHBOARD_ENABLED`, `DASHBOARD_HOST`, `DASHBOARD_PORT`
+- 알림: `TELEGRAM_*`

-**SmartVolatilityScanner** (`smart_scanner.py`) — Python-first filtering pipeline
+## Context Tree

- **Domestic (KR)**:
-  - **Step 1**: Fetch domestic fluctuation ranking as primary universe
-  - **Step 2**: Fetch domestic volume ranking for liquidity bonus
-  - **Step 3**: Compute volatility-first score (max of daily change% and intraday range%)
-  - **Step 4**: Apply liquidity bonus and return top N candidates
- **Overseas (US/JP/HK/CN/VN)**:
-  - **Step 1**: Fetch overseas ranking universe (fluctuation rank + volume rank bonus)
-  - **Step 2**: Compute volatility-first score (max of daily change% and intraday range%)
-  - **Step 3**: Apply liquidity bonus from volume ranking
-  - **Step 4**: Return top N candidates (default 3)
- **Fallback (overseas only)**: If ranking API is unavailable, uses dynamic universe
-  from runtime active symbols + recent traded symbols + current holdings (no static watchlist)
- **Realtime mode only**: Daily mode uses batch processing for API efficiency
+레이어 전략:

-**Benefits:**
- Reduces Gemini API calls from 20-30 stocks to 1-3 qualified candidates
- Fast Python-based filtering before expensive AI judgment
- Logs selection context (RSI-compatible proxy, volume_ratio, signal, score) for Evolution system
+- `L7~L5`: 시장별 키
+- `L4~L1`: 글로벌 통합 롤업

-### 3. Brain (`src/brain/`)
+구현 포인트:

-**GeminiClient** (`gemini_client.py`) — AI decision engine powered by Google Gemini
+- `L7` 쓰기: `volatility_{market}_{stock}` 등
+- `L6` 집계: `total_pnl_KR`, `trade_count_US` 등
+- `ContextScheduler.run_if_due()`:
+- 주간/월간/분기/연간/legacy 집계
+- 일 1회 `cleanup_expired_contexts()` 호출

- Constructs structured prompts from market data
- Parses JSON responses into `TradeDecision` objects (`action`, `confidence`, `rationale`)
- Forces HOLD when confidence < threshold (default 80)
- Falls back to safe HOLD on any parse/API error
- Handles markdown-wrapped JSON, malformed responses, invalid actions
+## Data Model (핵심)

-**PromptOptimizer** (`prompt_optimizer.py`) — Token efficiency optimization
+### `trades`

- Reduces prompt size while preserving decision quality
- Caches optimized prompts
+- `market`, `exchange_code`, `selection_context`, `decision_id` 포함
+- SELL 시 `get_latest_buy_trade()`를 통해 원본 BUY `decision_id`를 찾아 결과 업데이트

-**ContextSelector** (`context_selector.py`) — Relevant context selection for prompts
+### `decision_logs`

- Selects appropriate context layers for current market conditions
+- 의사결정 입력/컨텍스트 스냅샷 저장
+- `outcome_pnl`, `outcome_accuracy` 업데이트 가능

-### 4. Risk Manager (`src/core/risk_manager.py`)
+### `playbooks`

-**RiskManager** — Safety circuit breaker and order validation
+- `UNIQUE(date, market)`
+- `status`, `token_count`, `scenario_count`, `match_count` 관리

-> **READ-ONLY by policy** (see [`docs/agents.md`](./agents.md))
+## Dashboard

- **Circuit Breaker**: Halts all trading via `SystemExit` when daily P&L drops below -3.0%
-  - Threshold may only be made stricter, never relaxed
-  - Calculated as `(total_eval - purchase_total) / purchase_total * 100`
- **Fat-Finger Protection**: Rejects orders exceeding 30% of available cash
-  - Must always be enforced, cannot be disabled
+`src/dashboard/app.py`의 FastAPI 앱이 SQLite를 직접 조회합니다.

-### 5. Strategy (`src/strategy/`)
+엔드포인트:

-**Pre-Market Planner** (`pre_market_planner.py`) — AI playbook generation
+- `GET /api/status`
+- `GET /api/playbook/{date}?market=KR`
+- `GET /api/scorecard/{date}?market=KR`
+- `GET /api/performance?market=all`
+- `GET /api/context/{layer}`
+- `GET /api/decisions?market=KR`
+- `GET /api/scenarios/active?market=US`

- Runs before market open (configurable `PRE_MARKET_MINUTES`, default 30)
- Generates scenario-based playbooks via single Gemini API call per market
- Handles timeout (`PLANNER_TIMEOUT_SECONDS`, default 60) with defensive playbook fallback
- Persists playbooks to database for audit trail
+실행 통합:

-**Scenario Engine** (`scenario_engine.py`) — Local scenario matching
+- CLI `--dashboard`
+- 또는 `DASHBOARD_ENABLED=true`
+- `main.py`에서 daemon thread로 uvicorn 실행

- Matches live market data against pre-computed playbook scenarios
- No AI calls during trading hours — pure Python matching logic
- Returns matched scenarios with confidence scores
- Configurable `MAX_SCENARIOS_PER_STOCK` (default 5)
- Periodic rescan at `RESCAN_INTERVAL_SECONDS` (default 300)
+## Known Gaps (2026-02-16)

-**Playbook Store** (`playbook_store.py`) — Playbook persistence
-
- SQLite-backed storage for daily playbooks
- Date and market-based retrieval
- Status tracking (generated, active, expired)
-
-**Models** (`models.py`) — Pydantic data models
-
- Scenario, Playbook, MatchResult, and related type definitions
-
-### 6. Context System (`src/context/`)
-
-**Context Store** (`store.py`) — L1-L7 hierarchical memory
-
- 7-layer context system (see [docs/context-tree.md](./context-tree.md)):
-  - L1: Tick-level (real-time price)
-  - L2: Intraday (session summary)
-  - L3: Daily (end-of-day)
-  - L4: Weekly (trend analysis)
-  - L5: Monthly (strategy review)
-  - L6: Daily Review (scorecard)
-  - L7: Evolution (long-term learning)
- Key-value storage with timeframe tagging
- SQLite persistence in `contexts` table
-
-**Context Scheduler** (`scheduler.py`) — Periodic aggregation
-
- Scheduled summarization from lower to higher layers
- Configurable aggregation intervals
-
-**Context Summarizer** (`summarizer.py`) — Layer summarization
-
- Aggregates lower-layer data into higher-layer summaries
-
-### 7. Dashboard (`src/dashboard/`)
-
-**FastAPI App** (`app.py`) — Read-only monitoring dashboard
-
- Runs as daemon thread when enabled (`--dashboard` CLI flag or `DASHBOARD_ENABLED=true`)
- Configurable host/port (`DASHBOARD_HOST`, `DASHBOARD_PORT`, default `127.0.0.1:8080`)
- Serves static HTML frontend
-
-**8 API Endpoints:**
-
-| Endpoint | Method | Description |
-|----------|--------|-------------|
-| `/` | GET | Static HTML dashboard |
-| `/api/status` | GET | Daily trading status by market |
-| `/api/playbook/{date}` | GET | Playbook for specific date and market |
-| `/api/scorecard/{date}` | GET | Daily scorecard from L6_DAILY context |
-| `/api/performance` | GET | Trading performance metrics (by market + combined) |
-| `/api/context/{layer}` | GET | Query context by layer (L1-L7) |
-| `/api/decisions` | GET | Decision log entries with outcomes |
-| `/api/scenarios/active` | GET | Today's matched scenarios |
-
-### 8. Notifications (`src/notifications/telegram_client.py`)
-
-**TelegramClient** — Real-time event notifications via Telegram Bot API
-
- Sends alerts for trades, circuit breakers, fat-finger rejections, system events
- Non-blocking: failures are logged but never crash trading
- Rate-limited: 1 message/second default to respect Telegram API limits
- Auto-disabled when credentials missing
-
-**TelegramCommandHandler** — Bidirectional command interface
-
- Long polling from Telegram API (configurable `TELEGRAM_POLLING_INTERVAL`)
- 9 interactive commands: `/help`, `/status`, `/positions`, `/report`, `/scenarios`, `/review`, `/dashboard`, `/stop`, `/resume`
- Authorization filtering by `TELEGRAM_CHAT_ID`
- Enable/disable via `TELEGRAM_COMMANDS_ENABLED` (default: true)
-
-**Notification Types:**
- Trade execution (BUY/SELL with confidence)
- Circuit breaker trips (critical alert)
- Fat-finger protection triggers (order rejection)
- Market open/close events
- System startup/shutdown status
- Playbook generation results
- Stop-loss monitoring alerts
-
-### 9. Evolution (`src/evolution/`)
-
-**StrategyOptimizer** (`optimizer.py`) — Self-improvement loop
-
- Analyzes high-confidence losing trades from SQLite
- Asks Gemini to generate new `BaseStrategy` subclasses
- Validates generated strategies by running full pytest suite
- Simulates PR creation for human review
- Only activates strategies that pass all tests
-
-**DailyReview** (`daily_review.py`) — End-of-day review
-
- Generates comprehensive trade performance summary
- Stores results in L6_DAILY context layer
- Tracks win rate, P&L, confidence accuracy
-
-**DailyScorecard** (`scorecard.py`) — Performance scoring
-
- Calculates daily metrics (trades, P&L, win rate, avg confidence)
- Enables trend tracking across days
-
-**Stop-Loss Monitoring** — Real-time position protection
-
- Monitors positions against stop-loss levels from playbook scenarios
- Sends Telegram alerts when thresholds approached or breached
-
-### 10. Decision Logger (`src/logging/decision_logger.py`)
-
-**DecisionLogger** — Comprehensive audit trail
-
- Logs every trading decision with full context snapshot
- Captures input data, rationale, confidence, and outcomes
- Supports outcome tracking (P&L, accuracy) for post-analysis
- Stored in `decision_logs` table with indexed queries
- Review workflow support (reviewed flag, review notes)
-
-### 11. Data Integration (`src/data/`)
-
-**External Data Sources** (optional):
-
- `news_api.py` — News sentiment data
- `market_data.py` — Extended market data
- `economic_calendar.py` — Economic event calendar
-
-### 12. Backup (`src/backup/`)
-
-**Disaster Recovery** (see [docs/disaster_recovery.md](./disaster_recovery.md)):
-
- `scheduler.py` — Automated backup scheduling
- `exporter.py` — Data export to various formats
- `cloud_storage.py` — S3-compatible cloud backup
- `health_monitor.py` — Backup integrity verification
-
-## Data Flow
-
-### Playbook Mode (Daily — Primary v2 Flow)
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│ Pre-Market Phase (before market open)                       │
-└─────────────────────────────────────────────────────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Pre-Market Planner               │
-        │ - 1 Gemini API call per market   │
-        │ - Generate scenario playbook     │
-        │ - Store in playbooks table       │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-┌─────────────────────────────────────────────────────────────┐
-│ Trading Hours (market open → close)                         │
-└─────────────────────────────────────────────────────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Market Schedule Check            │
-        │ - Get open markets               │
-        │ - Filter by enabled markets      │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Scenario Engine (local)          │
-        │ - Match live data vs playbook    │
-        │ - No AI calls needed             │
-        │ - Return matched scenarios       │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Risk Manager: Validate Order     │
-        │ - Check circuit breaker          │
-        │ - Check fat-finger limit         │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Broker: Execute Order            │
-        │ - Domestic: send_order()         │
-        │ - Overseas: send_overseas_order()│
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Decision Logger + DB             │
-        │ - Full audit trail               │
-        │ - Context snapshot               │
-        │ - Telegram notification          │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-┌─────────────────────────────────────────────────────────────┐
-│ Post-Market Phase                                           │
-└─────────────────────────────────────────────────────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Daily Review + Scorecard         │
-        │ - Performance summary            │
-        │ - Store in L6_DAILY context      │
-        │ - Evolution learning             │
-        └──────────────────────────────────┘
-```
-
-### Realtime Mode (with Smart Scanner)
-
-```
-┌─────────────────────────────────────────────────────────────┐
-│ Main Loop (60s cycle per market)                            │
-└─────────────────────────────────────────────────────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Market Schedule Check            │
-        │ - Get open markets               │
-        │ - Filter by enabled markets      │
-        │ - Wait if all closed             │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Smart Scanner (Python-first)      │
-        │ - Domestic: fluctuation rank     │
-        │   + volume rank bonus            │
-        │   + volatility-first scoring     │
-        │ - Overseas: ranking universe     │
-        │   + volatility-first scoring     │
-        │ - Fallback: dynamic universe     │
-        │ - Return top 3 qualified stocks  │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ For Each Qualified Candidate     │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Broker: Fetch Market Data        │
-        │ - Domestic: orderbook + balance  │
-        │ - Overseas: price + balance      │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Brain: Get Decision (AI)         │
-        │ - Build prompt with market data  │
-        │ - Call Gemini API                │
-        │ - Parse JSON response            │
-        │ - Return TradeDecision           │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Risk Manager: Validate Order     │
-        │ - Check circuit breaker          │
-        │ - Check fat-finger limit         │
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Broker: Execute Order            │
-        │ - Domestic: send_order()         │
-        │ - Overseas: send_overseas_order()│
-        └──────────────────┬───────────────┘
-                           │
-                           ▼
-        ┌──────────────────────────────────┐
-        │ Decision Logger + Notifications  │
-        │ - Log trade to SQLite            │
-        │ - selection_context (JSON)       │
-        │ - Telegram notification          │
-        └──────────────────────────────────┘
-```
-
-## Database Schema
-
-**SQLite** (`src/db.py`) — Database: `data/trades.db`
-
-### trades
-```sql
-CREATE TABLE trades (
-    id INTEGER PRIMARY KEY AUTOINCREMENT,
-    timestamp TEXT NOT NULL,
-    stock_code TEXT NOT NULL,
-    action TEXT NOT NULL,          -- BUY | SELL | HOLD
-    confidence INTEGER NOT NULL,   -- 0-100
-    rationale TEXT,
-    quantity INTEGER,
-    price REAL,
-    pnl REAL DEFAULT 0.0,
-    market TEXT DEFAULT 'KR',
-    exchange_code TEXT DEFAULT 'KRX',
-    selection_context TEXT,        -- JSON: {rsi, volume_ratio, signal, score}
-    decision_id TEXT              -- Links to decision_logs
-);
-```
-
-### contexts
-```sql
-CREATE TABLE contexts (
-    id INTEGER PRIMARY KEY AUTOINCREMENT,
-    layer TEXT NOT NULL,           -- L1 through L7
-    timeframe TEXT,
-    key TEXT NOT NULL,
-    value TEXT NOT NULL,           -- JSON data
-    created_at TEXT NOT NULL,
-    updated_at TEXT NOT NULL
-);
-- Indices: idx_contexts_layer, idx_contexts_timeframe, idx_contexts_updated
-```
-
-### decision_logs
-```sql
-CREATE TABLE decision_logs (
-    decision_id TEXT PRIMARY KEY,
-    timestamp TEXT NOT NULL,
-    stock_code TEXT,
-    market TEXT,
-    exchange_code TEXT,
-    action TEXT,
-    confidence INTEGER,
-    rationale TEXT,
-    context_snapshot TEXT,         -- JSON: full context at decision time
-    input_data TEXT,              -- JSON: market data used
-    outcome_pnl REAL,
-    outcome_accuracy REAL,
-    reviewed INTEGER DEFAULT 0,
-    review_notes TEXT
-);
-- Indices: idx_decision_logs_timestamp, idx_decision_logs_reviewed, idx_decision_logs_confidence
-```
-
-### playbooks
-```sql
-CREATE TABLE playbooks (
-    id INTEGER PRIMARY KEY AUTOINCREMENT,
-    date TEXT NOT NULL,
-    market TEXT NOT NULL,
-    status TEXT DEFAULT 'generated',
-    playbook_json TEXT NOT NULL,   -- Full playbook with scenarios
-    generated_at TEXT NOT NULL,
-    token_count INTEGER,
-    scenario_count INTEGER,
-    match_count INTEGER DEFAULT 0
-);
-- Indices: idx_playbooks_date, idx_playbooks_market
-```
-
-### context_metadata
-```sql
-CREATE TABLE context_metadata (
-    layer TEXT PRIMARY KEY,
-    description TEXT,
-    retention_days INTEGER,
-    aggregation_source TEXT
-);
-```
-
-## Configuration
-
-**Pydantic Settings** (`src/config.py`)
-
-Loaded from `.env` file:
-
-```bash
-# Required
-KIS_APP_KEY=your_app_key
-KIS_APP_SECRET=your_app_secret
-KIS_ACCOUNT_NO=XXXXXXXX-XX
-GEMINI_API_KEY=your_gemini_key
-
-# Optional — Trading Mode
-MODE=paper                    # paper | live
-TRADE_MODE=daily              # daily | realtime
-DAILY_SESSIONS=4              # Sessions per day (daily mode only)
-SESSION_INTERVAL_HOURS=6      # Hours between sessions (daily mode only)
-
-# Optional — Database
-DB_PATH=data/trades.db
-
-# Optional — Risk
-CONFIDENCE_THRESHOLD=80
-MAX_LOSS_PCT=3.0
-MAX_ORDER_PCT=30.0
-
-# Optional — Markets
-ENABLED_MARKETS=KR,US         # Comma-separated market codes
-RATE_LIMIT_RPS=2.0            # KIS API requests per second
-
-# Optional — Pre-Market Planner (v2)
-PRE_MARKET_MINUTES=30         # Minutes before market open to generate playbook
-MAX_SCENARIOS_PER_STOCK=5     # Max scenarios per stock in playbook
-PLANNER_TIMEOUT_SECONDS=60    # Timeout for playbook generation
-DEFENSIVE_PLAYBOOK_ON_FAILURE=true  # Fallback on AI failure
-RESCAN_INTERVAL_SECONDS=300   # Scenario rescan interval during trading
-
-# Optional — Smart Scanner (realtime mode only)
-RSI_OVERSOLD_THRESHOLD=30     # 0-50, oversold threshold
-RSI_MOMENTUM_THRESHOLD=70     # 50-100, momentum threshold
-VOL_MULTIPLIER=2.0            # Minimum volume ratio (2.0 = 200%)
-SCANNER_TOP_N=3               # Max qualified candidates per scan
-
-# Optional — Dashboard
-DASHBOARD_ENABLED=false       # Enable FastAPI dashboard
-DASHBOARD_HOST=127.0.0.1      # Dashboard bind address
-DASHBOARD_PORT=8080           # Dashboard port (1-65535)
-
-# Optional — Telegram
-TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
-TELEGRAM_CHAT_ID=123456789
-TELEGRAM_ENABLED=true
-TELEGRAM_COMMANDS_ENABLED=true   # Enable bidirectional commands
-TELEGRAM_POLLING_INTERVAL=1.0    # Command polling interval (seconds)
-
-# Optional — Backup
-BACKUP_ENABLED=false
-BACKUP_DIR=data/backups
-S3_ENDPOINT_URL=...
-S3_ACCESS_KEY=...
-S3_SECRET_KEY=...
-S3_BUCKET_NAME=...
-S3_REGION=...
-
-# Optional — External Data
-NEWS_API_KEY=...
-NEWS_API_PROVIDER=...
-MARKET_DATA_API_KEY=...
-
-# Position Sizing (optional)
-POSITION_SIZING_ENABLED=true
-POSITION_BASE_ALLOCATION_PCT=5.0
-POSITION_MIN_ALLOCATION_PCT=1.0
-POSITION_MAX_ALLOCATION_PCT=10.0
-POSITION_VOLATILITY_TARGET_SCORE=50.0
-
-# Legacy/compat scanner thresholds (kept for backward compatibility)
-RSI_OVERSOLD_THRESHOLD=30
-RSI_MOMENTUM_THRESHOLD=70
-VOL_MULTIPLIER=2.0
-
-# Overseas Ranking API (optional override; account-dependent)
-OVERSEAS_RANKING_ENABLED=true
-OVERSEAS_RANKING_FLUCT_TR_ID=HHDFS76200100
-OVERSEAS_RANKING_VOLUME_TR_ID=HHDFS76200200
-OVERSEAS_RANKING_FLUCT_PATH=/uapi/overseas-price/v1/quotations/inquire-updown-rank
-OVERSEAS_RANKING_VOLUME_PATH=/uapi/overseas-price/v1/quotations/inquire-volume-rank
-```
-
-Tests use in-memory SQLite (`DB_PATH=":memory:"`) and dummy credentials via `tests/conftest.py`.
-
-## Error Handling
-
-### Connection Errors (Broker API)
- Retry with exponential backoff (2^attempt seconds)
- Max 3 retries per stock
- After exhaustion, skip stock and continue with next
-
-### API Quota Errors (Gemini)
- Return safe HOLD decision with confidence=0
- Log error but don't crash
- Agent continues trading on next cycle
-
-### Circuit Breaker Tripped
- Immediately halt via `SystemExit`
- Log critical message
- Requires manual intervention to restart
-
-### Market Closed
- Wait until next market opens
- Use `get_next_market_open()` to calculate wait time
- Sleep until market open time
-
-### Telegram API Errors
- Log warning but continue trading
- Missing credentials → auto-disable notifications
- Network timeout → skip notification, no retry
- Invalid token → log error, trading unaffected
- Rate limit exceeded → queued via rate limiter
-
-### Playbook Generation Failure
- Timeout → fall back to defensive playbook (`DEFENSIVE_PLAYBOOK_ON_FAILURE`)
- API error → use previous day's playbook if available
- No playbook → skip pre-market phase, fall back to direct AI calls
-
-**Guarantee**: Notification and dashboard failures never interrupt trading operations.
+- `Issue 4-1` Telegram 확장 명령 미구현 (`/report`, `/scenarios`, `/review`, `/dashboard`)
+- `Issue 1-7` 일부 미완:
+- `price_change_pct` 정규화 계층 명시 미흡
+- 영향: `price_change_pct` 기반 조건은 현재 사실상 매칭되지 않음
+- HOLD 시 별도 손절 모니터링 플래그 처리 미완
+- US 스캐닝 확장(`fetch_overseas_rankings`) 미구현
--- a/docs/commands.md
+++ b/docs/commands.md
@@ -1,206 +1,82 @@
 # Command Reference

