feat: unify domestic scanner and sizing; update docs

.env.example

@@ -1,82 +1,36 @@
-# ============================================================
-# The Ouroboros — Environment Configuration
-# ============================================================
-# Copy this file to .env and fill in your values.
-# Lines starting with # are comments.
-
-# ============================================================
 # Korea Investment Securities API
-# ============================================================
 KIS_APP_KEY=your_app_key_here
 KIS_APP_SECRET=your_app_secret_here
 KIS_ACCOUNT_NO=12345678-01
+KIS_BASE_URL=https://openapivts.koreainvestment.com:9443
 
-# Paper trading (VTS): https://openapivts.koreainvestment.com:29443
-# Live trading:        https://openapi.koreainvestment.com:9443
-KIS_BASE_URL=https://openapivts.koreainvestment.com:29443
-
-# ============================================================
-# Trading Mode
-# ============================================================
-# paper = 모의투자 (safe for testing), live = 실전투자 (real money)
-MODE=paper
-
-# daily = batch per session, realtime = per-stock continuous scan
-TRADE_MODE=daily
-
-# Comma-separated market codes: KR, US, JP, HK, CN, VN
-ENABLED_MARKETS=KR,US
-
-# Simulated USD cash for paper (VTS) overseas trading.
-# VTS overseas balance API often returns 0; this value is used as fallback.
-# Set to 0 to disable fallback (not used in live mode).
-PAPER_OVERSEAS_CASH=50000.0
-
-# ============================================================
 # Google Gemini
-# ============================================================
 GEMINI_API_KEY=your_gemini_api_key_here
-# Recommended: gemini-2.0-flash-exp or gemini-1.5-pro
-GEMINI_MODEL=gemini-2.0-flash-exp
+GEMINI_MODEL=gemini-pro
 
-# ============================================================
 # Risk Management
-# ============================================================
 CIRCUIT_BREAKER_PCT=-3.0
 FAT_FINGER_PCT=30.0
 CONFIDENCE_THRESHOLD=80
 
-# ============================================================
 # Database
-# ============================================================
 DB_PATH=data/trade_logs.db
 
-# ============================================================
-# Rate Limiting
-# ============================================================
-# KIS API real limit is ~2 RPS. Keep at 2.0 for maximum safety.
-# Increasing this risks EGW00201 "초당 거래건수 초과" errors.
-RATE_LIMIT_RPS=2.0
+# Rate Limiting (requests per second for KIS API)
+# Reduced to 5.0 to avoid "초당 거래건수 초과" errors (EGW00201)
+RATE_LIMIT_RPS=5.0
 
-# ============================================================
-# External Data APIs (optional)
-# ============================================================
+# Trading Mode (paper / live)
+MODE=paper
+
+# External Data APIs (optional — for enhanced decision-making)
 # NEWS_API_KEY=your_news_api_key_here
 # NEWS_API_PROVIDER=alphavantage
 # MARKET_DATA_API_KEY=your_market_data_key_here
 
-# ============================================================
 # Telegram Notifications (optional)
-# ============================================================
 # Get bot token from @BotFather on Telegram
 # Get chat ID from @userinfobot or your chat
 # TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
 # TELEGRAM_CHAT_ID=123456789
 # TELEGRAM_ENABLED=true
-
-# ============================================================
-# Dashboard (optional)
-# ============================================================
-# DASHBOARD_ENABLED=false
-# DASHBOARD_HOST=127.0.0.1
-# DASHBOARD_PORT=8080

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)
@@ -94,7 +87,6 @@ Smart Scanner runs in `TRADE_MODE=realtime` only. Daily mode uses static watchli
 - **[Testing](docs/testing.md)** — Test structure, coverage requirements, writing tests
 - **[Agent Policies](docs/agents.md)** — Prime directives, constraints, prohibited actions
 - **[Requirements Log](docs/requirements-log.md)** — User requirements and feedback tracking
-- **[Live Trading Checklist](docs/live-trading-checklist.md)** — 모의→실전 전환 체크리스트
 
 ## Core Principles
 
@@ -117,23 +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
 ```
 
@@ -145,7 +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)
@@ -171,7 +156,7 @@ Markets auto-detected based on timezone and enabled in `ENABLED_MARKETS` env var
 - `src/core/risk_manager.py` is **READ-ONLY** — changes require human approval
 - Circuit breaker at -3.0% P&L — may only be made **stricter**
 - Fat-finger protection: max 30% of cash per order — always enforced
-- Confidence 임계값 (market_outlook별, 낮출 수 없음): BEARISH ≥ 90, NEUTRAL/기본 ≥ 80, BULLISH ≥ 75
+- Confidence < 80 → force HOLD — cannot be weakened
 - All code changes → corresponding tests → coverage ≥ 80%
 
 ## Contributing

README.md

@@ -10,41 +10,28 @@ KIS(한국투자증권) API로 매매하고, Google Gemini로 판단하며, 자
 │  (매매 실행) │     │ (거래 루프)  │     │  (의사결정)  │
 └─────────────┘     └──────┬──────┘     └─────────────┘
                            │
-              ┌────────────┼────────────┐
-              │            │            │
-       ┌──────┴──────┐ ┌──┴───┐ ┌──────┴──────┐
-       │Risk Manager │ │  DB  │ │  Telegram   │
-       │  (안전장치)  │ │      │ │ (알림+명령)  │
-       └──────┬──────┘ └──────┘ └─────────────┘
-              │
-     ┌────────┼────────┐
-     │        │        │
-┌────┴────┐┌──┴──┐┌────┴─────┐
-│Strategy ││Ctx  ││Evolution │
-│(플레이북)││(메모리)││ (진화)   │
-└─────────┘└─────┘└