-## Common Command Failures
-
-**Critical: Learn from failures. Never repeat the same failed command without modification.**
-
-### tea CLI (Gitea Command Line Tool)
-
-#### ❌ TTY Error - Interactive Confirmation Fails
-```bash
-~/bin/tea issues create --repo X --title "Y" --description "Z"
-# Error: huh: could not open a new TTY: open /dev/tty: no such device or address
-```
-**💡 Reason:** tea tries to open `/dev/tty` for interactive confirmation prompts, which is unavailable in non-interactive environments.
-
-**✅ Solution:** Use `YES=""` environment variable to bypass confirmation
-```bash
-YES="" ~/bin/tea issues create --repo jihoson/The-Ouroboros --title "Title" --description "Body"
-YES="" ~/bin/tea issues edit <number> --repo jihoson/The-Ouroboros --description "Updated body"
-YES="" ~/bin/tea pulls create --repo jihoson/The-Ouroboros --head feature-branch --base main --title "Title" --description "Body"
-```
-
-**📝 Notes:**
- Always set default login: `~/bin/tea login default local`
- Use `--repo jihoson/The-Ouroboros` when outside repo directory
- tea is preferred over direct Gitea API calls for consistency
-
-#### ❌ Wrong Parameter Name
-```bash
-tea issues create --body "text"
-# Error: flag provided but not defined: -body
-```
-**💡 Reason:** Parameter is `--description`, not `--body`.
-
-**✅ Solution:** Use correct parameter name
-```bash
-YES="" ~/bin/tea issues create --description "text"
-```
-
-### Gitea API (Direct HTTP Calls)
-
-#### ❌ Wrong Hostname
-```bash
-curl http://gitea.local:3000/api/v1/...
-# Error: Could not resolve host: gitea.local
-```
-**💡 Reason:** Gitea instance runs on `localhost:3000`, not `gitea.local`.
-
-**✅ Solution:** Use correct hostname (but prefer tea CLI)
-```bash
-curl http://localhost:3000/api/v1/repos/jihoson/The-Ouroboros/issues \
-  -H "Authorization: token $GITEA_TOKEN" \
-  -H "Content-Type: application/json" \
-  -d '{"title":"...", "body":"..."}'
-```
-
-**📝 Notes:**
- Prefer `tea` CLI over direct API calls
- Only use curl for operations tea doesn't support
-
-### Git Commands
-
-#### ❌ User Not Configured
-```bash
-git commit -m "message"
-# Error: Author identity unknown
-```
-**💡 Reason:** Git user.name and user.email not set.
-
-**✅ Solution:** Configure git user
-```bash
-git config user.name "agentson"
-git config user.email "agentson@localhost"
-```
-
-#### ❌ Permission Denied on Push
-```bash
-git push origin branch
-# Error: User permission denied for writing
-```
-**💡 Reason:** Repository access token lacks write permissions or user lacks repo write access.
-
-**✅ Solution:**
-1. Verify user has write access to repository (admin grants this)
-2. Ensure git credential has correct token with `write:repository` scope
-3. Check remote URL uses correct authentication
-
-### Python/Pytest
-
-#### ❌ Module Import Error
-```bash
-pytest tests/test_foo.py
-# ModuleNotFoundError: No module named 'src'
-```
-**💡 Reason:** Package not installed in development mode.
-
-**✅ Solution:** Install package with dev dependencies
-```bash
-pip install -e ".[dev]"
-```
-
-#### ❌ Async Test Hangs
-```python
-async def test_something():  # Hangs forever
-    result = await async_function()
-```
-**💡 Reason:** Missing pytest-asyncio or wrong configuration.
-
-**✅ Solution:** Already configured in pyproject.toml
-```toml
-[tool.pytest.ini_options]
-asyncio_mode = "auto"
-```
-No decorator needed for async tests.
-
-## Build & Test Commands
+## Core Runtime Commands

 ```bash
-# Install all dependencies (production + dev)
-pip install -e ".[dev]"
-
-# Run full test suite with coverage (551 tests across 25 files)
-pytest -v --cov=src --cov-report=term-missing
-
-# Run a single test file
-pytest tests/test_risk.py -v
-
-# Run a single test by name
-pytest tests/test_brain.py -k "test_parse_valid_json" -v
-
-# Lint
-ruff check src/ tests/
-
-# Type check (strict mode, non-blocking in CI)
-mypy src/ --strict
-
-# Run the trading agent
+# run (paper)
 python -m src.main --mode=paper

-# Run with dashboard enabled
+# run with dashboard thread
 python -m src.main --mode=paper --dashboard

-# Docker
-docker compose up -d ouroboros          # Run agent
-docker compose --profile test up test   # Run tests in container
+# tests
+pytest -v --cov=src
+
+# lint
+ruff check src/ tests/
+
+# type-check
+mypy src/ --strict
 ```

-## Dashboard
+## Dashboard Runtime Controls

-The FastAPI dashboard provides read-only monitoring of the trading system.
+`Issue 4-3` 기준 반영:

-### Starting the Dashboard
+- CLI: `--dashboard`
+- ENV: `DASHBOARD_ENABLED=true`
+- Host/Port:
+- `DASHBOARD_HOST` (default `127.0.0.1`)
+- `DASHBOARD_PORT` (default `8080`)
+
+## Telegram Commands (현재 구현)
+
+`main.py` 등록 기준:
+
+- `/help`
+- `/status`
+- `/positions`
+- `/stop`
+- `/resume`
+
+## Telegram Commands (미구현 상태)
+
+V2 플랜 `Issue 4-1` 항목은 아직 미구현:
+
+- `/report [KR|US]`
+- `/scenarios [KR|US]`
+- `/review [KR|US]`
+- `/dashboard`
+
+## Gitea / tea Workflow Commands
+
+이슈 선등록 후 작업 시작:

 ```bash
-# Via CLI flag
-python -m src.main --mode=paper --dashboard
-
-# Via environment variable
-DASHBOARD_ENABLED=true python -m src.main --mode=paper
+YES="" ~/bin/tea issues create \
+  --repo jihoson/The-Ouroboros \
+  --title "..." \
+  --description "..."
 ```

-Dashboard runs as a daemon thread on `DASHBOARD_HOST:DASHBOARD_PORT` (default: `127.0.0.1:8080`).
-
-### API Endpoints
-
-| Endpoint | Description |
-|----------|-------------|
-| `GET /` | HTML dashboard UI |
-| `GET /api/status` | Daily trading status by market |
-| `GET /api/playbook/{date}` | Playbook for specific date (query: `market`) |
-| `GET /api/scorecard/{date}` | Daily scorecard from L6_DAILY context |
-| `GET /api/performance` | Performance metrics by market and combined |
-| `GET /api/context/{layer}` | Context data by layer L1-L7 (query: `timeframe`) |
-| `GET /api/decisions` | Decision log entries (query: `limit`, `market`) |
-| `GET /api/scenarios/active` | Today's matched scenarios |
-
-## Telegram Commands
-
-When `TELEGRAM_COMMANDS_ENABLED=true` (default), the bot accepts these interactive commands:
-
-| Command | Description |
-|---------|-------------|
-| `/help` | List available commands |
-| `/status` | Show trading status (mode, markets, P&L) |
-| `/positions` | Display account summary (balance, cash, P&L) |
-| `/report` | Daily summary metrics (trades, P&L, win rate) |
-| `/scenarios` | Show today's playbook scenarios |
-| `/review` | Display recent scorecards (L6_DAILY layer) |
-| `/dashboard` | Show dashboard URL if enabled |
-| `/stop` | Pause trading |
-| `/resume` | Resume trading |
-
-Commands are only processed from the authorized `TELEGRAM_CHAT_ID`.
-
-## Environment Setup
+작업은 `worktree` 기준 권장:

 ```bash
-# Create .env file from example
-cp .env.example .env
-
-# Edit .env with your credentials
-# Required: KIS_APP_KEY, KIS_APP_SECRET, KIS_ACCOUNT_NO, GEMINI_API_KEY
-
-# Verify configuration
-python -c "from src.config import Settings; print(Settings())"
+git worktree add ../The-Ouroboros-issue-<N> feature/issue-<N>-<slug>
 ```
+
+PR 생성:
+
+```bash
+YES="" ~/bin/tea pulls create \
+  --repo jihoson/The-Ouroboros \
+  --head feature/issue-<N>-<slug> \
+  --base main \
+  --title "..." \
+  --description "..."
+```
+
+## Known tea CLI Gotcha
+
+TTY 없는 환경에서는 `tea` 확인 프롬프트가 실패할 수 있습니다.
+항상 `YES=""`를 붙여 비대화식으로 실행하세요.
--- a/docs/context-tree.md
+++ b/docs/context-tree.md
@@ -1,243 +1,81 @@
 # Context Tree: Multi-Layered Memory Management

-The context tree implements **Pillar 2** of The Ouroboros: hierarchical memory management across 7 time horizons, from real-time market data to generational trading wisdom.
+## Summary

-## Overview
+컨텍스트 트리는 L7(실시간)부터 L1(레거시)까지 계층화된 메모리 구조입니다.

-Instead of a flat memory structure, The Ouroboros maintains a **7-tier context tree** where each layer represents a different time horizon and level of abstraction:
+- L7~L5: 시장별 독립 데이터 중심
+- L4~L1: 글로벌 포트폴리오 통합 데이터

-```
-L1 (Legacy)      ←  Cumulative wisdom across generations
-  ↑
-L2 (Annual)      ←  Yearly performance metrics
-  ↑
-L3 (Quarterly)   ←  Quarterly strategy adjustments
-  ↑
-L4 (Monthly)     ←  Monthly portfolio rebalancing
-  ↑
-L5 (Weekly)      ←  Weekly stock selection
-  ↑
-L6 (Daily)       ←  Daily trade logs
-  ↑
-L7 (Real-time)   ←  Live market data
-```
+## Layer Policy

-Data flows **bottom-up**: real-time trades aggregate into daily summaries, which roll up to weekly, then monthly, quarterly, annual, and finally into permanent legacy knowledge.
+### L7_REALTIME (시장+종목 스코프)

-## The 7 Layers
+- 주요 키 패턴:
+- `volatility_{market}_{stock_code}`
+- `price_{market}_{stock_code}`
+- `rsi_{market}_{stock_code}`
+- `volume_ratio_{market}_{stock_code}`

-### L7: Real-time
-**Retention**: 7 days
-**Timeframe format**: `YYYY-MM-DD` (same-day)
-**Content**: Current positions, live quotes, orderbook snapshots, tick-by-tick volatility
+`trading_cycle()`에서 실시간으로 기록합니다.

-**Use cases**:
- Immediate execution decisions
- Stop-loss triggers
- Real-time P&L tracking
+### L6_DAILY (시장 스코프)

-**Example keys**:
- `current_position_{stock_code}`: Current holdings
- `live_price_{stock_code}`: Latest quote
- `volatility_5m_{stock_code}`: 5-minute rolling volatility
+EOD 집계 결과를 시장별 키로 저장합니다.

-### L6: Daily
-**Retention**: 90 days
-**Timeframe format**: `YYYY-MM-DD`
-**Content**: Daily trade logs, end-of-day P&L, market summaries, decision accuracy
+- `trade_count_KR`, `buys_KR`, `sells_KR`, `holds_KR`
+- `avg_confidence_US`, `total_pnl_US`, `win_rate_US`
+- scorecard 저장 키: `scorecard_KR`, `scorecard_US`

-**Use cases**:
- Daily performance review
- Identify patterns in recent trading
- Backtest strategy adjustments
+### L5_WEEKLY

-**Example keys**:
- `total_pnl`: Daily profit/loss
- `trade_count`: Number of trades
- `win_rate`: Percentage of profitable trades
- `avg_confidence`: Average Gemini confidence
+L6 일일 데이터에서 시장별 주간 합계를 생성합니다.

-### L5: Weekly
-**Retention**: 1 year
-**Timeframe format**: `YYYY-Www` (ISO week, e.g., `2026-W06`)
-**Content**: Weekly stock selection, sector rotation, volatility regime classification
+- `weekly_pnl_KR`, `weekly_pnl_US`
+- `avg_confidence_KR`, `avg_confidence_US`

-**Use cases**:
- Weekly strategy adjustment
- Sector momentum tracking
- Identify hot/cold markets
+### L4_MONTHLY 이상

-**Example keys**:
- `weekly_pnl`: Week's total P&L
- `top_performers`: Best-performing stocks
- `sector_focus`: Dominant sectors
- `avg_confidence`: Weekly average confidence
+글로벌 통합 롤업입니다.

-### L4: Monthly
-**Retention**: 2 years
-**Timeframe format**: `YYYY-MM`
-**Content**: Monthly portfolio rebalancing, risk exposure analysis, drawdown recovery
+- L5 → L4: `monthly_pnl`
+- L4 → L3: `quarterly_pnl`
+- L3 → L2: `annual_pnl`
+- L2 → L1: `total_pnl`, `years_traded`, `avg_annual_pnl`

-**Use cases**:
- Monthly performance reporting
- Risk exposure adjustment
- Correlation analysis
+## Aggregation Flow

-**Example keys**:
- `monthly_pnl`: Month's total P&L
- `sharpe_ratio`: Risk-adjusted return
- `max_drawdown`: Largest peak-to-trough decline
- `rebalancing_notes`: Manual insights
+- EOD: `ContextAggregator.aggregate_daily_from_trades(date, market)`
+- 주기 롤업: `ContextScheduler.run_if_due()`

-### L3: Quarterly
-**Retention**: 3 years
-**Timeframe format**: `YYYY-Qn` (e.g., `2026-Q1`)
-**Content**: Quarterly strategy pivots, market phase detection (bull/bear/sideways), macro regime changes
+`ContextScheduler`는 다음을 처리합니다.

-**Use cases**:
- Strategic pivots (e.g., growth → value)
- Macro regime classification
- Long-term pattern recognition
-
-**Example keys**:
- `quarterly_pnl`: Quarter's total P&L
- `market_phase`: Bull/Bear/Sideways
- `strategy_adjustments`: Major changes made
- `lessons_learned`: Key insights
-
-### L2: Annual
-**Retention**: 10 years
-**Timeframe format**: `YYYY`
-**Content**: Yearly returns, Sharpe ratio, max drawdown, win rate, strategy effectiveness
-
-**Use cases**:
- Annual performance review
- Multi-year trend analysis
- Strategy benchmarking
-
-**Example keys**:
- `annual_pnl`: Year's total P&L
- `sharpe_ratio`: Annual risk-adjusted return
- `win_rate`: Yearly win percentage
- `best_strategy`: Most successful strategy
- `worst_mistake`: Biggest lesson learned
-
-### L1: Legacy
-**Retention**: Forever
-**Timeframe format**: `LEGACY` (single timeframe)
-**Content**: Cumulative trading history, core principles, generational wisdom
-
-**Use cases**:
- Long-term philosophy
- Foundational rules
- Lessons that transcend market cycles
-
-**Example keys**:
- `total_pnl`: All-time profit/loss
- `years_traded`: Trading longevity
- `avg_annual_pnl`: Long-term average return
- `core_principles`: Immutable trading rules
- `greatest_trades`: Hall of fame
- `never_again`: Permanent warnings
+- weekly/monthly/quarterly/annual/legacy 집계
+- 일 1회 `ContextStore.cleanup_expired_contexts()` 실행
+- 동일 날짜 중복 실행 방지(`_last_run`)

 ## Usage

-### Setting Context
-
 ```python
-from src.context import ContextLayer, ContextStore
-from src.db import init_db
+from datetime import UTC, datetime

-conn = init_db("data/ouroboros.db")
-store = ContextStore(conn)
-
-# Store daily P&L
-store.set_context(
-    layer=ContextLayer.L6_DAILY,
-    timeframe="2026-02-04",
-    key="total_pnl",
-    value=1234.56
-)
-
-# Store weekly insight
-store.set_context(
-    layer=ContextLayer.L5_WEEKLY,
-    timeframe="2026-W06",
-    key="top_performers",
-    value=["005930", "000660", "035720"]  # JSON-serializable
-)
-
-# Store legacy wisdom
-store.set_context(
-    layer=ContextLayer.L1_LEGACY,
-    timeframe="LEGACY",
-    key="core_principles",
-    value=[
-        "Cut losses fast",
-        "Let winners run",
-        "Never average down on losing positions"
-    ]
-)
-```
-
-### Retrieving Context
-
-```python
-# Get a specific value
-pnl = store.get_context(ContextLayer.L6_DAILY, "2026-02-04", "total_pnl")
-# Returns: 1234.56
-
-# Get all keys for a timeframe
-daily_summary = store.get_all_contexts(ContextLayer.L6_DAILY, "2026-02-04")
-# Returns: {"total_pnl": 1234.56, "trade_count": 10, "win_rate": 60.0, ...}
-
-# Get all data for a layer (any timeframe)
-all_daily = store.get_all_contexts(ContextLayer.L6_DAILY)
-# Returns: {"total_pnl": 1234.56, "trade_count": 10, ...} (latest timeframes first)
-
-# Get the latest timeframe
-latest = store.get_latest_timeframe(ContextLayer.L6_DAILY)
-# Returns: "2026-02-04"
-```
-
-### Automatic Aggregation
-
-The `ContextAggregator` rolls up data from lower to higher layers:
-
-```python
 from src.context.aggregator import ContextAggregator
+from src.context.scheduler import ContextScheduler

 aggregator = ContextAggregator(conn)
+scheduler = ContextScheduler(aggregator=aggregator, store=context_store)

-# Aggregate daily metrics from trades
-aggregator.aggregate_daily_from_trades("2026-02-04")
+# EOD market-scoped daily aggregation
+aggregator.aggregate_daily_from_trades(date="2026-02-16", market="KR")

-# Roll up weekly from daily
-aggregator.aggregate_weekly_from_daily("2026-W06")
-
-# Roll up all layers at once (bottom-up)
-aggregator.run_all_aggregations()
+# Run scheduled rollups when due
+scheduler.run_if_due(now=datetime.now(UTC))
 ```

-**Aggregation schedule** (recommended):
- **L7 → L6**: Every midnight (daily rollup)
- **L6 → L5**: Every Sunday (weekly rollup)
- **L5 → L4**: First day of each month (monthly rollup)
- **L4 → L3**: First day of quarter (quarterly rollup)
- **L3 → L2**: January 1st (annual rollup)
- **L2 → L1**: On demand (major milestones)
+## Retention

-### Context Cleanup
+`src/context/layer.py` 기준:

-Expired contexts are automatically deleted based on retention policies:
-
-```python
-# Manual cleanup
-deleted = store.cleanup_expired_contexts()
-# Returns: {ContextLayer.L7_REALTIME: 42, ContextLayer.L6_DAILY: 15, ...}
-```
-
-**Retention policies** (defined in `src/context/layer.py`):
 - L1: Forever
 - L2: 10 years
 - L3: 3 years
@@ -246,93 +84,8 @@ deleted = store.cleanup_expired_contexts()
 - L6: 90 days
 - L7: 7 days

-## Integration with Gemini Brain
+## Current Notes (2026-02-16)

-The context tree provides hierarchical memory for decision-making:
-
-```python
-from src.brain.gemini_client import GeminiClient
-
-# Build prompt with multi-layer context
-def build_enhanced_prompt(stock_code: str, store: ContextStore) -> str:
-    # L7: Real-time data
-    current_price = store.get_context(ContextLayer.L7_REALTIME, "2026-02-04", f"live_price_{stock_code}")
-
-    # L6: Recent daily performance
-    yesterday_pnl = store.get_context(ContextLayer.L6_DAILY, "2026-02-03", "total_pnl")
-
-    # L5: Weekly trend
-    weekly_data = store.get_all_contexts(ContextLayer.L5_WEEKLY, "2026-W06")
-
-    # L1: Core principles
-    principles = store.get_context(ContextLayer.L1_LEGACY, "LEGACY", "core_principles")
-
-    return f"""
-    Analyze {stock_code} for trading decision.
-
-    Current price: {current_price}
-    Yesterday's P&L: {yesterday_pnl}
-    This week: {weekly_data}
-
-    Core principles:
-    {chr(10).join(f'- {p}' for p in principles)}
-
-    Decision (BUY/SELL/HOLD):
-    """
-```
-
-## Database Schema
-
-```sql
-- Context storage
-CREATE TABLE contexts (
-    id INTEGER PRIMARY KEY AUTOINCREMENT,
-    layer TEXT NOT NULL,          -- L1_LEGACY, L2_ANNUAL, ..., L7_REALTIME
-    timeframe TEXT NOT NULL,      -- "LEGACY", "2026", "2026-Q1", "2026-02", "2026-W06", "2026-02-04"
-    key TEXT NOT NULL,            -- "total_pnl", "win_rate", "core_principles", etc.
-    value TEXT NOT NULL,          -- JSON-serialized value
-    created_at TEXT NOT NULL,     -- ISO 8601 timestamp
-    updated_at TEXT NOT NULL,     -- ISO 8601 timestamp
-    UNIQUE(layer, timeframe, key)
-);
-
-- Layer metadata
-CREATE TABLE context_metadata (
-    layer TEXT PRIMARY KEY,
-    description TEXT NOT NULL,
-    retention_days INTEGER,       -- NULL = keep forever
-    aggregation_source TEXT       -- Parent layer for rollup
-);
-
-- Indices for fast queries
-CREATE INDEX idx_contexts_layer ON contexts(layer);
-CREATE INDEX idx_contexts_timeframe ON contexts(timeframe);
-CREATE INDEX idx_contexts_updated ON contexts(updated_at);
-```
-
-## Best Practices
-
-1. **Write to leaf layers only** — Never manually write to L1-L5; let aggregation populate them
-2. **Aggregate regularly** — Schedule aggregation jobs to keep higher layers fresh
-3. **Query specific timeframes** — Use `get_context(layer, timeframe, key)` for precise retrieval
-4. **Clean up periodically** — Run `cleanup_expired_contexts()` weekly to free space
-5. **Preserve L1 forever** — Legacy wisdom should never expire
-6. **Use JSON-serializable values** — Store dicts, lists, strings, numbers (not custom objects)
-
-## Testing
-
-See `tests/test_context.py` for comprehensive test coverage (18 tests, 100% coverage on context modules).
-
-```bash
-pytest tests/test_context.py -v
-```
-
-## References
-
- **Implementation**: `src/context/`
-  - `layer.py`: Layer definitions and metadata
-  - `store.py`: CRUD operations
-  - `aggregator.py`: Bottom-up aggregation logic
- **Database**: `src/db.py` (table initialization)
- **Tests**: `tests/test_context.py`
- **Related**: Pillar 2 (Multi-layered Context Management)
+- L7 쓰기와 L6 시장별 집계는 `main.py`에 연결됨
+- scheduler 기반 cleanup/rollup도 연결됨
+- cross-market scorecard 조회는 `PreMarketPlanner`에서 사용 중
--- a/docs/requirements-log.md
+++ b/docs/requirements-log.md
@@ -91,178 +91,43 @@

 ## 2026-02-16

-### 문서 v2 동기화 (전체 문서 현행화)
+### V2 진행상태 재정렬 + 문서 동기화

 **배경:**
- v2 기능 구현 완료 후 문서가 실제 코드 상태와 크게 괴리
- 문서에는 54 tests / 4 files로 기록되었으나 실제로는 551 tests / 25 files
- v2 핵심 기능(Playbook, Scenario Engine, Dashboard, Telegram Commands, Daily Review, Context System, Backup) 문서화 누락
+- V2 이슈 다수가 병렬로 진행되며 구현/문서 간 상태 불일치가 발생
+- 사용자 요청으로 "현재 코드 기준 사실"에 맞춘 전면 문서 갱신 필요

-**요구사항:**
-1. `docs/testing.md` — 551 tests / 25 files 반영, 전체 테스트 파일 설명
-2. `docs/architecture.md` — v2 컴포넌트(Strategy, Context, Dashboard, Decision Logger 등) 추가, Playbook Mode 데이터 플로우, DB 스키마 5개 테이블, v2 환경변수
-3. `docs/commands.md` — Dashboard 실행 명령어, Telegram 명령어 9종 레퍼런스
-4. `CLAUDE.md` — Project Structure 트리 확장, 테스트 수 업데이트, `--dashboard` 플래그
-5. `docs/skills.md` — DB 파일명 `trades.db`로 통일, Dashboard 명령어 추가
-6. 기존에 유효한 트러블슈팅, 코드 예제 등은 유지
+**확인된 상태(코드 기준):**
+- 완료: 18/20
+- 부분 완료: `1-7`
+- 미완료: `4-1`

-**구현 결과:**
- 6개 문서 파일 업데이트
- 이전 시도(2개 커밋)는 기존 내용을 과도하게 삭제하여 폐기, main 기준으로 재작업
+**핵심 반영 사항:**
+1. 대시보드 실행 통합(`Issue 4-3`) 반영
+   - `--dashboard` 플래그
+   - `DASHBOARD_ENABLED`, `DASHBOARD_HOST`, `DASHBOARD_PORT`
+2. 컨텍스트 스케줄러 및 시장 스코프 키 정책 반영
+3. scorecard/review/evolution 연결 상태 반영
+4. 미완료 갭 명시
+   - Telegram 확장 명령어(`4-1`) 미구현
+   - `1-7` 잔여 항목(키 정규화/HOLD 손절 모니터링/US 코드 정합성)

-**이슈/PR:** #131, PR #134
+**프로세스 요구사항 강화:**
+- 모든 문서 작업도 Gitea 이슈 선등록 후 진행
+- 병렬 작업 후 상태 정합성 점검 결과를 `requirements-log`에 기록

-### 해외 스캐너 개선: 랭킹 연동 + 변동성 우선 선별
+**이슈/브랜치:**
+- Issue: #131
+- Branch(worktree): `feature/issue-131-docs-v2-status-sync`

-**배경:**
- `run_overnight` 실운영에서 미국장 동안 거래가 0건 지속
- 원인: 해외 시장에서도 국내 랭킹/일봉 API 경로를 사용하던 구조적 불일치
+### 문서 보강 2차 (리뷰 반영)

-**요구사항:**
-1. 해외 시장도 랭킹 API 기반 유니버스 탐색 지원
-2. 단순 상승률/거래대금 상위가 아니라, **변동성이 큰 종목**을 우선 선별
-3. 고정 티커 fallback 금지
+**리뷰 피드백 반영:**
+- README에 Quick Start(환경설정/설치/검증) 복원
+- architecture에 RiskManager/에러 처리/설정 레퍼런스 복원
+- testing 문서에 기존 핵심 테스트 파일 설명 복원
+- 시장 코드 불일치(`KR,US` vs `US_NASDAQ/US_NYSE`)를 "런타임 영향"으로 격상 명시
+- `price_change_pct` 누락 영향(조건 dead path)을 명시

-**구현 결과:**
- `src/broker/overseas.py`
-  - `fetch_overseas_rankings()` 추가 (fluctuation / volume)
-  - 해외 랭킹 API 경로/TR_ID를 설정값으로 오버라이드 가능하게 구현
- `src/analysis/smart_scanner.py`
-  - market-aware 스캔(국내/해외 분리)
-  - 해외: 랭킹 API 유니버스 + 변동성 우선 점수(일변동률 vs 장중 고저폭)
-  - 거래대금/거래량 랭킹은 유동성 보정 점수로 활용
-  - 랭킹 실패 시에는 동적 유니버스(active/recent/holdings)만 사용
- `src/config.py`
-  - `OVERSEAS_RANKING_*` 설정 추가
-
-**효과:**
- 해외 시장에서 스캐너 후보 0개로 정지되는 상황 완화
- 종목 선정 기준이 단순 상승률 중심에서 변동성 중심으로 개선
- 고정 티커 없이도 시장 주도 변동 종목 탐지 가능
-
-### 국내 스캐너/주문수량 정렬: 변동성 우선 + 리스크 타기팅
-
-**배경:**
- 해외만 변동성 우선으로 동작하고, 국내는 RSI/거래량 필터 중심으로 동작해 시장 간 전략 일관성이 낮았음
- 매수 수량이 고정 1주라서 변동성 구간별 익스포저 관리가 어려웠음
-
-**요구사항:**
-1. 국내 스캐너도 변동성 우선 선별로 해외와 통일
-2. 고변동 종목일수록 포지션 크기를 줄이는 수량 산식 적용
-
-**구현 결과:**
- `src/analysis/smart_scanner.py`
-  - 국내: `fluctuation ranking + volume ranking bonus` 기반 점수화로 전환
-  - 점수는 `max(abs(change_rate), intraday_range_pct)` 중심으로 계산
-  - 국내 랭킹 응답 스키마 키(`price`, `change_rate`, `volume`) 파싱 보강
- `src/main.py`
-  - `_determine_order_quantity()` 추가
-  - BUY 시 변동성 점수 기반 동적 수량 산정 적용
-  - `trading_cycle`, `run_daily_session` 경로 모두 동일 수량 로직 사용
- `src/config.py`
-  - `POSITION_SIZING_*` 설정 추가
-
-**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
+**의도:**
+- V2 상태 반영과 기존 온보딩/운영 문서 가치를 동시에 유지
--- a/docs/skills.md
+++ b/docs/skills.md
@@ -34,12 +34,6 @@ python -m src.main --mode=paper
 ```
 Runs the agent in paper-trading mode (no real orders).

-### Start Trading Agent with Dashboard
-```bash
-python -m src.main --mode=paper --dashboard
-```
-Runs the agent with FastAPI dashboard on `127.0.0.1:8080` (configurable via `DASHBOARD_HOST`/`DASHBOARD_PORT`).
-
 ### Start Trading Agent (Production)
 ```bash
 docker compose up -d ouroboros
@@ -65,7 +59,7 @@ Analyze the last 30 days of trade logs and generate performance metrics.
 python -m src.evolution.optimizer --evolve
 ```
 Triggers the evolution engine to:
-1. Analyze `trades.db` for failing patterns
+1. Analyze `trade_logs.db` for failing patterns
 2. Ask Gemini to generate a new strategy
 3. Run tests on the new strategy
 4. Create a PR if tests pass
@@ -97,12 +91,12 @@ curl http://localhost:8080/health

 ### View Trade Logs
 ```bash
-sqlite3 data/trades.db "SELECT * FROM trades ORDER BY timestamp DESC LIMIT 20;"
+sqlite3 data/trade_logs.db "SELECT * FROM trades ORDER BY timestamp DESC LIMIT 20;"
 ```

 ### Export Trade History
 ```bash
-sqlite3 -header -csv data/trades.db "SELECT * FROM trades;" > trades_export.csv
+sqlite3 -header -csv data/trade_logs.db "SELECT * FROM trades;" > trades_export.csv
 ```

 ## Safety Checklist (Pre-Deploy)
--- a/docs/testing.md
+++ b/docs/testing.md
@@ -1,287 +1,63 @@
 # Testing Guidelines

-## Test Structure
+## Current Test Baseline (2026-02-16)

-**551 tests** across **25 files**. `asyncio_mode = "auto"` in pyproject.toml — async tests need no special decorator.
-
-The `settings` fixture in `conftest.py` provides safe defaults with test credentials and in-memory DB.
-
-### Test Files
-
-#### Core Components
-
-##### `tests/test_risk.py` (14 tests)
- Circuit breaker boundaries and exact threshold triggers
- Fat-finger edge cases and percentage validation
- P&L calculation edge cases
- Order validation logic
-
-##### `tests/test_broker.py` (11 tests)
- OAuth token lifecycle
- Rate limiting enforcement
- Hash key generation
- Network error handling
- SSL context configuration
-
-##### `tests/test_brain.py` (24 tests)
- Valid JSON parsing and markdown-wrapped JSON handling
- Malformed JSON fallback
- Missing fields handling
- Invalid action validation
- Confidence threshold enforcement
- Empty response handling
- Prompt construction for different markets
-
-##### `tests/test_market_schedule.py` (24 tests)
- Market open/close logic
- Timezone handling (UTC, Asia/Seoul, America/New_York, etc.)
- DST (Daylight Saving Time) transitions
- Weekend handling and lunch break logic
- Multiple market filtering
- Next market open calculation
-
-##### `tests/test_db.py` (3 tests)
- Database initialization and table creation
- Trade logging with all fields (market, exchange_code, decision_id)
- Query and retrieval operations
-
-##### `tests/test_main.py` (37 tests)
- Trading loop orchestration
- Market iteration and stock processing
- Dashboard integration (`--dashboard` flag)
- Telegram command handler wiring
- Error handling and graceful shutdown
-
-#### Strategy & Playbook (v2)
-
-##### `tests/test_pre_market_planner.py` (37 tests)
- Pre-market playbook generation
- Gemini API integration for scenario creation
- Timeout handling and defensive playbook fallback
- Multi-market playbook generation
-
-##### `tests/test_scenario_engine.py` (44 tests)
- Scenario matching against live market data
- Confidence scoring and threshold filtering
- Multiple scenario type handling
- Edge cases (no match, partial match, expired scenarios)
-
-##### `tests/test_playbook_store.py` (23 tests)
- Playbook persistence to SQLite
- Date-based retrieval and market filtering
- Playbook status management (generated, active, expired)
- JSON serialization/deserialization
-
-##### `tests/test_strategy_models.py` (33 tests)
- Pydantic model validation for scenarios, playbooks, decisions
- Field constraints and default values
- Serialization round-trips
-
-#### Analysis & Scanning
-
-##### `tests/test_volatility.py` (24 tests)
- ATR and RSI calculation accuracy
- Volume surge ratio computation
- Momentum scoring
- Breakout/breakdown pattern detection
- Market scanner watchlist management
-
-##### `tests/test_smart_scanner.py` (13 tests)
- Python-first filtering pipeline
- RSI and volume ratio filter logic
- Candidate scoring and ranking
- Fallback to static watchlist
-
-#### Context & Memory
-
-##### `tests/test_context.py` (18 tests)
- L1-L7 layer storage and retrieval
- Context key-value CRUD operations
- Timeframe-based queries
- Layer metadata management
-
-##### `tests/test_context_scheduler.py` (5 tests)
- Periodic context aggregation scheduling
- Layer summarization triggers
-
-#### Evolution & Review
-
-##### `tests/test_evolution.py` (24 tests)
- Strategy optimization loop
- High-confidence losing trade analysis
- Generated strategy validation
-
-##### `tests/test_daily_review.py` (10 tests)
- End-of-day review generation
- Trade performance summarization
- Context layer (L6_DAILY) integration
-
-##### `tests/test_scorecard.py` (3 tests)
- Daily scorecard metrics calculation
- Win rate, P&L, confidence tracking
-
-#### Notifications & Commands
-
-##### `tests/test_telegram.py` (25 tests)
- Message sending and formatting
- Rate limiting (leaky bucket)
- Error handling (network timeout, invalid token)
- Auto-disable on missing credentials
- Notification types (trade, circuit breaker, fat-finger, market events)
-
-##### `tests/test_telegram_commands.py` (31 tests)
- 9 command handlers (/help, /status, /positions, /report, /scenarios, /review, /dashboard, /stop, /resume)
- Long polling and command dispatch
- Authorization filtering by chat_id
- Command response formatting
-
-#### Dashboard
-
-##### `tests/test_dashboard.py` (14 tests)
- FastAPI endpoint responses (8 API routes)
- Status, playbook, scorecard, performance, context, decisions, scenarios
- Query parameter handling (market, date, limit)
-
-#### Performance & Quality
-
-##### `tests/test_token_efficiency.py` (34 tests)
- Gemini token usage optimization
- Prompt size reduction verification
- Cache effectiveness
-
-##### `tests/test_latency_control.py` (30 tests)
- API call latency measurement
- Rate limiter timing accuracy
- Async operation overhead
-
-##### `tests/test_decision_logger.py` (9 tests)
- Decision audit trail completeness
- Context snapshot capture
- Outcome tracking (P&L, accuracy)
-
-##### `tests/test_data_integration.py` (38 tests)
- External data source integration
- News API, market data, economic calendar
- Error handling for API failures
-
-##### `tests/test_backup.py` (23 tests)
- Backup scheduler and execution
- Cloud storage (S3) upload
- Health monitoring
- Data export functionality
-
-## Coverage Requirements
-
-**Minimum coverage: 80%**
-
-Check coverage:
-```bash
-pytest -v --cov=src --cov-report=term-missing
-```
-
-**Note:** `main.py` has lower coverage as it contains the main loop which is tested via integration/manual testing.
-
-## Test Configuration
-
-### `pyproject.toml`
-```toml
-[tool.pytest.ini_options]
-asyncio_mode = "auto"
-testpaths = ["tests"]
-python_files = ["test_*.py"]
-```
-
-### `tests/conftest.py`
-```python
-@pytest.fixture
-def settings() -> Settings:
-    """Provide test settings with safe defaults."""
-    return Settings(
-        KIS_APP_KEY="test_key",
-        KIS_APP_SECRET="test_secret",
-        KIS_ACCOUNT_NO="12345678-01",
-        GEMINI_API_KEY="test_gemini_key",
-        MODE="paper",
-        DB_PATH=":memory:",  # In-memory SQLite
-        CONFIDENCE_THRESHOLD=80,
-        ENABLED_MARKETS="KR",
-    )
-```
-
-## Writing New Tests
-
-### Naming Convention
- Test files: `test_<module>.py`
- Test functions: `test_<feature>_<scenario>()`
- Use descriptive names that explain what is being tested
-
-### Good Test Example
-```python
-async def test_send_order_with_market_price(broker, settings):
-    """Market orders should use price=0 and ORD_DVSN='01'."""
-    # Arrange
-    stock_code = "005930"
-    order_type = "BUY"
-    quantity = 10
-
-    # Act
-    with patch.object(broker._session, 'post') as mock_post:
-        mock_post.return_value.__aenter__.return_value.status = 200
-        mock_post.return_value.__aenter__.return_value.json = AsyncMock(
-            return_value={"rt_cd": "0", "msg1": "OK"}
-        )
-
-        await broker.send_order(stock_code, order_type, quantity, price=0)
-
-    # Assert
-    call_args = mock_post.call_args
-    body = call_args.kwargs['json']
-    assert body['ORD_DVSN'] == '01'  # Market order
-    assert body['ORD_UNPR'] == '0'   # Price 0
-```
-
-### Test Checklist
- [ ] Test passes in isolation (`pytest tests/test_foo.py::test_bar -v`)
- [ ] Test has clear docstring explaining what it tests
- [ ] Arrange-Act-Assert structure
- [ ] Uses appropriate fixtures from conftest.py
- [ ] Mocks external dependencies (API calls, network)
- [ ] Tests edge cases and error conditions
- [ ] Doesn't rely on test execution order
-
-## Running Tests
+수집 기준:

 ```bash
-# All tests
-pytest -v
-
-# Specific file
-pytest tests/test_risk.py -v
-
-# Specific test
-pytest tests/test_brain.py::test_parse_valid_json -v
-
-# With coverage
-pytest -v --cov=src --cov-report=term-missing
-
-# Stop on first failure
-pytest -x
-
-# Verbose output with print statements
-pytest -v -s
+pytest --collect-only -q
+# 538 tests collected
 ```

-## CI/CD Integration
+V2 핵심 영역 테스트가 포함되어 있습니다.

-Tests run automatically on:
- Every commit to feature branches
- Every PR to main
- Scheduled daily runs
+- `tests/test_strategy_models.py`
+- `tests/test_pre_market_planner.py`
+- `tests/test_scenario_engine.py`
+- `tests/test_playbook_store.py`
+- `tests/test_context_scheduler.py`
+- `tests/test_daily_review.py`
+- `tests/test_scorecard.py`
+- `tests/test_dashboard.py`
+- `tests/test_main.py`

-**Blocking conditions:**
- Test failures → PR blocked
- Coverage < 80% → PR blocked (warning only for main.py)
+기존 핵심 영역 테스트도 유지됩니다.

-**Non-blocking:**
- `mypy --strict` errors (type hints encouraged but not enforced)
- `ruff check` warnings (must be acknowledged)
+- `tests/test_risk.py`: circuit breaker/fat-finger 안전장치 검증
+- `tests/test_broker.py`: KIS API 호출/에러 처리/인증 흐름 검증
+- `tests/test_brain.py`: Gemini 응답 파싱/신뢰도 게이트 검증
+- `tests/test_market_schedule.py`: 시장 오픈/클로즈/타임존 로직 검증
+
+## Required Checks
+
+```bash
+pytest -v --cov=src
+ruff check src/ tests/
+mypy src/ --strict
+```
+
+## FastAPI Note
+
+대시보드 테스트(`tests/test_dashboard.py`)는 `fastapi`가 환경에 없으면 skip될 수 있습니다.
+의도된 동작이며 CI/개발환경에서 의존성 설치 여부를 확인하세요.
+
+## Targeted Smoke Commands
+
+```bash
+# dashboard integration
+pytest -q tests/test_main.py -k "dashboard"
+
+# planner/scenario/review paths
+pytest -q tests/test_pre_market_planner.py tests/test_scenario_engine.py tests/test_daily_review.py
+
+# context rollup/scheduler
+pytest -q tests/test_context.py tests/test_context_scheduler.py
+```
+
+## Review Checklist (테스트 관점)
+
+- 플랜 항목별 테스트 존재 여부 확인
+- 시장 스코프 키(`*_KR`, `*_US`) 검증 확인
+- EOD 흐름(`aggregate_daily_from_trades`, `scorecard_{market}` 저장) 검증
+- decision outcome 연결(`decision_id`) 검증
+- 대시보드 API market filter 검증
--- a/docs/workflow.md
+++ b/docs/workflow.md
@@ -8,8 +8,9 @@
 2. **Create Feature Branch** — Branch from `main` using format `feature/issue-{N}-{short-description}`
   - After creating the branch, run `git pull origin main` and rebase to ensure the branch is up to date
 3. **Implement Changes** — Write code, tests, and documentation on the feature branch
-4. **Create Pull Request** — Submit PR to `main` branch referencing the issue number
-5. **Review & Merge** — After approval, merge via PR (squash or merge commit)
+4. **Sync Status Docs** — Before PR, update `README.md` and relevant `docs/*.md` so implementation status/gaps are explicit
+5. **Create Pull Request** — Submit PR to `main` branch referencing the issue number
+6. **Review & Merge** — After approval, merge via PR (squash or merge commit)

 **Never commit directly to `main`.** This policy applies to all changes, no exceptions.

--- a/scripts/morning_report.sh
+++ b/scripts/morning_report.sh
@@ -1,54 +0,0 @@
-#!/usr/bin/env bash
-# Morning summary for overnight run logs.
-
-set -euo pipefail
-
-LOG_DIR="${LOG_DIR:-data/overnight}"
-
-if [ ! -d "$LOG_DIR" ]; then
-    echo "로그 디렉터리가 없습니다: $LOG_DIR"
-    exit 1
-fi
-
-latest_run="$(ls -1t "$LOG_DIR"/run_*.log 2>/dev/null | head -n 1 || true)"
-latest_watchdog="$(ls -1t "$LOG_DIR"/watchdog_*.log 2>/dev/null | head -n 1 || true)"
-
-if [ -z "$latest_run" ]; then
-    echo "run 로그가 없습니다: $LOG_DIR/run_*.log"
-    exit 1
-fi
-
-echo "Overnight report"
-echo "- run log: $latest_run"
-if [ -n "$latest_watchdog" ]; then
-    echo "- watchdog log: $latest_watchdog"
-fi
-
-start_line="$(head -n 1 "$latest_run" || true)"
-end_line="$(tail -n 1 "$latest_run" || true)"
-
-info_count="$(rg -c '"level": "INFO"' "$latest_run" || true)"
-warn_count="$(rg -c '"level": "WARNING"' "$latest_run" || true)"
-error_count="$(rg -c '"level": "ERROR"' "$latest_run" || true)"
-critical_count="$(rg -c '"level": "CRITICAL"' "$latest_run" || true)"
-traceback_count="$(rg -c 'Traceback' "$latest_run" || true)"
-
-echo "- start: ${start_line:-N/A}"
-echo "- end:   ${end_line:-N/A}"
-echo "- INFO: ${info_count:-0}"
-echo "- WARNING: ${warn_count:-0}"
-echo "- ERROR: ${error_count:-0}"
-echo "- CRITICAL: ${critical_count:-0}"
-echo "- Traceback: ${traceback_count:-0}"
-
-if [ -n "$latest_watchdog" ]; then
-    watchdog_errors="$(rg -c '\[ERROR\]' "$latest_watchdog" || true)"
-    echo "- watchdog ERROR: ${watchdog_errors:-0}"
-    echo ""
-    echo "최근 watchdog 로그:"
-    tail -n 5 "$latest_watchdog" || true
-fi
-
-echo ""
-echo "최근 앱 로그:"
-tail -n 20 "$latest_run" || true
--- a/scripts/run_overnight.sh
+++ b/scripts/run_overnight.sh
@@ -1,87 +0,0 @@
-#!/usr/bin/env bash
-# Start The Ouroboros overnight with logs and watchdog.
-
-set -euo pipefail
-
-LOG_DIR="${LOG_DIR:-data/overnight}"
-CHECK_INTERVAL="${CHECK_INTERVAL:-30}"
-TMUX_AUTO="${TMUX_AUTO:-true}"
-TMUX_ATTACH="${TMUX_ATTACH:-true}"
-TMUX_SESSION_PREFIX="${TMUX_SESSION_PREFIX:-ouroboros_overnight}"
-
-if [ -z "${APP_CMD:-}" ]; then
-    if [ -x ".venv/bin/python" ]; then
-        PYTHON_BIN=".venv/bin/python"
-    elif command -v python3 >/dev/null 2>&1; then
-        PYTHON_BIN="python3"
-    elif command -v python >/dev/null 2>&1; then
-        PYTHON_BIN="python"
-    else
-        echo ".venv/bin/python 또는 python3/python 실행 파일을 찾을 수 없습니다."
-        exit 1
-    fi
-
-    dashboard_port="${DASHBOARD_PORT:-8080}"
-
-    APP_CMD="DASHBOARD_PORT=$dashboard_port $PYTHON_BIN -m src.main --mode=paper --dashboard"
-fi
-
-mkdir -p "$LOG_DIR"
-
-timestamp="$(date +"%Y%m%d_%H%M%S")"
-RUN_LOG="$LOG_DIR/run_${timestamp}.log"
-WATCHDOG_LOG="$LOG_DIR/watchdog_${timestamp}.log"
-PID_FILE="$LOG_DIR/app.pid"
-WATCHDOG_PID_FILE="$LOG_DIR/watchdog.pid"
-
-if [ -f "$PID_FILE" ]; then
-    old_pid="$(cat "$PID_FILE" || true)"
-    if [ -n "$old_pid" ] && kill -0 "$old_pid" 2>/dev/null; then
-        echo "앱이 이미 실행 중입니다. pid=$old_pid"
-        exit 1
-    fi
-fi
-
-echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] starting: $APP_CMD" | tee -a "$RUN_LOG"
-nohup bash -lc "$APP_CMD" >>"$RUN_LOG" 2>&1 &
-app_pid=$!
-echo "$app_pid" > "$PID_FILE"
-
-echo "[$(date -u +"%Y-%m-%dT%H:%M:%SZ")] app pid=$app_pid" | tee -a "$RUN_LOG"
-
-nohup env PID_FILE="$PID_FILE" LOG_FILE="$WATCHDOG_LOG" CHECK_INTERVAL="$CHECK_INTERVAL" \
-    bash scripts/watchdog.sh >/dev/null 2>&1 &
-watchdog_pid=$!
-echo "$watchdog_pid" > "$WATCHDOG_PID_FILE"
-
-cat <<EOF
-시작 완료
- app pid: $app_pid
- watchdog pid: $watchdog_pid
- app log: $RUN_LOG
- watchdog log: $WATCHDOG_LOG
-
-실시간 확인:
-tail -f "$RUN_LOG"
-tail -f "$WATCHDOG_LOG"
-EOF
-
-if [ "$TMUX_AUTO" = "true" ]; then
-    if ! command -v tmux >/dev/null 2>&1; then
-        echo "tmux를 찾지 못해 자동 세션 생성은 건너뜁니다."
-        exit 0
-    fi
-
-    session_name="${TMUX_SESSION_PREFIX}_${timestamp}"
-    window_name="overnight"
-    tmux new-session -d -s "$session_name" -n "$window_name" "tail -f '$RUN_LOG'"
-    tmux split-window -t "${session_name}:${window_name}" -v "tail -f '$WATCHDOG_LOG'"
-    tmux select-layout -t "${session_name}:${window_name}" even-vertical
-
-    echo "tmux session 생성: $session_name"
-    echo "수동 접속: tmux attach -t $session_name"
-
-    if [ -z "${TMUX:-}" ] && [ "$TMUX_ATTACH" = "true" ]; then
-        tmux attach -t "$session_name"
-    fi
-fi
--- a/scripts/stop_overnight.sh
+++ b/scripts/stop_overnight.sh
@@ -1,76 +0,0 @@
-#!/usr/bin/env bash
-# Stop The Ouroboros overnight app/watchdog/tmux session.
-
-set -euo pipefail
-
-LOG_DIR="${LOG_DIR:-data/overnight}"
-PID_FILE="$LOG_DIR/app.pid"
-WATCHDOG_PID_FILE="$LOG_DIR/watchdog.pid"
-TMUX_SESSION_PREFIX="${TMUX_SESSION_PREFIX:-ouroboros_overnight}"
-KILL_TIMEOUT="${KILL_TIMEOUT:-5}"
-
-stop_pid() {
-    local name="$1"
-    local pid="$2"
-
-    if [ -z "$pid" ]; then
-        echo "$name PID가 비어 있습니다."
-        return 1
-    fi
-
-    if ! kill -0 "$pid" 2>/dev/null; then
-        echo "$name 프로세스가 이미 종료됨 (pid=$pid)"
-        return 0
-    fi
-
-    kill "$pid" 2>/dev/null || true
-    for _ in $(seq 1 "$KILL_TIMEOUT"); do
-        if ! kill -0 "$pid" 2>/dev/null; then
-            echo "$name 종료됨 (pid=$pid)"
-            return 0
-        fi
-        sleep 1
-    done
-
-    kill -9 "$pid" 2>/dev/null || true
-    if ! kill -0 "$pid" 2>/dev/null; then
-        echo "$name 강제 종료됨 (pid=$pid)"
-        return 0
-    fi
-
-    echo "$name 종료 실패 (pid=$pid)"
-    return 1
-}
-
-status=0
-
-if [ -f "$WATCHDOG_PID_FILE" ]; then
-    watchdog_pid="$(cat "$WATCHDOG_PID_FILE" || true)"
-    stop_pid "watchdog" "$watchdog_pid" || status=1
-    rm -f "$WATCHDOG_PID_FILE"
-else
-    echo "watchdog pid 파일 없음: $WATCHDOG_PID_FILE"
-fi
-
-if [ -f "$PID_FILE" ]; then
-    app_pid="$(cat "$PID_FILE" || true)"
-    stop_pid "app" "$app_pid" || status=1
-    rm -f "$PID_FILE"
-else
-    echo "app pid 파일 없음: $PID_FILE"
-fi
-
-if command -v tmux >/dev/null 2>&1; then
-    sessions="$(tmux ls 2>/dev/null | awk -F: -v p="$TMUX_SESSION_PREFIX" '$1 ~ "^" p "_" {print $1}')"
-    if [ -n "$sessions" ]; then
-        while IFS= read -r s; do
-            [ -z "$s" ] && continue
-            tmux kill-session -t "$s" 2>/dev/null || true
-            echo "tmux 세션 종료: $s"
-        done <<< "$sessions"
-    else
-        echo "종료할 tmux 세션 없음 (prefix=${TMUX_SESSION_PREFIX}_)"
-    fi
-fi
-
-exit "$status"
--- a/scripts/watchdog.sh
+++ b/scripts/watchdog.sh
@@ -1,42 +0,0 @@
-#!/usr/bin/env bash
-# Simple watchdog for The Ouroboros process.
-
-set -euo pipefail
-
-PID_FILE="${PID_FILE:-data/overnight/app.pid}"
-LOG_FILE="${LOG_FILE:-data/overnight/watchdog.log}"
-CHECK_INTERVAL="${CHECK_INTERVAL:-30}"
-STATUS_EVERY="${STATUS_EVERY:-10}"
-
-mkdir -p "$(dirname "$LOG_FILE")"
-
-log() {
-    printf '%s %s\n' "$(date -u +"%Y-%m-%dT%H:%M:%SZ")" "$1" | tee -a "$LOG_FILE"
-}
-
-if [ ! -f "$PID_FILE" ]; then
-    log "[ERROR] pid file not found: $PID_FILE"
-    exit 1
-fi
-
-PID="$(cat "$PID_FILE")"
-if [ -z "$PID" ]; then
-    log "[ERROR] pid file is empty: $PID_FILE"
-    exit 1
-fi
-
-log "[INFO] watchdog started (pid=$PID, interval=${CHECK_INTERVAL}s)"
-
-count=0
-while true; do
-    if kill -0 "$PID" 2>/dev/null; then
-        count=$((count + 1))
-        if [ $((count % STATUS_EVERY)) -eq 0 ]; then
-            log "[INFO] process alive (pid=$PID)"
-        fi
-    else
-        log "[ERROR] process stopped (pid=$PID)"
-        exit 1
-    fi
-    sleep "$CHECK_INTERVAL"
-done
--- a/src/analysis/smart_scanner.py
+++ b/src/analysis/smart_scanner.py
@@ -1,4 +1,8 @@
-"""Smart Volatility Scanner with volatility-first market ranking logic."""
+"""Smart Volatility Scanner with RSI and volume filters.
+
+Fetches market rankings from KIS API and applies technical filters
+to identify high-probability trading candidates.
+"""

 from __future__ import annotations

@@ -8,9 +12,7 @@ from typing import Any

 from src.analysis.volatility import VolatilityAnalyzer
 from src.broker.kis_api import KISBroker
-from src.broker.overseas import OverseasBroker
 from src.config import Settings
-from src.markets.schedule import MarketInfo

 logger = logging.getLogger(__name__)

@@ -30,19 +32,19 @@ class ScanCandidate:


 class SmartVolatilityScanner:
-    """Scans market rankings and applies volatility-first filters.
+    """Scans market rankings and applies RSI/volume filters.

    Flow:
-    1. Fetch fluctuation rankings as primary universe
-    2. Fetch volume rankings for liquidity bonus
-    3. Score by volatility first, liquidity second
-    4. Return top N qualified candidates
+    1. Fetch volume rankings from KIS API
+    2. For each ranked stock, fetch daily prices
+    3. Calculate RSI and volume ratio
+    4. Apply filters: volume > VOL_MULTIPLIER AND (RSI < 30 OR RSI > 70)
+    5. Return top N qualified candidates
    """

    def __init__(
        self,
        broker: KISBroker,
-        overseas_broker: OverseasBroker | None,
        volatility_analyzer: VolatilityAnalyzer,
        settings: Settings,
    ) -> None:
@@ -54,7 +56,6 @@ class SmartVolatilityScanner:
            settings: Application settings
        """
        self.broker = broker
-        self.overseas_broker = overseas_broker
        self.analyzer = volatility_analyzer
        self.settings = settings

@@ -66,129 +67,107 @@ class SmartVolatilityScanner:

    async def scan(
        self,
-        market: MarketInfo | None = None,
        fallback_stocks: list[str] | None = None,
    ) -> list[ScanCandidate]:
        """Execute smart scan and return qualified candidates.

        Args:
-            market: Target market info (domestic vs overseas behavior)
            fallback_stocks: Stock codes to use if ranking API fails

        Returns:
            List of ScanCandidate, sorted by score, up to top_n items
        """
-        if market and not market.is_domestic:
-            return await self._scan_overseas(market, fallback_stocks)
-
-        return await self._scan_domestic(fallback_stocks)
-
-    async def _scan_domestic(
-        self,
-        fallback_stocks: list[str] | None = None,
-    ) -> list[ScanCandidate]:
-        """Scan domestic market using volatility-first ranking + liquidity bonus."""
-        # 1) Primary universe from fluctuation ranking.
+        # Step 1: Fetch rankings
        try:
-            fluct_rows = await self.broker.fetch_market_rankings(
-                ranking_type="fluctuation",
-                limit=50,
-            )
-        except ConnectionError as exc:
-            logger.warning("Domestic fluctuation ranking failed: %s", exc)
-            fluct_rows = []
-
-        # 2) Liquidity bonus from volume ranking.
-        try:
-            volume_rows = await self.broker.fetch_market_rankings(
+            rankings = await self.broker.fetch_market_rankings(
                ranking_type="volume",
-                limit=50,
+                limit=30,  # Fetch more than needed for filtering
            )
+            logger.info("Fetched %d stocks from volume rankings", len(rankings))
        except ConnectionError as exc:
-            logger.warning("Domestic volume ranking failed: %s", exc)
-            volume_rows = []
-
-        if not fluct_rows and fallback_stocks:
-            logger.info(
-                "Domestic ranking unavailable; using fallback symbols (%d)",
-                len(fallback_stocks),
-            )
-            fluct_rows = [
-                {
-                    "stock_code": code,
-                    "name": code,
-                    "price": 0.0,
-                    "volume": 0.0,
-                    "change_rate": 0.0,
-                    "volume_increase_rate": 0.0,
-                }
-                for code in fallback_stocks
-            ]
-
-        if not fluct_rows:
-            return []
-
-        volume_rank_bonus: dict[str, float] = {}
-        for idx, row in enumerate(volume_rows):
-            code = _extract_stock_code(row)
-            if not code:
-                continue
-            volume_rank_bonus[code] = max(0.0, 15.0 - idx * 0.3)
+            logger.warning("Ranking API failed, using fallback: %s", exc)
+            if fallback_stocks:
+                # Create minimal ranking data for fallback
+                rankings = [
+                    {
+                        "stock_code": code,
+                        "name": code,
+                        "price": 0,
+                        "volume": 0,
+                        "change_rate": 0,
+                        "volume_increase_rate": 0,
+                    }
+                    for code in fallback_stocks
+                ]
+            else:
+                return []

+        # Step 2: Analyze each stock
        candidates: list[ScanCandidate] = []
-        for stock in fluct_rows:
-            stock_code = _extract_stock_code(stock)
+
+        for stock in rankings:
+            stock_code = stock["stock_code"]
            if not stock_code:
                continue

            try:
-                price = _extract_last_price(stock)
-                change_rate = _extract_change_rate_pct(stock)
-                volume = _extract_volume(stock)
+                # Fetch daily prices for RSI calculation
+                daily_prices = await self.broker.get_daily_prices(stock_code, days=20)

-                intraday_range_pct = 0.0
-                volume_ratio = _safe_float(stock.get("volume_increase_rate"), 0.0) / 100.0 + 1.0
-
-                # Use daily chart to refine range/volume when available.
-                daily_prices = await self.broker.get_daily_prices(stock_code, days=2)
-                if daily_prices:
-                    latest = daily_prices[-1]
-                    latest_close = _safe_float(latest.get("close"), default=price)
-                    if price <= 0:
-                        price = latest_close
-                    latest_high = _safe_float(latest.get("high"))
-                    latest_low = _safe_float(latest.get("low"))
-                    if latest_close > 0 and latest_high > 0 and latest_low > 0 and latest_high >= latest_low:
-                        intraday_range_pct = (latest_high - latest_low) / latest_close * 100.0
-                    if volume <= 0:
-                        volume = _safe_float(latest.get("volume"))
-                    if len(daily_prices) >= 2:
-                        prev_day_volume = _safe_float(daily_prices[-2].get("volume"))
-                        if prev_day_volume > 0:
-                            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 len(daily_prices) < 15:  # Need at least 14+1 for RSI
+                    logger.debug("Insufficient price history for %s", stock_code)
                    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 * 4.0)))
+                # Calculate RSI
+                close_prices = [p["close"] for p in daily_prices]
+                rsi = self.analyzer.calculate_rsi(close_prices, period=14)

-                candidates.append(
-                    ScanCandidate(
-                        stock_code=stock_code,
-                        name=stock.get("name", stock_code),
-                        price=price,
-                        volume=volume,
-                        volume_ratio=max(1.0, volume_ratio, volatility_pct / 2.0),
-                        rsi=implied_rsi,
-                        signal=signal,
-                        score=score,
+                # Calculate volume ratio (today vs previous day avg)
+                if len(daily_prices) >= 2:
+                    prev_day_volume = daily_prices[-2]["volume"]
+                    current_volume = stock.get("volume", 0) or daily_prices[-1]["volume"]
+                    volume_ratio = (
+                        current_volume / prev_day_volume if prev_day_volume > 0 else 1.0
+                    )
+                else:
+                    volume_ratio = stock.get("volume_increase_rate", 0) / 100 + 1  # Fallback
+
+                # Apply filters
+                volume_qualified = volume_ratio >= self.vol_multiplier
+                rsi_oversold = rsi < self.rsi_oversold
+                rsi_momentum = rsi > self.rsi_momentum
+
+                if volume_qualified and (rsi_oversold or rsi_momentum):
+                    signal = "oversold" if rsi_oversold else "momentum"
+
+                    # Calculate composite score
+                    # Higher score for: extreme RSI + high volume
+                    rsi_extremity = abs(rsi - 50) / 50  # 0-1 scale
+                    volume_score = min(volume_ratio / 5, 1.0)  # Cap at 5x
+                    score = (rsi_extremity * 0.6 + volume_score * 0.4) * 100
+
+                    candidates.append(
+                        ScanCandidate(
+                            stock_code=stock_code,
+                            name=stock.get("name", stock_code),
+                            price=stock.get("price", daily_prices[-1]["close"]),
+                            volume=current_volume,
+                            volume_ratio=volume_ratio,
+                            rsi=rsi,
+                            signal=signal,
+                            score=score,
+                        )
+                    )
+
+                    logger.info(
+                        "Qualified: %s (%s) RSI=%.1f vol=%.1fx signal=%s score=%.1f",
+                        stock_code,
+                        stock.get("name", ""),
+                        rsi,
+                        volume_ratio,
+                        signal,
+                        score,
                    )
-                )

            except ConnectionError as exc:
                logger.warning("Failed to analyze %s: %s", stock_code, exc)
@@ -197,171 +176,10 @@ class SmartVolatilityScanner:
                logger.error("Unexpected error analyzing %s: %s", stock_code, exc)
                continue

-        logger.info("Domestic ranking scan found %d candidates", len(candidates))
+        # Sort by score and return top N
        candidates.sort(key=lambda c: c.score, reverse=True)
        return candidates[: self.top_n]

-    async def _scan_overseas(
-        self,
-        market: MarketInfo,
-        fallback_stocks: list[str] | None = None,
-    ) -> list[ScanCandidate]:
-        """Scan overseas symbols using ranking API first, then fallback universe."""
-        if self.overseas_broker is None:
-            logger.warning(
-                "Overseas scanner unavailable for %s: overseas broker not configured",
-                market.name,
-            )
-            return []
-
-        candidates = await self._scan_overseas_from_rankings(market)
-        if not candidates:
-            candidates = await self._scan_overseas_from_symbols(market, fallback_stocks)
-
-        candidates.sort(key=lambda c: c.score, reverse=True)
-        return candidates[: self.top_n]
-
-    async def _scan_overseas_from_rankings(
-        self,
-        market: MarketInfo,
-    ) -> list[ScanCandidate]:
-        """Build overseas candidates from ranking APIs using volatility-first scoring."""
-        assert self.overseas_broker is not None
-        try:
-            fluct_rows = await self.overseas_broker.fetch_overseas_rankings(
-                exchange_code=market.exchange_code,
-                ranking_type="fluctuation",
-                limit=50,
-            )
-        except Exception as exc:
-            logger.warning(
-                "Overseas fluctuation ranking failed for %s: %s", market.code, exc
-            )
-            fluct_rows = []
-
-        if not fluct_rows:
-            return []
-
-        volume_rank_bonus: dict[str, float] = {}
-        try:
-            volume_rows = await self.overseas_broker.fetch_overseas_rankings(
-                exchange_code=market.exchange_code,
-                ranking_type="volume",
-                limit=50,
-            )
-        except Exception as exc:
-            logger.warning(
-                "Overseas volume ranking failed for %s: %s", market.code, exc
-            )
-            volume_rows = []
-
-        for idx, row in enumerate(volume_rows):
-            code = _extract_stock_code(row)
-            if not code:
-                continue
-            # Top-ranked by traded value/volume gets higher liquidity bonus.
-            volume_rank_bonus[code] = max(0.0, 15.0 - idx * 0.3)
-
-        candidates: list[ScanCandidate] = []
-        for row in fluct_rows:
-            stock_code = _extract_stock_code(row)
-            if not stock_code:
-                continue
-
-            price = _extract_last_price(row)
-            change_rate = _extract_change_rate_pct(row)
-            volume = _extract_volume(row)
-            intraday_range_pct = _extract_intraday_range_pct(row, price)
-            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:
-                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 * 4.0)))
-            candidates.append(
-                ScanCandidate(
-                    stock_code=stock_code,
-                    name=str(row.get("name") or row.get("ovrs_item_name") or stock_code),
-                    price=price,
-                    volume=volume,
-                    volume_ratio=max(1.0, volatility_pct / 2.0),
-                    rsi=implied_rsi,
-                    signal=signal,
-                    score=score,
-                )
-            )
-
-        if candidates:
-            logger.info(
-                "Overseas ranking scan found %d candidates for %s",
-                len(candidates),
-                market.name,
-            )
-        return candidates
-
-    async def _scan_overseas_from_symbols(
-        self,
-        market: MarketInfo,
-        symbols: list[str] | None,
-    ) -> list[ScanCandidate]:
-        """Fallback overseas scan from dynamic symbol universe."""
-        assert self.overseas_broker is not None
-        if not symbols:
-            logger.info("Overseas scanner: no symbol universe for %s", market.name)
-            return []
-
-        logger.info(
-            "Overseas scanner: scanning %d fallback symbols for %s",
-            len(symbols),
-            market.name,
-        )
-        candidates: list[ScanCandidate] = []
-        for stock_code in symbols:
-            try:
-                price_data = await self.overseas_broker.get_overseas_price(
-                    market.exchange_code, stock_code
-                )
-                output = price_data.get("output", {})
-                price = _extract_last_price(output)
-                change_rate = _extract_change_rate_pct(output)
-                volume = _extract_volume(output)
-                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:
-                    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 * 4.0)))
-                candidates.append(
-                    ScanCandidate(
-                        stock_code=stock_code,
-                        name=stock_code,
-                        price=price,
-                        volume=volume,
-                        volume_ratio=max(1.0, volatility_pct / 2.0),
-                        rsi=implied_rsi,
-                        signal=signal,
-                        score=score,
-                    )
-                )
-            except ConnectionError as exc:
-                logger.warning("Failed to analyze overseas %s: %s", stock_code, exc)
-            except Exception as exc:
-                logger.error("Unexpected error analyzing overseas %s: %s", stock_code, exc)
-        logger.info(
-            "Overseas symbol fallback scan found %d candidates for %s",
-            len(candidates),
-            market.name,
-        )
-        return candidates
-
    def get_stock_codes(self, candidates: list[ScanCandidate]) -> list[str]:
        """Extract stock codes from candidates for watchlist update.

@@ -372,78 +190,3 @@ class SmartVolatilityScanner:
            List of stock codes
        """
        return [c.stock_code for c in candidates]
-
-
-def _safe_float(value: Any, default: float = 0.0) -> float:
-    """Convert arbitrary values to float safely."""
-    if value in (None, ""):
-        return default
-    try:
-        return float(value)
-    except (TypeError, ValueError):
-        return default
-
-
-def _extract_stock_code(row: dict[str, Any]) -> str:
-    """Extract normalized stock code from various API schemas."""
-    return (
-        str(
-            row.get("symb")
-            or row.get("ovrs_pdno")
-            or row.get("stock_code")
-            or row.get("pdno")
-            or ""
-        )
-        .strip()
-        .upper()
-    )
-
-
-def _extract_last_price(row: dict[str, Any]) -> float:
-    """Extract last/close-like price from API schema variants."""
-    return _safe_float(
-        row.get("last")
-        or row.get("ovrs_nmix_prpr")
-        or row.get("stck_prpr")
-        or row.get("price")
-        or row.get("close")
-    )
-
-
-def _extract_change_rate_pct(row: dict[str, Any]) -> float:
-    """Extract daily change rate (%) from API schema variants."""
-    return _safe_float(
-        row.get("rate")
-        or row.get("change_rate")
-        or row.get("prdy_ctrt")
-        or row.get("evlu_pfls_rt")
-        or row.get("chg_rt")
-    )
-
-
-def _extract_volume(row: dict[str, Any]) -> float:
-    """Extract volume/traded-amount proxy from schema variants."""
-    return _safe_float(
-        row.get("tvol") or row.get("acml_vol") or row.get("vol") or row.get("volume")
-    )
-
-
-def _extract_intraday_range_pct(row: dict[str, Any], price: float) -> float:
-    """Estimate intraday range percentage from high/low fields."""
-    if price <= 0:
-        return 0.0
-    high = _safe_float(
-        row.get("high")
-        or row.get("ovrs_hgpr")
-        or row.get("stck_hgpr")
-        or row.get("day_hgpr")
-    )
-    low = _safe_float(
-        row.get("low")
-        or row.get("ovrs_lwpr")
-        or row.get("stck_lwpr")
-        or row.get("day_lwpr")
-    )
-    if high <= 0 or low <= 0 or high < low:
-        return 0.0
-    return (high - low) / price * 100.0
--- a/src/brain/gemini_client.py
+++ b/src/brain/gemini_client.py
@@ -410,10 +410,8 @@ class GeminiClient:
                    cached=True,
                )

-        # Build prompt (prompt_override takes priority for callers like pre_market_planner)
-        if "prompt_override" in market_data:
-            prompt = market_data["prompt_override"]
-        elif self._enable_optimization:
+        # Build optimized prompt
+        if self._enable_optimization:
            prompt = self._optimizer.build_compressed_prompt(market_data)
        else:
            prompt = await self.build_prompt(market_data, news_sentiment)
--- a/src/broker/kis_api.py
+++ b/src/broker/kis_api.py
@@ -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."""

@@ -137,14 +104,12 @@ class KISBroker:
            time_since_last_attempt = now - self._last_refresh_attempt
            if time_since_last_attempt < self._refresh_cooldown:
                remaining = self._refresh_cooldown - time_since_last_attempt
-                # Do not fail fast here. If token is unavailable, upstream calls
-                # will all fail for up to a minute and scanning returns no trades.
-                logger.warning(
-                    "Token refresh on cooldown. Waiting %.1fs before retry (KIS allows 1/minute)",
-                    remaining,
+                error_msg = (
+                    f"Token refresh on cooldown. "
+                    f"Retry in {remaining:.1f}s (KIS allows 1/minute)"
                )
-                await asyncio.sleep(remaining)
-                now = asyncio.get_event_loop().time()
+                logger.warning(error_msg)
+                raise ConnectionError(error_msg)

            logger.info("Refreshing KIS access token")
            self._last_refresh_attempt = now
@@ -231,55 +196,6 @@ 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()
@@ -331,23 +247,13 @@ class KISBroker:
        session = self._get_session()

        tr_id = "VTTC0802U" if order_type == "BUY" else "VTTC0801U"
-
-        # 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)
@@ -396,46 +302,26 @@ class KISBroker:
        await self._rate_limiter.acquire()
        session = self._get_session()

-        if ranking_type == "volume":
-            # 거래량순위: FHPST01710000 / /quotations/volume-rank
-            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": "0000",
-                "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",
-            }
-
+        # TR_ID for volume ranking
+        tr_id = "FHPST01710000" if ranking_type == "volume" else "FHPST01710100"
        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:
--- a/src/broker/overseas.py
+++ b/src/broker/overseas.py
@@ -12,24 +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
-
-
 class OverseasBroker:
    """KIS Overseas Stock API wrapper that reuses KISBroker infrastructure."""

@@ -62,11 +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"
@@ -84,81 +64,6 @@ class OverseasBroker:
                f"Network error fetching overseas price: {exc}"
            ) from exc

-    async def fetch_overseas_rankings(
-        self,
-        exchange_code: str,
-        ranking_type: str = "fluctuation",
-        limit: int = 30,
-    ) -> list[dict[str, Any]]:
-        """Fetch overseas rankings (price change or volume surge).
-
-        Ranking API specs may differ by account/product. Endpoint paths and
-        TR_IDs are configurable via settings and can be overridden in .env.
-        """
-        if not self._broker._settings.OVERSEAS_RANKING_ENABLED:
-            return []
-
-        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
-            path = self._broker._settings.OVERSEAS_RANKING_VOLUME_PATH
-            params: dict[str, str] = {
-                "AUTH": "",
-                "EXCD": ranking_excd,
-                "MIXN": "0",
-                "VOL_RANG": "0",
-            }
-        else:
-            tr_id = self._broker._settings.OVERSEAS_RANKING_FLUCT_TR_ID
-            path = self._broker._settings.OVERSEAS_RANKING_FLUCT_PATH
-            params = {
-                "AUTH": "",
-                "EXCD": ranking_excd,
-                "NDAY": "0",
-                "GUBN": "1",
-                "VOL_RANG": "0",
-            }
-
-        headers = await self._broker._auth_headers(tr_id)
-        url = f"{self._broker._base_url}{path}"
-
-        try:
-            async with session.get(url, headers=headers, params=params) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    if resp.status == 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 ({resp.status}): {text}"
-                    )
-
-                data = await resp.json()
-                rows = self._extract_ranking_rows(data)
-                if rows:
-                    return rows[:limit]
-
-                logger.debug(
-                    "Overseas ranking returned empty for %s/%s (keys=%s)",
-                    exchange_code,
-                    ranking_type,
-                    list(data.keys()),
-                )
-                return []
-        except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
-                f"Network error fetching overseas rankings: {exc}"
-            ) from exc
-
    async def get_overseas_balance(self, exchange_code: str) -> dict[str, Any]:
        """
        Fetch overseas account balance.
@@ -257,27 +162,14 @@ class OverseasBroker:
                        f"send_overseas_order failed ({resp.status}): {text}"
                    )
                data = await resp.json()
-                rt_cd = data.get("rt_cd", "")
-                msg1 = data.get("msg1", "")
-                if rt_cd == "0":
-                    logger.info(
-                        "Overseas order submitted",
-                        extra={
-                            "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,
-                    )
+                logger.info(
+                    "Overseas order submitted",
+                    extra={
+                        "exchange": exchange_code,
+                        "stock_code": stock_code,
+                        "action": order_type,
+                    },
+                )
                return data
        except (TimeoutError, aiohttp.ClientError) as exc:
            raise ConnectionError(
@@ -306,11 +198,3 @@ class OverseasBroker:
            "HSX": "VND",
        }
        return currency_map.get(exchange_code, "USD")
-
-    def _extract_ranking_rows(self, data: dict[str, Any]) -> list[dict[str, Any]]:
-        """Extract list rows from ranking response across schema variants."""
-        candidates = [data.get("output"), data.get("output1"), data.get("output2")]
-        for value in candidates:
-            if isinstance(value, list):
-                return [row for row in value if isinstance(row, dict)]
-        return []
--- a/src/config.py
+++ b/src/config.py
@@ -38,11 +38,6 @@ class Settings(BaseSettings):
    RSI_MOMENTUM_THRESHOLD: int = Field(default=70, ge=50, le=100)
    VOL_MULTIPLIER: float = Field(default=2.0, gt=1.0, le=10.0)
    SCANNER_TOP_N: int = Field(default=3, ge=1, le=10)
-    POSITION_SIZING_ENABLED: bool = True
-    POSITION_BASE_ALLOCATION_PCT: float = Field(default=5.0, gt=0.0, le=30.0)
-    POSITION_MIN_ALLOCATION_PCT: float = Field(default=1.0, gt=0.0, le=20.0)
-    POSITION_MAX_ALLOCATION_PCT: float = Field(default=10.0, gt=0.0, le=50.0)
-    POSITION_VOLATILITY_TARGET_SCORE: float = Field(default=50.0, gt=0.0, le=100.0)

    # Database
    DB_PATH: str = "data/trade_logs.db"
@@ -55,11 +50,6 @@ 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)
@@ -93,28 +83,6 @@ 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_VOLUME_TR_ID: str = "HHDFS76270000"
-    OVERSEAS_RANKING_FLUCT_PATH: str = (
-        "/uapi/overseas-stock/v1/ranking/updown-rate"
-    )
-    OVERSEAS_RANKING_VOLUME_PATH: str = (
-        "/uapi/overseas-stock/v1/ranking/volume-surge"
-    )
-
    # Dashboard (optional)
    DASHBOARD_ENABLED: bool = False
    DASHBOARD_HOST: str = "127.0.0.1"
@@ -133,7 +101,4 @@ class Settings(BaseSettings):
    @property
    def enabled_market_list(self) -> list[str]:
        """Parse ENABLED_MARKETS into list of market codes."""
-        from src.markets.schedule import expand_market_codes
-
-        raw = [m.strip() for m in self.ENABLED_MARKETS.split(",") if m.strip()]
-        return expand_market_codes(raw)
+        return [m.strip() for m in self.ENABLED_MARKETS.split(",") if m.strip()]
--- a/src/dashboard/app.py
+++ b/src/dashboard/app.py
@@ -26,19 +26,7 @@ def create_dashboard_app(db_path: str) -> FastAPI:
    def get_status() -> dict[str, Any]:
        today = datetime.now(UTC).date().isoformat()
        with _connect(db_path) as conn:
-            market_rows = conn.execute(
-                """
-                SELECT DISTINCT market FROM (
-                    SELECT market FROM trades WHERE DATE(timestamp) = ?
-                    UNION
-                    SELECT market FROM decision_logs WHERE DATE(timestamp) = ?
-                    UNION
-                    SELECT market FROM playbooks WHERE date = ?
-                ) ORDER BY market
-                """,
-                (today, today, today),
-            ).fetchall()
-            markets = [row[0] for row in market_rows] if market_rows else []
+            markets = ["KR", "US"]
            market_status: dict[str, Any] = {}
            total_trades = 0
            total_pnl = 0.0
@@ -259,50 +247,6 @@ def create_dashboard_app(db_path: str) -> 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"),
--- 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;
@@ -12,390 +11,51 @@
        --fg: #e6eef7;
        --muted: #9fb3c8;
        --accent: #3cb371;
-        --red: #e05555;
-        --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; }
-
-      /* Header */
-      header {
-        display: flex;
-        align-items: center;
-        justify-content: space-between;
-        margin-bottom: 20px;
-        padding-bottom: 12px;
-        border-bottom: 1px solid var(--border);
+      .wrap {
+        max-width: 900px;
+        margin: 48px auto;
+        padding: 0 16px;
      }
-      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); }
-
-      /* 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);
-        border: 1px solid var(--border);
-        border-radius: 10px;
-        padding: 16px;
+        background: color-mix(in oklab, var(--panel), black 12%);
+        border: 1px solid #28455f;
+        border-radius: 12px;
+        padding: 20px;
      }
-      .card-label { color: var(--muted); font-size: 11px; margin-bottom: 6px; text-transform: uppercase; letter-spacing: 0.5px; }
-      .card-value { font-size: 22px; font-weight: 700; }
-      .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;
+      h1 {
+        margin-top: 0;
      }
-      .panel-header {
-        display: flex;
-        align-items: center;
-        justify-content: space-between;
-        margin-bottom: 16px;
+      code {
+        color: var(--accent);
      }
-      .panel-title { font-size: 13px; color: var(--muted); font-weight: 600; }
-      .chart-container { position: relative; height: 180px; }
-      .chart-error { color: var(--muted); text-align: center; padding: 40px 0; font-size: 12px; }
-
-      /* 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;
+      li {
+        margin: 6px 0;
+        color: var(--muted);
      }
-      .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; }
-
-      /* 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); } }
    </style>
  </head>
  <body>
    <div class="wrap">
-      <!-- Header -->
-      <header>
-        <h1>&#x1F40D; The Ouroboros</h1>
-        <div class="header-right">
-          <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>
-
-      <!-- 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 class="card">
+        <h1>The Ouroboros Dashboard API</h1>
+        <p>Use the following endpoints:</p>
+        <ul>
+          <li><code>/api/status</code></li>
+          <li><code>/api/playbook/{date}?market=KR</code></li>
+          <li><code>/api/scorecard/{date}?market=KR</code></li>
+          <li><code>/api/performance?market=all</code></li>
+          <li><code>/api/context/{layer}</code></li>
+          <li><code>/api/decisions?market=KR</code></li>
+          <li><code>/api/scenarios/active?market=US</code></li>
+        </ul>
      </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>`;
-      }
-
-      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 ${t.decision_count ?? 0}건`;
-        } catch {}
-      }
-
-      async function fetchPerformance() {
-        try {
-          const r = await fetch('/api/performance?market=all');
-          if (!r.ok) return;
-          const d = await r.json();
-          const c = d.combined || {};
-          document.getElementById('card-winrate').textContent = c.win_rate !== undefined ? `${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);
-      }
-
-      async function refreshAll() {
-        document.getElementById('last-updated').textContent = '업데이트 중...';
-        await Promise.all([
-          fetchStatus(),
-          fetchPerformance(),
-          fetchPnlHistory(currentDays),
-          fetchDecisions(currentMarket),
-        ]);
-        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
@@ -214,42 +214,3 @@ def get_latest_buy_trade(
    if not row:
        return None
    return {"decision_id": row[0], "price": row[1], "quantity": row[2]}
-
-
-def get_open_position(
-    conn: sqlite3.Connection, stock_code: str, market: str
-) -> dict[str, Any] | None:
-    """Return open position if latest trade is BUY, else None."""
-    cursor = conn.execute(
-        """
-        SELECT action, decision_id, price, quantity
-        FROM trades
-        WHERE stock_code = ?
-          AND market = ?
-        ORDER BY timestamp DESC
-        LIMIT 1
-        """,
-        (stock_code, market),
-    )
-    row = cursor.fetchone()
-    if not row or row[0] != "BUY":
-        return None
-    return {"decision_id": row[1], "price": row[2], "quantity": row[3]}
-
-
-def get_recent_symbols(
-    conn: sqlite3.Connection, market: str, limit: int = 30
-) -> list[str]:
-    """Return recent unique symbols for a market, newest first."""
-    cursor = conn.execute(
-        """
-        SELECT stock_code, MAX(timestamp) AS last_ts
-        FROM trades
-        WHERE market = ?
-        GROUP BY stock_code
-        ORDER BY last_ts DESC
-        LIMIT ?
-        """,
-        (market, limit),
-    )
-    return [row[0] for row in cursor.fetchall() if row and row[0]]
--- a/src/main.py
+++ b/src/main.py
--- a/src/markets/schedule.py
+++ b/src/markets/schedule.py
@@ -123,23 +123,6 @@ MARKETS: dict[str, MarketInfo] = {
    ),
 }

-MARKET_SHORTHAND: dict[str, list[str]] = {
-    "US": ["US_NASDAQ", "US_NYSE", "US_AMEX"],
-    "CN": ["CN_SHA", "CN_SZA"],
-    "VN": ["VN_HAN", "VN_HCM"],
-}
-
-
-def expand_market_codes(codes: list[str]) -> list[str]:
-    """Expand shorthand market codes into concrete exchange market codes."""
-    expanded: list[str] = []
-    for code in codes:
-        if code in MARKET_SHORTHAND:
-            expanded.extend(MARKET_SHORTHAND[code])
-        else:
-            expanded.append(code)
-    return expanded
-

 def is_market_open(market: MarketInfo, now: datetime | None = None) -> bool:
    """
--- 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
@@ -484,8 +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"
@@ -512,7 +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
@@ -521,7 +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")
@@ -530,19 +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:
@@ -663,14 +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)
-            args_handler = self._commands_with_args.get(command_name)
-            if args_handler:
-                logger.info("Executing command: /%s %s", command_name, command_parts[1:])
-                await args_handler(command_parts[1:])
-            elif command_name in self._commands:
+            # Execute handler
+            handler = self._commands.get(command_name)
+            if handler:
                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
-(momentum/oversold) to generate BUY conditions, avoiding the all-HOLD problem.
+On failure, returns a defensive playbook (all HOLD, no trades).
 """

 from __future__ import annotations
@@ -135,7 +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(
@@ -294,8 +293,7 @@ class PreMarketPlanner:
            f'      "stock_code": "...",\n'
            f'      "scenarios": [\n'
            f'        {{\n'
-            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0,'
-            f' "unrealized_pnl_pct_above": 3.0, "holding_days_above": 5}},\n'
+            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0}},\n'
            f'          "action": "BUY|SELL|HOLD",\n'
            f'          "confidence": 85,\n'
            f'          "allocation_pct": 10.0,\n'
@@ -391,10 +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():
@@ -476,99 +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_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

 # ---------------------------------------------------------------------------
@@ -274,97 +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."
-
-        mock_response = MagicMock()
-        mock_response.text = '{"action": "HOLD", "confidence": 50, "rationale": "test"}'
-
-        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)
-
-            # 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
-
-    @pytest.mark.asyncio
-    async def test_prompt_override_skips_optimization(self, settings):
-        """prompt_override should bypass prompt optimization."""
-        client = GeminiClient(settings)
-        client._enable_optimization = True
-
-        custom_prompt = "Custom playbook prompt"
-
-        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": "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
-            )
-            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):
-        """Token refresh should wait out cooldown then retry (issue #54)."""
+    async def test_token_refresh_cooldown_prevents_rapid_retries(self, settings):
+        """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)
-            with pytest.raises(ConnectionError, match="Token refresh failed"):
+            # Second attempt within cooldown should fail with cooldown error
+            with pytest.raises(ConnectionError, match="Token refresh on cooldown"):
                await broker._ensure_token()

        await broker.close()
@@ -296,280 +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"
-
-    @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
-
-
-# ---------------------------------------------------------------------------
-# 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"
-        assert body["ORD_UNPR"] == "0"
--- a/tests/test_dashboard.py
+++ b/tests/test_dashboard.py
@@ -1,25 +1,21 @@
-"""Tests for dashboard endpoint handlers."""
+"""Tests for FastAPI dashboard endpoints."""

 from __future__ import annotations

 import json
 import sqlite3
-from collections.abc import Callable
-from datetime import UTC, datetime
 from pathlib import Path
-from typing import Any

 import pytest
-from fastapi import HTTPException
-from fastapi.responses import FileResponse
+
+pytest.importorskip("fastapi")
+from fastapi.testclient import TestClient

 from src.dashboard.app import create_dashboard_app
 from src.db import init_db


 def _seed_db(conn: sqlite3.Connection) -> None:
-    today = datetime.now(UTC).date().isoformat()
-
    conn.execute(
        """
        INSERT INTO playbooks (
@@ -38,24 +34,6 @@ def _seed_db(conn: sqlite3.Connection) -> None:
            1,
        ),
    )
-    conn.execute(
-        """
-        INSERT INTO playbooks (
-            date, market, status, playbook_json, generated_at,
-            token_count, scenario_count, match_count
-        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
-        """,
-        (
-            today,
-            "US_NASDAQ",
-            "ready",
-            json.dumps({"market": "US_NASDAQ", "stock_playbooks": []}),
-            f"{today}T08:30:00+00:00",
-            100,
-            1,
-            0,
-        ),
-    )
    conn.execute(
        """
        INSERT INTO contexts (layer, timeframe, key, value, created_at, updated_at)
@@ -93,7 +71,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
        """,
        (
            "d-kr-1",
-            f"{today}T09:10:00+00:00",
+            "2026-02-14T09:10:00+00:00",
            "005930",
            "KR",
            "KRX",
@@ -113,9 +91,9 @@ def _seed_db(conn: sqlite3.Connection) -> None:
        """,
        (
            "d-us-1",
-            f"{today}T21:10:00+00:00",
+            "2026-02-14T21:10:00+00:00",
            "AAPL",
-            "US_NASDAQ",
+            "US",
            "NASDAQ",
            "SELL",
            80,
@@ -132,7 +110,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (
-            f"{today}T09:11:00+00:00",
+            "2026-02-14T09:11:00+00:00",
            "005930",
            "BUY",
            85,
@@ -154,7 +132,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
        (
-            f"{today}T21:11:00+00:00",
+            "2026-02-14T21:11:00+00:00",
            "AAPL",
            "SELL",
            80,
@@ -162,7 +140,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
            1,
            200,
            -1.0,
-            "US_NASDAQ",
+            "US",
            "NASDAQ",
            None,
            "d-us-1",
@@ -171,148 +149,122 @@ def _seed_db(conn: sqlite3.Connection) -> None:
    conn.commit()


-def _app(tmp_path: Path) -> Any:
+def _client(tmp_path: Path) -> TestClient:
    db_path = tmp_path / "dashboard_test.db"
    conn = init_db(str(db_path))
    _seed_db(conn)
    conn.close()
-    return create_dashboard_app(str(db_path))
-
-
-def _endpoint(app: Any, path: str) -> Callable[..., Any]:
-    for route in app.routes:
-        if getattr(route, "path", None) == path:
-            return route.endpoint
-    raise AssertionError(f"route not found: {path}")
+    app = create_dashboard_app(str(db_path))
+    return TestClient(app)


 def test_index_serves_html(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    index = _endpoint(app, "/")
-    resp = index()
-    assert isinstance(resp, FileResponse)
-    assert "index.html" in str(resp.path)
+    client = _client(tmp_path)
+    resp = client.get("/")
+    assert resp.status_code == 200
+    assert "The Ouroboros Dashboard API" in resp.text


 def test_status_endpoint(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
+    client = _client(tmp_path)
+    resp = client.get("/api/status")
+    assert resp.status_code == 200
+    body = resp.json()
    assert "KR" in body["markets"]
-    assert "US_NASDAQ" in body["markets"]
+    assert "US" in body["markets"]
    assert "totals" in body


 def test_playbook_found(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_playbook = _endpoint(app, "/api/playbook/{date_str}")
-    body = get_playbook("2026-02-14", market="KR")
-    assert body["market"] == "KR"
+    client = _client(tmp_path)
+    resp = client.get("/api/playbook/2026-02-14?market=KR")
+    assert resp.status_code == 200
+    assert resp.json()["market"] == "KR"


 def test_playbook_not_found(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_playbook = _endpoint(app, "/api/playbook/{date_str}")
-    with pytest.raises(HTTPException, match="playbook not found"):
-        get_playbook("2026-02-15", market="KR")
+    client = _client(tmp_path)
+    resp = client.get("/api/playbook/2026-02-15?market=KR")
+    assert resp.status_code == 404


 def test_scorecard_found(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_scorecard = _endpoint(app, "/api/scorecard/{date_str}")
-    body = get_scorecard("2026-02-14", market="KR")
-    assert body["scorecard"]["total_pnl"] == 1.5
+    client = _client(tmp_path)
+    resp = client.get("/api/scorecard/2026-02-14?market=KR")
+    assert resp.status_code == 200
+    assert resp.json()["scorecard"]["total_pnl"] == 1.5


 def test_scorecard_not_found(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_scorecard = _endpoint(app, "/api/scorecard/{date_str}")
-    with pytest.raises(HTTPException, match="scorecard not found"):
-        get_scorecard("2026-02-15", market="KR")
+    client = _client(tmp_path)
+    resp = client.get("/api/scorecard/2026-02-15?market=KR")
+    assert resp.status_code == 404


 def test_performance_all(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_performance = _endpoint(app, "/api/performance")
-    body = get_performance(market="all")
+    client = _client(tmp_path)
+    resp = client.get("/api/performance?market=all")
+    assert resp.status_code == 200
+    body = resp.json()
    assert body["market"] == "all"
    assert body["combined"]["total_trades"] == 2
    assert len(body["by_market"]) == 2


 def test_performance_market_filter(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_performance = _endpoint(app, "/api/performance")
-    body = get_performance(market="KR")
+    client = _client(tmp_path)
+    resp = client.get("/api/performance?market=KR")
+    assert resp.status_code == 200
+    body = resp.json()
    assert body["market"] == "KR"
    assert body["metrics"]["total_trades"] == 1


 def test_performance_empty_market(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_performance = _endpoint(app, "/api/performance")
-    body = get_performance(market="JP")
-    assert body["metrics"]["total_trades"] == 0
+    client = _client(tmp_path)
+    resp = client.get("/api/performance?market=JP")
+    assert resp.status_code == 200
+    assert resp.json()["metrics"]["total_trades"] == 0


 def test_context_layer_all(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_context_layer = _endpoint(app, "/api/context/{layer}")
-    body = get_context_layer("L7_REALTIME", timeframe=None, limit=100)
+    client = _client(tmp_path)
+    resp = client.get("/api/context/L7_REALTIME")
+    assert resp.status_code == 200
+    body = resp.json()
    assert body["layer"] == "L7_REALTIME"
    assert body["count"] == 1


 def test_context_layer_timeframe_filter(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_context_layer = _endpoint(app, "/api/context/{layer}")
-    body = get_context_layer("L6_DAILY", timeframe="2026-02-14", limit=100)
+    client = _client(tmp_path)
+    resp = client.get("/api/context/L6_DAILY?timeframe=2026-02-14")
+    assert resp.status_code == 200
+    body = resp.json()
    assert body["count"] == 1
    assert body["entries"][0]["key"] == "scorecard_KR"


 def test_decisions_endpoint(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_decisions = _endpoint(app, "/api/decisions")
-    body = get_decisions(market="KR", limit=50)
+    client = _client(tmp_path)
+    resp = client.get("/api/decisions?market=KR")
+    assert resp.status_code == 200
+    body = resp.json()
    assert body["count"] == 1
    assert body["decisions"][0]["decision_id"] == "d-kr-1"


 def test_scenarios_active_filters_non_matched(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_active_scenarios = _endpoint(app, "/api/scenarios/active")
-    body = get_active_scenarios(
-        market="KR",
-        date_str=datetime.now(UTC).date().isoformat(),
-        limit=50,
-    )
+    client = _client(tmp_path)
+    resp = client.get("/api/scenarios/active?market=KR&date_str=2026-02-14")
+    assert resp.status_code == 200
+    body = resp.json()
    assert body["count"] == 1
    assert body["matches"][0]["stock_code"] == "005930"


 def test_scenarios_active_empty_when_no_matches(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    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
+    client = _client(tmp_path)
+    resp = client.get("/api/scenarios/active?market=US&date_str=2026-02-14")
+    assert resp.status_code == 200
+    assert resp.json()["count"] == 0
--- a/tests/test_db.py
+++ b/tests/test_db.py
@@ -1,60 +0,0 @@
-"""Tests for database helper functions."""
-
-from src.db import get_open_position, init_db, log_trade
-
-
-def test_get_open_position_returns_latest_buy() -> None:
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        quantity=2,
-        price=70000.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id="d-buy-1",
-    )
-
-    position = get_open_position(conn, "005930", "KR")
-    assert position is not None
-    assert position["decision_id"] == "d-buy-1"
-    assert position["price"] == 70000.0
-    assert position["quantity"] == 2
-
-
-def test_get_open_position_returns_none_when_latest_is_sell() -> None:
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        quantity=1,
-        price=70000.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id="d-buy-1",
-    )
-    log_trade(
-        conn=conn,
-        stock_code="005930",
-        action="SELL",
-        confidence=95,
-        rationale="exit",
-        quantity=1,
-        price=71000.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id="d-sell-1",
-    )
-
-    assert get_open_position(conn, "005930", "KR") is 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
--- a/tests/test_main.py
+++ b/tests/test_main.py
@@ -14,9 +14,6 @@ from src.evolution.scorecard import DailyScorecard
 from src.logging.decision_logger import DecisionLogger
 from src.main import (
    _apply_dashboard_flag,
-    _determine_order_quantity,
-    _extract_held_codes_from_balance,
-    _extract_held_qty_from_balance,
    _handle_market_close,
    _run_context_scheduler,
    _run_evolution_loop,
@@ -71,141 +68,6 @@ def _make_sell_match(stock_code: str = "005930") -> ScenarioMatch:
    )


-class TestExtractHeldQtyFromBalance:
-    """Tests for _extract_held_qty_from_balance()."""
-
-    def _domestic_balance(self, stock_code: str, ord_psbl_qty: int) -> dict:
-        return {
-            "output1": [{"pdno": stock_code, "ord_psbl_qty": str(ord_psbl_qty)}],
-            "output2": [{"dnca_tot_amt": "1000000"}],
-        }
-
-    def test_domestic_returns_ord_psbl_qty(self) -> None:
-        balance = self._domestic_balance("005930", 7)
-        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 7
-
-    def test_domestic_fallback_to_hldg_qty(self) -> None:
-        balance = {"output1": [{"pdno": "005930", "hldg_qty": "3"}]}
-        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 3
-
-    def test_domestic_returns_zero_when_not_found(self) -> None:
-        balance = self._domestic_balance("005930", 5)
-        assert _extract_held_qty_from_balance(balance, "000660", is_domestic=True) == 0
-
-    def test_domestic_returns_zero_when_output1_empty(self) -> None:
-        balance = {"output1": [], "output2": [{}]}
-        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 0
-
-    def test_overseas_returns_ovrs_cblc_qty(self) -> None:
-        balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "10"}]}
-        assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 10
-
-    def test_overseas_fallback_to_hldg_qty(self) -> None:
-        balance = {"output1": [{"ovrs_pdno": "AAPL", "hldg_qty": "4"}]}
-        assert _extract_held_qty_from_balance(balance, "AAPL", is_domestic=False) == 4
-
-    def test_case_insensitive_match(self) -> None:
-        balance = {"output1": [{"pdno": "005930", "ord_psbl_qty": "2"}]}
-        assert _extract_held_qty_from_balance(balance, "005930", is_domestic=True) == 2
-
-
-class TestExtractHeldCodesFromBalance:
-    """Tests for _extract_held_codes_from_balance()."""
-
-    def test_returns_codes_with_positive_qty(self) -> None:
-        balance = {
-            "output1": [
-                {"pdno": "005930", "ord_psbl_qty": "5"},
-                {"pdno": "000660", "ord_psbl_qty": "3"},
-            ]
-        }
-        result = _extract_held_codes_from_balance(balance, is_domestic=True)
-        assert set(result) == {"005930", "000660"}
-
-    def test_excludes_zero_qty_holdings(self) -> None:
-        balance = {
-            "output1": [
-                {"pdno": "005930", "ord_psbl_qty": "0"},
-                {"pdno": "000660", "ord_psbl_qty": "2"},
-            ]
-        }
-        result = _extract_held_codes_from_balance(balance, is_domestic=True)
-        assert "005930" not in result
-        assert "000660" in result
-
-    def test_returns_empty_when_output1_missing(self) -> None:
-        balance: dict = {}
-        assert _extract_held_codes_from_balance(balance, is_domestic=True) == []
-
-    def test_overseas_uses_ovrs_pdno(self) -> None:
-        balance = {"output1": [{"ovrs_pdno": "AAPL", "ovrs_cblc_qty": "3"}]}
-        result = _extract_held_codes_from_balance(balance, is_domestic=False)
-        assert result == ["AAPL"]
-
-
-class TestDetermineOrderQuantity:
-    """Test _determine_order_quantity() — SELL uses broker_held_qty."""
-
-    def test_sell_returns_broker_held_qty(self) -> None:
-        result = _determine_order_quantity(
-            action="SELL",
-            current_price=105.0,
-            total_cash=50000.0,
-            candidate=None,
-            settings=None,
-            broker_held_qty=7,
-        )
-        assert result == 7
-
-    def test_sell_returns_zero_when_broker_qty_zero(self) -> None:
-        result = _determine_order_quantity(
-            action="SELL",
-            current_price=105.0,
-            total_cash=50000.0,
-            candidate=None,
-            settings=None,
-            broker_held_qty=0,
-        )
-        assert result == 0
-
-    def test_buy_without_position_sizing_returns_one(self) -> None:
-        result = _determine_order_quantity(
-            action="BUY",
-            current_price=50000.0,
-            total_cash=1000000.0,
-            candidate=None,
-            settings=None,
-        )
-        assert result == 1
-
-    def test_buy_with_zero_cash_returns_zero(self) -> None:
-        result = _determine_order_quantity(
-            action="BUY",
-            current_price=50000.0,
-            total_cash=0.0,
-            candidate=None,
-            settings=None,
-        )
-        assert result == 0
-
-    def test_buy_with_position_sizing_calculates_correctly(self) -> None:
-        settings = MagicMock(spec=Settings)
-        settings.POSITION_SIZING_ENABLED = True
-        settings.POSITION_VOLATILITY_TARGET_SCORE = 50.0
-        settings.POSITION_BASE_ALLOCATION_PCT = 10.0
-        settings.POSITION_MAX_ALLOCATION_PCT = 30.0
-        settings.POSITION_MIN_ALLOCATION_PCT = 1.0
-        # 1,000,000 * 10% = 100,000 budget // 50,000 price = 2 shares
-        result = _determine_order_quantity(
-            action="BUY",
-            current_price=50000.0,
-            total_cash=1000000.0,
-            candidate=None,
-            settings=settings,
-        )
-        assert result == 2
-
-
 class TestSafeFloat:
    """Test safe_float() helper function."""

@@ -249,7 +111,14 @@ class TestTradingCycleTelegramIntegration:
    def mock_broker(self) -> MagicMock:
        """Create mock broker."""
        broker = MagicMock()
-        broker.get_current_price = AsyncMock(return_value=(50000.0, 1.23, 100.0))
+        broker.get_orderbook = AsyncMock(
+            return_value={
+                "output1": {
+                    "stck_prpr": "50000",
+                    "frgn_ntby_qty": "100",
+                }
+            }
+        )
        broker.get_balance = AsyncMock(
            return_value={
                "output2": [
@@ -868,83 +737,6 @@ class TestOverseasBalanceParsing:
        # Verify price API was called
        mock_overseas_broker_with_empty_price.get_overseas_price.assert_called_once()

-    @pytest.fixture
-    def mock_overseas_broker_with_buy_scenario(self) -> MagicMock:
-        """Create mock overseas broker that returns a valid price for BUY orders."""
-        broker = MagicMock()
-        broker.get_overseas_price = AsyncMock(
-            return_value={"output": {"last": "182.50"}}
-        )
-        broker.get_overseas_balance = AsyncMock(
-            return_value={
-                "output2": [
-                    {
-                        "frcr_evlu_tota": "100000.00",
-                        "frcr_dncl_amt_2": "50000.00",
-                        "frcr_buy_amt_smtl": "50000.00",
-                    }
-                ]
-            }
-        )
-        broker.send_overseas_order = AsyncMock(return_value={"msg1": "주문접수"})
-        return broker
-
-    @pytest.fixture
-    def mock_scenario_engine_buy(self) -> MagicMock:
-        """Create mock scenario engine that returns BUY."""
-        engine = MagicMock(spec=ScenarioEngine)
-        engine.evaluate = MagicMock(return_value=_make_buy_match("AAPL"))
-        return engine
-
-    @pytest.mark.asyncio
-    async def test_overseas_buy_order_uses_limit_price(
-        self,
-        mock_domestic_broker: MagicMock,
-        mock_overseas_broker_with_buy_scenario: MagicMock,
-        mock_scenario_engine_buy: MagicMock,
-        mock_playbook: DayPlaybook,
-        mock_risk: MagicMock,
-        mock_db: MagicMock,
-        mock_decision_logger: MagicMock,
-        mock_context_store: MagicMock,
-        mock_criticality_assessor: MagicMock,
-        mock_telegram: MagicMock,
-        mock_overseas_market: MagicMock,
-    ) -> None:
-        """Overseas BUY order must use current_price (limit), not 0 (market).
-
-        KIS VTS rejects market orders for overseas paper trading.
-        Regression test for issue #149.
-        """
-        mock_telegram.notify_trade_execution = AsyncMock()
-
-        with patch("src.main.log_trade"):
-            await trading_cycle(
-                broker=mock_domestic_broker,
-                overseas_broker=mock_overseas_broker_with_buy_scenario,
-                scenario_engine=mock_scenario_engine_buy,
-                playbook=mock_playbook,
-                risk=mock_risk,
-                db_conn=mock_db,
-                decision_logger=mock_decision_logger,
-                context_store=mock_context_store,
-                criticality_assessor=mock_criticality_assessor,
-                telegram=mock_telegram,
-                market=mock_overseas_market,
-                stock_code="AAPL",
-                scan_candidates={},
-            )
-
-        # Verify limit order was sent with actual price + 0.5% premium (issue #151), not 0.0
-        mock_overseas_broker_with_buy_scenario.send_overseas_order.assert_called_once()
-        call_kwargs = mock_overseas_broker_with_buy_scenario.send_overseas_order.call_args
-        sent_price = call_kwargs[1].get("price") or call_kwargs[0][4]
-        expected_price = round(182.5 * 1.005, 4)  # 0.5% premium for BUY limit orders
-        assert sent_price == expected_price, (
-            f"Expected limit price {expected_price} (182.5 * 1.005) but got {sent_price}. "
-            "KIS VTS only accepts limit orders; BUY uses 0.5% premium to improve fill rate."
-        )
-

 class TestScenarioEngineIntegration:
    """Test scenario engine integration in trading_cycle."""
@@ -953,7 +745,11 @@ class TestScenarioEngineIntegration:
    def mock_broker(self) -> MagicMock:
        """Create mock broker with standard domestic data."""
        broker = MagicMock()
-        broker.get_current_price = AsyncMock(return_value=(50000.0, 2.50, 100.0))
+        broker.get_orderbook = AsyncMock(
+            return_value={
+                "output1": {"stck_prpr": "50000", "frgn_ntby_qty": "100"}
+            }
+        )
        broker.get_balance = AsyncMock(
            return_value={
                "output2": [
@@ -1034,7 +830,6 @@ class TestScenarioEngineIntegration:
        assert market_data["rsi"] == 25.0
        assert market_data["volume_ratio"] == 3.5
        assert market_data["current_price"] == 50000.0
-        assert market_data["price_change_pct"] == 2.5

        # Portfolio data should include pnl
        assert "portfolio_pnl_pct" in portfolio_data
@@ -1375,17 +1170,18 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
    )

    broker = MagicMock()
-    broker.get_current_price = AsyncMock(return_value=(120.0, 0.0, 0.0))
+    broker.get_orderbook = AsyncMock(
+        return_value={"output1": {"stck_prpr": "120", "frgn_ntby_qty": "0"}}
+    )
    broker.get_balance = AsyncMock(
        return_value={
-            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
            "output2": [
                {
                    "tot_evlu_amt": "100000",
                    "dnca_tot_amt": "10000",
                    "pchs_amt_smtl_amt": "90000",
                }
-            ],
+            ]
        }
    )
    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
@@ -1436,418 +1232,6 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
    assert updated_buy.outcome_accuracy == 1


-@pytest.mark.asyncio
-async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
-    """HOLD decision should be overridden to SELL when stop-loss threshold is breached."""
-    db_conn = init_db(":memory:")
-    decision_logger = DecisionLogger(db_conn)
-
-    buy_decision_id = decision_logger.log_decision(
-        stock_code="005930",
-        market="KR",
-        exchange_code="KRX",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        context_snapshot={},
-        input_data={},
-    )
-    log_trade(
-        conn=db_conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        quantity=1,
-        price=100.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id=buy_decision_id,
-    )
-
-    broker = MagicMock()
-    broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
-    broker.get_balance = AsyncMock(
-        return_value={
-            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
-            "output2": [
-                {
-                    "tot_evlu_amt": "100000",
-                    "dnca_tot_amt": "10000",
-                    "pchs_amt_smtl_amt": "90000",
-                }
-            ],
-        }
-    )
-    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
-
-    scenario = StockScenario(
-        condition=StockCondition(rsi_below=30),
-        action=ScenarioAction.BUY,
-        confidence=88,
-        stop_loss_pct=-2.0,
-        rationale="stop loss policy",
-    )
-    playbook = DayPlaybook(
-        date=date(2026, 2, 8),
-        market="KR",
-        stock_playbooks=[
-            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
-        ],
-    )
-    engine = MagicMock(spec=ScenarioEngine)
-    engine.evaluate = MagicMock(return_value=_make_hold_match())
-
-    market = MagicMock()
-    market.name = "Korea"
-    market.code = "KR"
-    market.exchange_code = "KRX"
-    market.is_domestic = True
-
-    telegram = MagicMock()
-    telegram.notify_trade_execution = AsyncMock()
-    telegram.notify_fat_finger = AsyncMock()
-    telegram.notify_circuit_breaker = AsyncMock()
-    telegram.notify_scenario_matched = AsyncMock()
-
-    await trading_cycle(
-        broker=broker,
-        overseas_broker=MagicMock(),
-        scenario_engine=engine,
-        playbook=playbook,
-        risk=MagicMock(),
-        db_conn=db_conn,
-        decision_logger=decision_logger,
-        context_store=MagicMock(
-            get_latest_timeframe=MagicMock(return_value=None),
-            set_context=MagicMock(),
-        ),
-        criticality_assessor=MagicMock(
-            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
-            get_timeout=MagicMock(return_value=5.0),
-        ),
-        telegram=telegram,
-        market=market,
-        stock_code="005930",
-        scan_candidates={},
-    )
-
-    broker.send_order.assert_called_once()
-    assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
-
-
-@pytest.mark.asyncio
-async def test_hold_overridden_to_sell_when_take_profit_triggered() -> None:
-    """HOLD decision should be overridden to SELL when take-profit threshold is reached."""
-    db_conn = init_db(":memory:")
-    decision_logger = DecisionLogger(db_conn)
-
-    buy_decision_id = decision_logger.log_decision(
-        stock_code="005930",
-        market="KR",
-        exchange_code="KRX",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        context_snapshot={},
-        input_data={},
-    )
-    log_trade(
-        conn=db_conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        quantity=1,
-        price=100.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id=buy_decision_id,
-    )
-
-    broker = MagicMock()
-    # Current price 106.0 → +6% gain, above take_profit_pct=3.0
-    broker.get_current_price = AsyncMock(return_value=(106.0, 6.0, 0.0))
-    broker.get_balance = AsyncMock(
-        return_value={
-            "output1": [{"pdno": "005930", "ord_psbl_qty": "1"}],
-            "output2": [
-                {
-                    "tot_evlu_amt": "100000",
-                    "dnca_tot_amt": "10000",
-                    "pchs_amt_smtl_amt": "90000",
-                }
-            ],
-        }
-    )
-    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
-
-    scenario = StockScenario(
-        condition=StockCondition(rsi_below=30),
-        action=ScenarioAction.BUY,
-        confidence=88,
-        stop_loss_pct=-2.0,
-        take_profit_pct=3.0,
-        rationale="take profit policy",
-    )
-    playbook = DayPlaybook(
-        date=date(2026, 2, 8),
-        market="KR",
-        stock_playbooks=[
-            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
-        ],
-    )
-    engine = MagicMock(spec=ScenarioEngine)
-    engine.evaluate = MagicMock(return_value=_make_hold_match())
-
-    market = MagicMock()
-    market.name = "Korea"
-    market.code = "KR"
-    market.exchange_code = "KRX"
-    market.is_domestic = True
-
-    telegram = MagicMock()
-    telegram.notify_trade_execution = AsyncMock()
-    telegram.notify_fat_finger = AsyncMock()
-    telegram.notify_circuit_breaker = AsyncMock()
-    telegram.notify_scenario_matched = AsyncMock()
-
-    await trading_cycle(
-        broker=broker,
-        overseas_broker=MagicMock(),
-        scenario_engine=engine,
-        playbook=playbook,
-        risk=MagicMock(),
-        db_conn=db_conn,
-        decision_logger=decision_logger,
-        context_store=MagicMock(
-            get_latest_timeframe=MagicMock(return_value=None),
-            set_context=MagicMock(),
-        ),
-        criticality_assessor=MagicMock(
-            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
-            get_timeout=MagicMock(return_value=5.0),
-        ),
-        telegram=telegram,
-        market=market,
-        stock_code="005930",
-        scan_candidates={},
-    )
-
-    broker.send_order.assert_called_once()
-    assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
-
-
-@pytest.mark.asyncio
-async def test_hold_not_overridden_when_between_stop_loss_and_take_profit() -> None:
-    """HOLD should remain HOLD when P&L is within stop-loss and take-profit bounds."""
-    db_conn = init_db(":memory:")
-    decision_logger = DecisionLogger(db_conn)
-
-    buy_decision_id = decision_logger.log_decision(
-        stock_code="005930",
-        market="KR",
-        exchange_code="KRX",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        context_snapshot={},
-        input_data={},
-    )
-    log_trade(
-        conn=db_conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        quantity=1,
-        price=100.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id=buy_decision_id,
-    )
-
-    broker = MagicMock()
-    # Current price 101.0 → +1% gain, within [-2%, +3%] range
-    broker.get_current_price = AsyncMock(return_value=(101.0, 1.0, 0.0))
-    broker.get_balance = AsyncMock(
-        return_value={
-            "output2": [
-                {
-                    "tot_evlu_amt": "100000",
-                    "dnca_tot_amt": "10000",
-                    "pchs_amt_smtl_amt": "90000",
-                }
-            ]
-        }
-    )
-    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
-
-    scenario = StockScenario(
-        condition=StockCondition(rsi_below=30),
-        action=ScenarioAction.BUY,
-        confidence=88,
-        stop_loss_pct=-2.0,
-        take_profit_pct=3.0,
-        rationale="within range policy",
-    )
-    playbook = DayPlaybook(
-        date=date(2026, 2, 8),
-        market="KR",
-        stock_playbooks=[
-            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
-        ],
-    )
-    engine = MagicMock(spec=ScenarioEngine)
-    engine.evaluate = MagicMock(return_value=_make_hold_match())
-
-    market = MagicMock()
-    market.name = "Korea"
-    market.code = "KR"
-    market.exchange_code = "KRX"
-    market.is_domestic = True
-
-    telegram = MagicMock()
-    telegram.notify_trade_execution = AsyncMock()
-    telegram.notify_fat_finger = AsyncMock()
-    telegram.notify_circuit_breaker = AsyncMock()
-    telegram.notify_scenario_matched = AsyncMock()
-
-    await trading_cycle(
-        broker=broker,
-        overseas_broker=MagicMock(),
-        scenario_engine=engine,
-        playbook=playbook,
-        risk=MagicMock(),
-        db_conn=db_conn,
-        decision_logger=decision_logger,
-        context_store=MagicMock(
-            get_latest_timeframe=MagicMock(return_value=None),
-            set_context=MagicMock(),
-        ),
-        criticality_assessor=MagicMock(
-            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
-            get_timeout=MagicMock(return_value=5.0),
-        ),
-        telegram=telegram,
-        market=market,
-        stock_code="005930",
-        scan_candidates={},
-    )
-
-    broker.send_order.assert_not_called()
-
-
-@pytest.mark.asyncio
-async def test_sell_order_uses_broker_balance_qty_not_db() -> None:
-    """SELL quantity must come from broker balance output1, not DB.
-
-    The DB records order quantity which may differ from actual fill quantity.
-    This test verifies that we use the broker-confirmed orderable quantity.
-    """
-    db_conn = init_db(":memory:")
-    decision_logger = DecisionLogger(db_conn)
-
-    buy_decision_id = decision_logger.log_decision(
-        stock_code="005930",
-        market="KR",
-        exchange_code="KRX",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        context_snapshot={},
-        input_data={},
-    )
-    # DB records 10 shares ordered — but only 5 actually filled (partial fill scenario)
-    log_trade(
-        conn=db_conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=90,
-        rationale="entry",
-        quantity=10,  # ordered quantity (may differ from fill)
-        price=100.0,
-        market="KR",
-        exchange_code="KRX",
-        decision_id=buy_decision_id,
-    )
-
-    broker = MagicMock()
-    # Stop-loss triggers (price dropped below -2%)
-    broker.get_current_price = AsyncMock(return_value=(95.0, -5.0, 0.0))
-    broker.get_balance = AsyncMock(
-        return_value={
-            # Broker confirms only 5 shares are actually orderable (partial fill)
-            "output1": [{"pdno": "005930", "ord_psbl_qty": "5"}],
-            "output2": [
-                {
-                    "tot_evlu_amt": "100000",
-                    "dnca_tot_amt": "10000",
-                    "pchs_amt_smtl_amt": "90000",
-                }
-            ],
-        }
-    )
-    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
-
-    scenario = StockScenario(
-        condition=StockCondition(rsi_below=30),
-        action=ScenarioAction.BUY,
-        confidence=88,
-        stop_loss_pct=-2.0,
-        rationale="stop loss policy",
-    )
-    playbook = DayPlaybook(
-        date=date(2026, 2, 8),
-        market="KR",
-        stock_playbooks=[
-            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
-        ],
-    )
-    engine = MagicMock(spec=ScenarioEngine)
-    engine.evaluate = MagicMock(return_value=_make_hold_match())
-
-    market = MagicMock()
-    market.name = "Korea"
-    market.code = "KR"
-    market.exchange_code = "KRX"
-    market.is_domestic = True
-
-    telegram = MagicMock()
-    telegram.notify_trade_execution = AsyncMock()
-    telegram.notify_fat_finger = AsyncMock()
-    telegram.notify_circuit_breaker = AsyncMock()
-    telegram.notify_scenario_matched = AsyncMock()
-
-    await trading_cycle(
-        broker=broker,
-        overseas_broker=MagicMock(),
-        scenario_engine=engine,
-        playbook=playbook,
-        risk=MagicMock(),
-        db_conn=db_conn,
-        decision_logger=decision_logger,
-        context_store=MagicMock(
-            get_latest_timeframe=MagicMock(return_value=None),
-            set_context=MagicMock(),
-        ),
-        criticality_assessor=MagicMock(
-            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
-            get_timeout=MagicMock(return_value=5.0),
-        ),
-        telegram=telegram,
-        market=market,
-        stock_code="005930",
-        scan_candidates={},
-    )
-
-    broker.send_order.assert_called_once()
-    call_kwargs = broker.send_order.call_args.kwargs
-    assert call_kwargs["order_type"] == "SELL"
-    # Must use broker-confirmed qty (5), NOT DB-recorded ordered qty (10)
-    assert call_kwargs["quantity"] == 5
-
-
@pytest.mark.asyncio
 async def test_handle_market_close_runs_daily_review_flow() -> None:
    """Market close should aggregate, create scorecard, lessons, and notify."""
@@ -2043,7 +1427,7 @@ async def test_run_evolution_loop_notifies_when_pr_generated() -> None:
    await _run_evolution_loop(
        evolution_optimizer=optimizer,
        telegram=telegram,
-        market_code="US_NASDAQ",
+        market_code="US",
        market_date="2026-02-14",
    )

@@ -2067,7 +1451,7 @@ async def test_run_evolution_loop_notification_error_is_ignored() -> None:
    await _run_evolution_loop(
        evolution_optimizer=optimizer,
        telegram=telegram,
-        market_code="US_NYSE",
+        market_code="US",
        market_date="2026-02-14",
    )

--- a/tests/test_market_schedule.py
+++ b/tests/test_market_schedule.py
@@ -7,7 +7,6 @@ import pytest

 from src.markets.schedule import (
    MARKETS,
-    expand_market_codes,
    get_next_market_open,
    get_open_markets,
    is_market_open,
@@ -200,28 +199,3 @@ class TestGetNextMarketOpen:
            enabled_markets=["INVALID", "KR"], now=test_time
        )
        assert market.code == "KR"
-
-
-class TestExpandMarketCodes:
-    """Test shorthand market expansion."""
-
-    def test_expand_us_shorthand(self) -> None:
-        assert expand_market_codes(["US"]) == ["US_NASDAQ", "US_NYSE", "US_AMEX"]
-
-    def test_expand_cn_shorthand(self) -> None:
-        assert expand_market_codes(["CN"]) == ["CN_SHA", "CN_SZA"]
-
-    def test_expand_vn_shorthand(self) -> None:
-        assert expand_market_codes(["VN"]) == ["VN_HAN", "VN_HCM"]
-
-    def test_expand_mixed_codes(self) -> None:
-        assert expand_market_codes(["KR", "US", "JP"]) == [
-            "KR",
-            "US_NASDAQ",
-            "US_NYSE",
-            "US_AMEX",
-            "JP",
-        ]
-
-    def test_expand_preserves_unknown_code(self) -> None:
-        assert expand_market_codes(["KR", "UNKNOWN"]) == ["KR", "UNKNOWN"]
--- a/tests/test_overseas_broker.py
+++ b/tests/test_overseas_broker.py
@@ -1,643 +0,0 @@
-"""Tests for OverseasBroker — rankings, price, balance, order, and helpers."""
-
-from __future__ import annotations
-
-from unittest.mock import AsyncMock, MagicMock
-
-import aiohttp
-import pytest
-
-from src.broker.kis_api import KISBroker
-from src.broker.overseas import OverseasBroker, _PRICE_EXCHANGE_MAP, _RANKING_EXCHANGE_MAP
-from src.config import Settings
-
-
-def _make_async_cm(mock_resp: AsyncMock) -> MagicMock:
-    """Create an async context manager that returns mock_resp on __aenter__."""
-    cm = MagicMock()
-    cm.__aenter__ = AsyncMock(return_value=mock_resp)
-    cm.__aexit__ = AsyncMock(return_value=False)
-    return cm
-
-
-@pytest.fixture
-def mock_settings() -> Settings:
-    """Provide mock settings with correct default TR_IDs/paths."""
-    return Settings(
-        KIS_APP_KEY="test_key",
-        KIS_APP_SECRET="test_secret",
-        KIS_ACCOUNT_NO="12345678-01",
-        GEMINI_API_KEY="test_gemini_key",
-    )
-
-
-@pytest.fixture
-def mock_broker(mock_settings: Settings) -> KISBroker:
-    """Provide a mock KIS broker."""
-    broker = KISBroker(mock_settings)
-    broker.get_orderbook = AsyncMock()  # type: ignore[method-assign]
-    return broker
-
-
-@pytest.fixture
-def overseas_broker(mock_broker: KISBroker) -> OverseasBroker:
-    """Provide an OverseasBroker wrapping a mock KISBroker."""
-    return OverseasBroker(mock_broker)
-
-
-def _setup_broker_mocks(overseas_broker: OverseasBroker, mock_session: MagicMock) -> None:
-    """Wire up common broker mocks."""
-    overseas_broker._broker._rate_limiter.acquire = AsyncMock()
-    overseas_broker._broker._get_session = MagicMock(return_value=mock_session)
-    overseas_broker._broker._auth_headers = AsyncMock(return_value={})
-
-
-class TestRankingExchangeMap:
-    """Test exchange code mapping for ranking API."""
-
-    def test_nasd_maps_to_nas(self) -> None:
-        assert _RANKING_EXCHANGE_MAP["NASD"] == "NAS"
-
-    def test_nyse_maps_to_nys(self) -> None:
-        assert _RANKING_EXCHANGE_MAP["NYSE"] == "NYS"
-
-    def test_amex_maps_to_ams(self) -> None:
-        assert _RANKING_EXCHANGE_MAP["AMEX"] == "AMS"
-
-    def test_sehk_maps_to_hks(self) -> None:
-        assert _RANKING_EXCHANGE_MAP["SEHK"] == "HKS"
-
-    def test_unmapped_exchange_passes_through(self) -> None:
-        assert _RANKING_EXCHANGE_MAP.get("UNKNOWN", "UNKNOWN") == "UNKNOWN"
-
-    def test_tse_unchanged(self) -> None:
-        assert _RANKING_EXCHANGE_MAP["TSE"] == "TSE"
-
-
-class TestConfigDefaults:
-    """Test that config defaults match KIS official API specs."""
-
-    def test_fluct_tr_id(self, mock_settings: Settings) -> None:
-        assert mock_settings.OVERSEAS_RANKING_FLUCT_TR_ID == "HHDFS76290000"
-
-    def test_volume_tr_id(self, mock_settings: Settings) -> None:
-        assert mock_settings.OVERSEAS_RANKING_VOLUME_TR_ID == "HHDFS76270000"
-
-    def test_fluct_path(self, mock_settings: Settings) -> None:
-        assert mock_settings.OVERSEAS_RANKING_FLUCT_PATH == "/uapi/overseas-stock/v1/ranking/updown-rate"
-
-    def test_volume_path(self, mock_settings: Settings) -> None:
-        assert mock_settings.OVERSEAS_RANKING_VOLUME_PATH == "/uapi/overseas-stock/v1/ranking/volume-surge"
-
-
-class TestFetchOverseasRankings:
-    """Test fetch_overseas_rankings method."""
-
-    @pytest.mark.asyncio
-    async def test_fluctuation_uses_correct_params(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """Fluctuation ranking should use HHDFS76290000, updown-rate path, and correct params."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(
-            return_value={"output": [{"symb": "AAPL", "name": "Apple"}]}
-        )
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._auth_headers = AsyncMock(
-            return_value={"authorization": "Bearer test"}
-        )
-
-        result = await overseas_broker.fetch_overseas_rankings("NASD", "fluctuation")
-
-        assert len(result) == 1
-        assert result[0]["symb"] == "AAPL"
-
-        call_args = mock_session.get.call_args
-        url = call_args[0][0]
-        params = call_args[1]["params"]
-
-        assert "/uapi/overseas-stock/v1/ranking/updown-rate" in url
-        assert params["EXCD"] == "NAS"
-        assert params["NDAY"] == "0"
-        assert params["GUBN"] == "1"
-        assert params["VOL_RANG"] == "0"
-
-        overseas_broker._broker._auth_headers.assert_called_with("HHDFS76290000")
-
-    @pytest.mark.asyncio
-    async def test_volume_uses_correct_params(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """Volume ranking should use HHDFS76270000, volume-surge path, and correct params."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(
-            return_value={"output": [{"symb": "TSLA", "name": "Tesla"}]}
-        )
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._auth_headers = AsyncMock(
-            return_value={"authorization": "Bearer test"}
-        )
-
-        result = await overseas_broker.fetch_overseas_rankings("NYSE", "volume")
-
-        assert len(result) == 1
-
-        call_args = mock_session.get.call_args
-        url = call_args[0][0]
-        params = call_args[1]["params"]
-
-        assert "/uapi/overseas-stock/v1/ranking/volume-surge" in url
-        assert params["EXCD"] == "NYS"
-        assert params["MIXN"] == "0"
-        assert params["VOL_RANG"] == "0"
-        assert "NDAY" not in params
-        assert "GUBN" not in params
-
-        overseas_broker._broker._auth_headers.assert_called_with("HHDFS76270000")
-
-    @pytest.mark.asyncio
-    async def test_404_returns_empty_list(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """HTTP 404 should return empty list (fallback) instead of raising."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 404
-        mock_resp.text = AsyncMock(return_value="Not Found")
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        result = await overseas_broker.fetch_overseas_rankings("AMEX", "fluctuation")
-        assert result == []
-
-    @pytest.mark.asyncio
-    async def test_non_404_error_raises(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """Non-404 HTTP errors should raise ConnectionError."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 500
-        mock_resp.text = AsyncMock(return_value="Internal Server Error")
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        with pytest.raises(ConnectionError, match="500"):
-            await overseas_broker.fetch_overseas_rankings("NASD")
-
-    @pytest.mark.asyncio
-    async def test_empty_response_returns_empty(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """Empty output in response should return empty list."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"output": []})
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        result = await overseas_broker.fetch_overseas_rankings("NASD")
-        assert result == []
-
-    @pytest.mark.asyncio
-    async def test_ranking_disabled_returns_empty(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """When OVERSEAS_RANKING_ENABLED=False, should return empty immediately."""
-        overseas_broker._broker._settings.OVERSEAS_RANKING_ENABLED = False
-        result = await overseas_broker.fetch_overseas_rankings("NASD")
-        assert result == []
-
-    @pytest.mark.asyncio
-    async def test_limit_truncates_results(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """Results should be truncated to the specified limit."""
-        rows = [{"symb": f"SYM{i}"} for i in range(20)]
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"output": rows})
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        result = await overseas_broker.fetch_overseas_rankings("NASD", limit=5)
-        assert len(result) == 5
-
-    @pytest.mark.asyncio
-    async def test_network_error_raises(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """Network errors should raise ConnectionError."""
-        cm = MagicMock()
-        cm.__aenter__ = AsyncMock(side_effect=aiohttp.ClientError("timeout"))
-        cm.__aexit__ = AsyncMock(return_value=False)
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=cm)
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        with pytest.raises(ConnectionError, match="Network error"):
-            await overseas_broker.fetch_overseas_rankings("NASD")
-
-    @pytest.mark.asyncio
-    async def test_exchange_code_mapping_applied(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """All major exchanges should use mapped codes in API params."""
-        for original, mapped in [("NASD", "NAS"), ("NYSE", "NYS"), ("AMEX", "AMS")]:
-            mock_resp = AsyncMock()
-            mock_resp.status = 200
-            mock_resp.json = AsyncMock(return_value={"output": [{"symb": "X"}]})
-
-            mock_session = MagicMock()
-            mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-            _setup_broker_mocks(overseas_broker, mock_session)
-
-            await overseas_broker.fetch_overseas_rankings(original)
-
-            call_params = mock_session.get.call_args[1]["params"]
-            assert call_params["EXCD"] == mapped, f"{original} should map to {mapped}"
-
-
-class TestGetOverseasPrice:
-    """Test get_overseas_price method."""
-
-    @pytest.mark.asyncio
-    async def test_success(self, overseas_broker: OverseasBroker) -> None:
-        """Successful price fetch returns JSON data."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"output": {"last": "150.00"}})
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._auth_headers = AsyncMock(return_value={"authorization": "Bearer t"})
-
-        result = await overseas_broker.get_overseas_price("NASD", "AAPL")
-        assert result["output"]["last"] == "150.00"
-
-        call_args = mock_session.get.call_args
-        params = call_args[1]["params"]
-        assert params["EXCD"] == "NAS"  # NASD → NAS via _PRICE_EXCHANGE_MAP
-        assert params["SYMB"] == "AAPL"
-
-    @pytest.mark.asyncio
-    async def test_http_error_raises(self, overseas_broker: OverseasBroker) -> None:
-        """Non-200 response should raise ConnectionError."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 400
-        mock_resp.text = AsyncMock(return_value="Bad Request")
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        with pytest.raises(ConnectionError, match="get_overseas_price failed"):
-            await overseas_broker.get_overseas_price("NASD", "AAPL")
-
-    @pytest.mark.asyncio
-    async def test_network_error_raises(self, overseas_broker: OverseasBroker) -> None:
-        """Network error should raise ConnectionError."""
-        cm = MagicMock()
-        cm.__aenter__ = AsyncMock(side_effect=aiohttp.ClientError("conn refused"))
-        cm.__aexit__ = AsyncMock(return_value=False)
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=cm)
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        with pytest.raises(ConnectionError, match="Network error"):
-            await overseas_broker.get_overseas_price("NASD", "AAPL")
-
-
-class TestGetOverseasBalance:
-    """Test get_overseas_balance method."""
-
-    @pytest.mark.asyncio
-    async def test_success(self, overseas_broker: OverseasBroker) -> None:
-        """Successful balance fetch returns JSON data."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"output1": [{"pdno": "AAPL"}]})
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        result = await overseas_broker.get_overseas_balance("NASD")
-        assert result["output1"][0]["pdno"] == "AAPL"
-
-    @pytest.mark.asyncio
-    async def test_http_error_raises(self, overseas_broker: OverseasBroker) -> None:
-        """Non-200 should raise ConnectionError."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 500
-        mock_resp.text = AsyncMock(return_value="Server Error")
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        with pytest.raises(ConnectionError, match="get_overseas_balance failed"):
-            await overseas_broker.get_overseas_balance("NASD")
-
-    @pytest.mark.asyncio
-    async def test_network_error_raises(self, overseas_broker: OverseasBroker) -> None:
-        """Network error should raise ConnectionError."""
-        cm = MagicMock()
-        cm.__aenter__ = AsyncMock(side_effect=TimeoutError("timeout"))
-        cm.__aexit__ = AsyncMock(return_value=False)
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=cm)
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        with pytest.raises(ConnectionError, match="Network error"):
-            await overseas_broker.get_overseas_balance("NYSE")
-
-
-class TestSendOverseasOrder:
-    """Test send_overseas_order method."""
-
-    @pytest.mark.asyncio
-    async def test_buy_market_order(self, overseas_broker: OverseasBroker) -> None:
-        """Market buy order should use VTTT1002U and ORD_DVSN=01."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"rt_cd": "0"})
-
-        mock_session = MagicMock()
-        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
-
-        result = await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 10)
-        assert result["rt_cd"] == "0"
-
-        # Verify BUY TR_ID
-        overseas_broker._broker._auth_headers.assert_called_with("VTTT1002U")
-
-        call_args = mock_session.post.call_args
-        body = call_args[1]["json"]
-        assert body["ORD_DVSN"] == "01"  # market order
-        assert body["OVRS_ORD_UNPR"] == "0"
-
-    @pytest.mark.asyncio
-    async def test_sell_limit_order(self, overseas_broker: OverseasBroker) -> None:
-        """Limit sell order should use VTTT1006U and ORD_DVSN=00."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"rt_cd": "0"})
-
-        mock_session = MagicMock()
-        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
-
-        result = await overseas_broker.send_overseas_order("NYSE", "MSFT", "SELL", 5, price=350.0)
-        assert result["rt_cd"] == "0"
-
-        overseas_broker._broker._auth_headers.assert_called_with("VTTT1006U")
-
-        call_args = mock_session.post.call_args
-        body = call_args[1]["json"]
-        assert body["ORD_DVSN"] == "00"  # limit order
-        assert body["OVRS_ORD_UNPR"] == "350.0"
-
-    @pytest.mark.asyncio
-    async def test_order_http_error_raises(self, overseas_broker: OverseasBroker) -> None:
-        """Non-200 should raise ConnectionError."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 400
-        mock_resp.text = AsyncMock(return_value="Bad Request")
-
-        mock_session = MagicMock()
-        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
-
-        with pytest.raises(ConnectionError, match="send_overseas_order failed"):
-            await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 1)
-
-    @pytest.mark.asyncio
-    async def test_order_network_error_raises(self, overseas_broker: OverseasBroker) -> None:
-        """Network error should raise ConnectionError."""
-        cm = MagicMock()
-        cm.__aenter__ = AsyncMock(side_effect=aiohttp.ClientError("conn reset"))
-        cm.__aexit__ = AsyncMock(return_value=False)
-
-        mock_session = MagicMock()
-        mock_session.post = MagicMock(return_value=cm)
-
-        _setup_broker_mocks(overseas_broker, mock_session)
-        overseas_broker._broker._get_hash_key = AsyncMock(return_value="hashval")
-
-        with pytest.raises(ConnectionError, match="Network error"):
-            await overseas_broker.send_overseas_order("NASD", "TSLA", "SELL", 2)
-
-
-class TestGetCurrencyCode:
-    """Test _get_currency_code mapping."""
-
-    def test_us_exchanges(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._get_currency_code("NASD") == "USD"
-        assert overseas_broker._get_currency_code("NYSE") == "USD"
-        assert overseas_broker._get_currency_code("AMEX") == "USD"
-
-    def test_japan(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._get_currency_code("TSE") == "JPY"
-
-    def test_hong_kong(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._get_currency_code("SEHK") == "HKD"
-
-    def test_china(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._get_currency_code("SHAA") == "CNY"
-        assert overseas_broker._get_currency_code("SZAA") == "CNY"
-
-    def test_vietnam(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._get_currency_code("HNX") == "VND"
-        assert overseas_broker._get_currency_code("HSX") == "VND"
-
-    def test_unknown_defaults_usd(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._get_currency_code("UNKNOWN") == "USD"
-
-
-class TestExtractRankingRows:
-    """Test _extract_ranking_rows helper."""
-
-    def test_output_key(self, overseas_broker: OverseasBroker) -> None:
-        data = {"output": [{"a": 1}, {"b": 2}]}
-        assert overseas_broker._extract_ranking_rows(data) == [{"a": 1}, {"b": 2}]
-
-    def test_output1_key(self, overseas_broker: OverseasBroker) -> None:
-        data = {"output1": [{"c": 3}]}
-        assert overseas_broker._extract_ranking_rows(data) == [{"c": 3}]
-
-    def test_output2_key(self, overseas_broker: OverseasBroker) -> None:
-        data = {"output2": [{"d": 4}]}
-        assert overseas_broker._extract_ranking_rows(data) == [{"d": 4}]
-
-    def test_no_list_returns_empty(self, overseas_broker: OverseasBroker) -> None:
-        data = {"output": "not a list"}
-        assert overseas_broker._extract_ranking_rows(data) == []
-
-    def test_empty_data(self, overseas_broker: OverseasBroker) -> None:
-        assert overseas_broker._extract_ranking_rows({}) == []
-
-    def test_filters_non_dict_rows(self, overseas_broker: OverseasBroker) -> None:
-        data = {"output": [{"a": 1}, "invalid", {"b": 2}]}
-        assert overseas_broker._extract_ranking_rows(data) == [{"a": 1}, {"b": 2}]
-
-
-class TestPriceExchangeMap:
-    """Test _PRICE_EXCHANGE_MAP is applied in get_overseas_price (issue #151)."""
-
-    def test_price_map_equals_ranking_map(self) -> None:
-        assert _PRICE_EXCHANGE_MAP is _RANKING_EXCHANGE_MAP
-
-    @pytest.mark.parametrize("original,expected", [
-        ("NASD", "NAS"),
-        ("NYSE", "NYS"),
-        ("AMEX", "AMS"),
-    ])
-    def test_us_exchange_code_mapping(self, original: str, expected: str) -> None:
-        assert _PRICE_EXCHANGE_MAP[original] == expected
-
-    @pytest.mark.asyncio
-    async def test_get_overseas_price_sends_mapped_code(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """NASD → NAS must be sent to HHDFS00000300."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"output": {"last": "200.00"}})
-
-        mock_session = MagicMock()
-        mock_session.get = MagicMock(return_value=_make_async_cm(mock_resp))
-        _setup_broker_mocks(overseas_broker, mock_session)
-
-        await overseas_broker.get_overseas_price("NASD", "AAPL")
-
-        params = mock_session.get.call_args[1]["params"]
-        assert params["EXCD"] == "NAS"
-
-
-class TestOrderRtCdCheck:
-    """Test that send_overseas_order checks rt_cd and logs accordingly (issue #151)."""
-
-    @pytest.fixture
-    def overseas_broker(self, mock_settings: Settings) -> OverseasBroker:
-        broker = MagicMock(spec=KISBroker)
-        broker._settings = mock_settings
-        broker._account_no = "12345678"
-        broker._product_cd = "01"
-        broker._base_url = "https://openapivts.koreainvestment.com:9443"
-        broker._rate_limiter = AsyncMock()
-        broker._rate_limiter.acquire = AsyncMock()
-        broker._auth_headers = AsyncMock(return_value={"authorization": "Bearer t"})
-        broker._get_hash_key = AsyncMock(return_value="hashval")
-        return OverseasBroker(broker)
-
-    @pytest.mark.asyncio
-    async def test_success_rt_cd_returns_data(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """rt_cd='0' → order accepted, data returned."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"rt_cd": "0", "msg1": "완료"})
-
-        mock_session = MagicMock()
-        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
-        overseas_broker._broker._get_session = MagicMock(return_value=mock_session)
-
-        result = await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 10, price=150.0)
-        assert result["rt_cd"] == "0"
-
-    @pytest.mark.asyncio
-    async def test_error_rt_cd_returns_data_with_msg(
-        self, overseas_broker: OverseasBroker
-    ) -> None:
-        """rt_cd != '0' → order rejected, data still returned (caller checks rt_cd)."""
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(
-            return_value={"rt_cd": "1", "msg1": "주문가능금액이 부족합니다."}
-        )
-
-        mock_session = MagicMock()
-        mock_session.post = MagicMock(return_value=_make_async_cm(mock_resp))
-        overseas_broker._broker._get_session = MagicMock(return_value=mock_session)
-
-        result = await overseas_broker.send_overseas_order("NASD", "AAPL", "BUY", 10, price=150.0)
-        assert result["rt_cd"] == "1"
-        assert "부족" in result["msg1"]
-
-
-class TestPaperOverseasCash:
-    """Test PAPER_OVERSEAS_CASH config setting (issue #151)."""
-
-    def test_default_value(self) -> None:
-        settings = Settings(
-            KIS_APP_KEY="k",
-            KIS_APP_SECRET="s",
-            KIS_ACCOUNT_NO="12345678-01",
-            GEMINI_API_KEY="g",
-        )
-        assert settings.PAPER_OVERSEAS_CASH == 50000.0
-
-    def test_env_override(self) -> None:
-        import os
-        os.environ["PAPER_OVERSEAS_CASH"] = "25000"
-        settings = Settings(
-            KIS_APP_KEY="k",
-            KIS_APP_SECRET="s",
-            KIS_ACCOUNT_NO="12345678-01",
-            GEMINI_API_KEY="g",
-        )
-        assert settings.PAPER_OVERSEAS_CASH == 25000.0
-        del os.environ["PAPER_OVERSEAS_CASH"]
-
-    def test_zero_disables_fallback(self) -> None:
-        import os
-        os.environ["PAPER_OVERSEAS_CASH"] = "0"
-        settings = Settings(
-            KIS_APP_KEY="k",
-            KIS_APP_SECRET="s",
-            KIS_ACCOUNT_NO="12345678-01",
-            GEMINI_API_KEY="g",
-        )
-        assert settings.PAPER_OVERSEAS_CASH == 0.0
-        del os.environ["PAPER_OVERSEAS_CASH"]
--- 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
+        assert pb.market_outlook == MarketOutlook.NEUTRAL_TO_BEARISH
        assert pb.stock_count == 1
-        # Oversold candidate → first scenario is BUY, second is SELL stop-loss
-        scenarios = pb.stock_playbooks[0].scenarios
-        assert scenarios[0].action == ScenarioAction.BUY
-        assert scenarios[0].condition.rsi_below == 30
-        assert scenarios[1].action == ScenarioAction.SELL
+        # Defensive playbook has stop-loss scenarios
+        assert pb.stock_playbooks[0].scenarios[0].action == ScenarioAction.SELL

    @pytest.mark.asyncio
    async def test_gemini_failure_empty_when_defensive_disabled(self) -> None:
@@ -662,171 +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
--- 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
@@ -8,7 +8,6 @@ from unittest.mock import AsyncMock, MagicMock
 from src.analysis.smart_scanner import ScanCandidate, SmartVolatilityScanner
 from src.analysis.volatility import VolatilityAnalyzer
 from src.broker.kis_api import KISBroker
-from src.broker.overseas import OverseasBroker
 from src.config import Settings


@@ -44,70 +43,61 @@ def scanner(mock_broker: MagicMock, mock_settings: Settings) -> SmartVolatilityS
    analyzer = VolatilityAnalyzer()
    return SmartVolatilityScanner(
        broker=mock_broker,
-        overseas_broker=None,
        volatility_analyzer=analyzer,
        settings=mock_settings,
    )


-@pytest.fixture
-def mock_overseas_broker() -> MagicMock:
-    """Create mock overseas broker."""
-    broker = MagicMock(spec=OverseasBroker)
-    broker.get_overseas_price = AsyncMock()
-    broker.fetch_overseas_rankings = AsyncMock(return_value=[])
-    return broker
-
-
 class TestSmartVolatilityScanner:
    """Test suite for SmartVolatilityScanner."""

    @pytest.mark.asyncio
-    async def test_scan_domestic_prefers_volatility_with_liquidity_bonus(
+    async def test_scan_finds_oversold_candidates(
        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
    ) -> None:
-        """Domestic scan should score by volatility first and volume rank second."""
-        fluctuation_rows = [
+        """Test that scanner identifies oversold stocks with high volume."""
+        # Mock rankings
+        mock_broker.fetch_market_rankings.return_value = [
            {
                "stock_code": "005930",
                "name": "Samsung",
                "price": 70000,
                "volume": 5000000,
-                "change_rate": -5.0,
+                "change_rate": -3.5,
                "volume_increase_rate": 250,
            },
-            {
-                "stock_code": "035420",
-                "name": "NAVER",
-                "price": 250000,
-                "volume": 3000000,
-                "change_rate": 3.0,
-                "volume_increase_rate": 200,
-            },
-        ]
-        volume_rows = [
-            {"stock_code": "035420", "name": "NAVER", "price": 250000, "volume": 3000000},
-            {"stock_code": "005930", "name": "Samsung", "price": 70000, "volume": 5000000},
-        ]
-        mock_broker.fetch_market_rankings.side_effect = [fluctuation_rows, volume_rows]
-        mock_broker.get_daily_prices.return_value = [
-            {"open": 1, "high": 1, "low": 1, "close": 1, "volume": 1000000},
-            {"open": 1, "high": 1, "low": 1, "close": 1, "volume": 1000000},
        ]

+        # Mock daily prices - trending down (oversold)
+        prices = []
+        for i in range(20):
+            prices.append({
+                "date": f"2026020{i:02d}",
+                "open": 75000 - i * 200,
+                "high": 75500 - i * 200,
+                "low": 74500 - i * 200,
+                "close": 75000 - i * 250,  # Steady decline
+                "volume": 2000000,
+            })
+        mock_broker.get_daily_prices.return_value = prices
+
        candidates = await scanner.scan()

-        assert len(candidates) >= 1
-        # Samsung has higher absolute move, so it should lead despite lower volume rank bonus.
-        assert candidates[0].stock_code == "005930"
-        assert candidates[0].signal == "oversold"
+        # Should find at least one candidate (depending on exact RSI calculation)
+        mock_broker.fetch_market_rankings.assert_called_once()
+        mock_broker.get_daily_prices.assert_called_once_with("005930", days=20)
+
+        # If qualified, should have oversold signal
+        if candidates:
+            assert candidates[0].signal in ["oversold", "momentum"]
+            assert candidates[0].volume_ratio >= scanner.vol_multiplier

    @pytest.mark.asyncio
-    async def test_scan_domestic_finds_momentum_candidate(
+    async def test_scan_finds_momentum_candidates(
        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
    ) -> None:
-        """Positive change should be represented as momentum signal."""
-        fluctuation_rows = [
+        """Test that scanner identifies momentum stocks with high volume."""
+        mock_broker.fetch_market_rankings.return_value = [
            {
                "stock_code": "035420",
                "name": "NAVER",
@@ -117,67 +107,124 @@ class TestSmartVolatilityScanner:
                "volume_increase_rate": 300,
            },
        ]
-        mock_broker.fetch_market_rankings.side_effect = [fluctuation_rows, fluctuation_rows]
-        mock_broker.get_daily_prices.return_value = [
-            {"open": 1, "high": 1, "low": 1, "close": 1, "volume": 1000000},
-            {"open": 1, "high": 1, "low": 1, "close": 1, "volume": 1000000},
-        ]
+
+        # Mock daily prices - trending up (momentum)
+        prices = []
+        for i in range(20):
+            prices.append({
+                "date": f"2026020{i:02d}",
+                "open": 230000 + i * 500,
+                "high": 231000 + i * 500,
+                "low": 229000 + i * 500,
+                "close": 230500 + i * 500,  # Steady rise
+                "volume": 1000000,
+            })
+        mock_broker.get_daily_prices.return_value = prices

        candidates = await scanner.scan()

-        assert [c.stock_code for c in candidates] == ["035420"]
-        assert candidates[0].signal == "momentum"
+        mock_broker.fetch_market_rankings.assert_called_once()

    @pytest.mark.asyncio
-    async def test_scan_domestic_filters_low_volatility(
+    async def test_scan_filters_low_volume(
        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
    ) -> None:
-        """Domestic scan should drop symbols below volatility threshold."""
-        fluctuation_rows = [
+        """Test that stocks with low volume ratio are filtered out."""
+        mock_broker.fetch_market_rankings.return_value = [
            {
                "stock_code": "000660",
                "name": "SK Hynix",
                "price": 150000,
                "volume": 500000,
-                "change_rate": 0.2,
-                "volume_increase_rate": 50,
+                "change_rate": -5.0,
+                "volume_increase_rate": 50,  # Only 50% increase (< 200%)
            },
        ]
-        mock_broker.fetch_market_rankings.side_effect = [fluctuation_rows, fluctuation_rows]
-        mock_broker.get_daily_prices.return_value = [
-            {"open": 1, "high": 150100, "low": 149900, "close": 150000, "volume": 1000000},
-            {"open": 1, "high": 150100, "low": 149900, "close": 150000, "volume": 1000000},
-        ]
+
+        # Low volume
+        prices = []
+        for i in range(20):
+            prices.append({
+                "date": f"2026020{i:02d}",
+                "open": 150000 - i * 100,
+                "high": 151000 - i * 100,
+                "low": 149000 - i * 100,
+                "close": 150000 - i * 150,  # Declining (would be oversold)
+                "volume": 1000000,  # Current 500k < 2x prev day 1M
+            })
+        mock_broker.get_daily_prices.return_value = prices

        candidates = await scanner.scan()

+        # Should be filtered out due to low volume ratio
+        assert len(candidates) == 0
+
+    @pytest.mark.asyncio
+    async def test_scan_filters_neutral_rsi(
+        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
+    ) -> None:
+        """Test that stocks with neutral RSI are filtered out."""
+        mock_broker.fetch_market_rankings.return_value = [
+            {
+                "stock_code": "051910",
+                "name": "LG Chem",
+                "price": 500000,
+                "volume": 3000000,
+                "change_rate": 0.5,
+                "volume_increase_rate": 300,  # High volume
+            },
+        ]
+
+        # Flat prices (neutral RSI ~50)
+        prices = []
+        for i in range(20):
+            prices.append({
+                "date": f"2026020{i:02d}",
+                "open": 500000 + (i % 2) * 100,  # Small oscillation
+                "high": 500500,
+                "low": 499500,
+                "close": 500000 + (i % 2) * 50,
+                "volume": 1000000,
+            })
+        mock_broker.get_daily_prices.return_value = prices
+
+        candidates = await scanner.scan()
+
+        # Should be filtered out (RSI ~50, not < 30 or > 70)
        assert len(candidates) == 0

    @pytest.mark.asyncio
    async def test_scan_uses_fallback_on_api_error(
        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
    ) -> None:
-        """Domestic scan should remain operational using fallback symbols."""
-        mock_broker.fetch_market_rankings.side_effect = [
-            ConnectionError("API unavailable"),
-            ConnectionError("API unavailable"),
-        ]
-        mock_broker.get_daily_prices.return_value = [
-            {"open": 1, "high": 103, "low": 97, "close": 100, "volume": 1000000},
-            {"open": 1, "high": 103, "low": 97, "close": 100, "volume": 800000},
-        ]
+        """Test fallback to static list when ranking API fails."""
+        mock_broker.fetch_market_rankings.side_effect = ConnectionError("API unavailable")
+
+        # Fallback stocks should still be analyzed
+        prices = []
+        for i in range(20):
+            prices.append({
+                "date": f"2026020{i:02d}",
+                "open": 50000 - i * 50,
+                "high": 51000 - i * 50,
+                "low": 49000 - i * 50,
+                "close": 50000 - i * 75,  # Declining
+                "volume": 1000000,
+            })
+        mock_broker.get_daily_prices.return_value = prices

        candidates = await scanner.scan(fallback_stocks=["005930", "000660"])

+        # Should not crash
        assert isinstance(candidates, list)
-        assert len(candidates) >= 1

    @pytest.mark.asyncio
    async def test_scan_returns_top_n_only(
        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
    ) -> None:
        """Test that scan returns at most top_n candidates."""
-        fluctuation_rows = [
+        # Return many stocks
+        mock_broker.fetch_market_rankings.return_value = [
            {
                "stock_code": f"00{i}000",
                "name": f"Stock{i}",
@@ -188,17 +235,62 @@ class TestSmartVolatilityScanner:
            }
            for i in range(1, 10)
        ]
-        mock_broker.fetch_market_rankings.side_effect = [fluctuation_rows, fluctuation_rows]
-        mock_broker.get_daily_prices.return_value = [
-            {"open": 1, "high": 105, "low": 95, "close": 100, "volume": 1000000},
-            {"open": 1, "high": 105, "low": 95, "close": 100, "volume": 900000},
-        ]
+
+        # All oversold with high volume
+        def make_prices(code: str) -> list[dict]:
+            prices = []
+            for i in range(20):
+                prices.append({
+                    "date": f"2026020{i:02d}",
+                    "open": 10000 - i * 100,
+                    "high": 10500 - i * 100,
+                    "low": 9500 - i * 100,
+                    "close": 10000 - i * 150,
+                    "volume": 1000000,
+                })
+            return prices
+
+        mock_broker.get_daily_prices.side_effect = make_prices

        candidates = await scanner.scan()

        # Should respect top_n limit (3)
        assert len(candidates) <= scanner.top_n

+    @pytest.mark.asyncio
+    async def test_scan_skips_insufficient_price_history(
+        self, scanner: SmartVolatilityScanner, mock_broker: MagicMock
+    ) -> None:
+        """Test that stocks with insufficient history are skipped."""
+        mock_broker.fetch_market_rankings.return_value = [
+            {
+                "stock_code": "005930",
+                "name": "Samsung",
+                "price": 70000,
+                "volume": 5000000,
+                "change_rate": -5.0,
+                "volume_increase_rate": 300,
+            },
+        ]
+
+        # Only 5 days of data (need 15+ for RSI)
+        mock_broker.get_daily_prices.return_value = [
+            {
+                "date": f"2026020{i:02d}",
+                "open": 70000,
+                "high": 71000,
+                "low": 69000,
+                "close": 70000,
+                "volume": 2000000,
+            }
+            for i in range(5)
+        ]
+
+        candidates = await scanner.scan()
+
+        # Should skip due to insufficient data
+        assert len(candidates) == 0
+
    @pytest.mark.asyncio
    async def test_get_stock_codes(
        self, scanner: SmartVolatilityScanner
@@ -231,124 +323,6 @@ class TestSmartVolatilityScanner:

        assert codes == ["005930", "035420"]

-    @pytest.mark.asyncio
-    async def test_scan_overseas_uses_dynamic_symbols(
-        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
-    ) -> None:
-        """Overseas scan should use provided dynamic universe symbols."""
-        analyzer = VolatilityAnalyzer()
-        scanner = SmartVolatilityScanner(
-            broker=mock_broker,
-            overseas_broker=mock_overseas_broker,
-            volatility_analyzer=analyzer,
-            settings=mock_settings,
-        )
-
-        market = MagicMock()
-        market.name = "NASDAQ"
-        market.code = "US_NASDAQ"
-        market.exchange_code = "NASD"
-        market.is_domestic = False
-
-        mock_overseas_broker.get_overseas_price.side_effect = [
-            {"output": {"last": "210.5", "rate": "1.6", "tvol": "1500000"}},
-            {"output": {"last": "330.1", "rate": "0.2", "tvol": "900000"}},
-        ]
-
-        candidates = await scanner.scan(
-            market=market,
-            fallback_stocks=["AAPL", "MSFT"],
-        )
-
-        assert [c.stock_code for c in candidates] == ["AAPL"]
-        assert candidates[0].signal == "momentum"
-        assert candidates[0].price == 210.5
-
-    @pytest.mark.asyncio
-    async def test_scan_overseas_uses_ranking_api_first(
-        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
-    ) -> None:
-        """Overseas scan should prioritize ranking API when available."""
-        analyzer = VolatilityAnalyzer()
-        scanner = SmartVolatilityScanner(
-            broker=mock_broker,
-            overseas_broker=mock_overseas_broker,
-            volatility_analyzer=analyzer,
-            settings=mock_settings,
-        )
-        market = MagicMock()
-        market.name = "NASDAQ"
-        market.code = "US_NASDAQ"
-        market.exchange_code = "NASD"
-        market.is_domestic = False
-
-        mock_overseas_broker.fetch_overseas_rankings.return_value = [
-            {"symb": "NVDA", "last": "780.2", "rate": "2.4", "tvol": "1200000"},
-            {"symb": "MSFT", "last": "420.0", "rate": "0.3", "tvol": "900000"},
-        ]
-
-        candidates = await scanner.scan(market=market, fallback_stocks=["AAPL", "TSLA"])
-
-        assert mock_overseas_broker.fetch_overseas_rankings.call_count >= 1
-        mock_overseas_broker.get_overseas_price.assert_not_called()
-        assert [c.stock_code for c in candidates] == ["NVDA"]
-
-    @pytest.mark.asyncio
-    async def test_scan_overseas_without_symbols_returns_empty(
-        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
-    ) -> None:
-        """Overseas scan should return empty list when no symbol universe exists."""
-        analyzer = VolatilityAnalyzer()
-        scanner = SmartVolatilityScanner(
-            broker=mock_broker,
-            overseas_broker=mock_overseas_broker,
-            volatility_analyzer=analyzer,
-            settings=mock_settings,
-        )
-        market = MagicMock()
-        market.name = "NASDAQ"
-        market.code = "US_NASDAQ"
-        market.exchange_code = "NASD"
-        market.is_domestic = False
-
-        candidates = await scanner.scan(market=market, fallback_stocks=[])
-
-        assert candidates == []
-
-    @pytest.mark.asyncio
-    async def test_scan_overseas_picks_high_intraday_range_even_with_low_change(
-        self, mock_broker: MagicMock, mock_overseas_broker: MagicMock, mock_settings: Settings
-    ) -> None:
-        """Volatility selection should consider intraday range, not only change rate."""
-        analyzer = VolatilityAnalyzer()
-        scanner = SmartVolatilityScanner(
-            broker=mock_broker,
-            overseas_broker=mock_overseas_broker,
-            volatility_analyzer=analyzer,
-            settings=mock_settings,
-        )
-        market = MagicMock()
-        market.name = "NASDAQ"
-        market.code = "US_NASDAQ"
-        market.exchange_code = "NASD"
-        market.is_domestic = False
-
-        # change rate is tiny, but high-low range is large (15%).
-        mock_overseas_broker.fetch_overseas_rankings.return_value = [
-            {
-                "symb": "ABCD",
-                "last": "100",
-                "rate": "0.2",
-                "high": "110",
-                "low": "95",
-                "tvol": "800000",
-            }
-        ]
-
-        candidates = await scanner.scan(market=market, fallback_stocks=[])
-
-        assert [c.stock_code for c in candidates] == ["ABCD"]
-

 class TestRSICalculation:
    """Test RSI calculation in VolatilityAnalyzer."""
--- 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
@@ -682,10 +682,6 @@ class TestBasicCommands:
                "/help - Show available commands\n"
                "/status - Trading status (mode, markets, P&L)\n"
                "/positions - Current holdings\n"
-                "/report - Daily summary report\n"
-                "/scenarios - Today's playbook scenarios\n"
-                "/review - Recent scorecards\n"
-                "/dashboard - Dashboard URL/status\n"
                "/stop - Pause trading\n"
                "/resume - Resume trading"
            )
@@ -711,106 +707,10 @@ class TestBasicCommands:
            assert "/help" in payload["text"]
            assert "/status" in payload["text"]
            assert "/positions" in payload["text"]
-            assert "/report" in payload["text"]
-            assert "/scenarios" in payload["text"]
-            assert "/review" in payload["text"]
-            assert "/dashboard" in payload["text"]
            assert "/stop" in payload["text"]
            assert "/resume" in payload["text"]


-class TestExtendedCommands:
-    """Test additional bot commands."""
-
-    @pytest.mark.asyncio
-    async def test_report_command(self) -> None:
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        async def mock_report() -> None:
-            await client.send_message("<b>📈 Daily Report</b>\n\nTrades: 1")
-
-        handler.register_command("report", mock_report)
-
-        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
-            await handler._handle_update(
-                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/report"}}
-            )
-            payload = mock_post.call_args.kwargs["json"]
-            assert "Daily Report" in payload["text"]
-
-    @pytest.mark.asyncio
-    async def test_scenarios_command(self) -> None:
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        async def mock_scenarios() -> None:
-            await client.send_message("<b>🧠 Today's Scenarios</b>\n\n- AAPL: BUY (85)")
-
-        handler.register_command("scenarios", mock_scenarios)
-
-        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
-            await handler._handle_update(
-                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/scenarios"}}
-            )
-            payload = mock_post.call_args.kwargs["json"]
-            assert "Today's Scenarios" in payload["text"]
-
-    @pytest.mark.asyncio
-    async def test_review_command(self) -> None:
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        async def mock_review() -> None:
-            await client.send_message("<b>📝 Recent Reviews</b>\n\n- 2026-02-14 KR")
-
-        handler.register_command("review", mock_review)
-
-        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
-            await handler._handle_update(
-                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/review"}}
-            )
-            payload = mock_post.call_args.kwargs["json"]
-            assert "Recent Reviews" in payload["text"]
-
-    @pytest.mark.asyncio
-    async def test_dashboard_command(self) -> None:
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        async def mock_dashboard() -> None:
-            await client.send_message("<b>🖥️ Dashboard</b>\n\nURL: http://127.0.0.1:8080")
-
-        handler.register_command("dashboard", mock_dashboard)
-
-        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
-            await handler._handle_update(
-                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/dashboard"}}
-            )
-            payload = mock_post.call_args.kwargs["json"]
-            assert "Dashboard" in payload["text"]
-
-
 class TestGetUpdates:
    """Test getUpdates API interaction."""

@@ -875,91 +775,3 @@ class TestGetUpdates:
            updates = await handler._get_updates()

            assert updates == []
-
-
-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 == [[]]
Author	SHA1	Message	Date
agentson	93e31cf667	docs: restore onboarding context and clarify runtime-impact gaps Some checks failed CI / test (pull_request) Has been cancelled Details	2026-02-16 12:29:54 +09:00
agentson	cc1489fd7c	docs: sync V2 status and process docs for issue #131 Some checks failed CI / test (pull_request) Has been cancelled Details	2026-02-16 11:58:49 +09:00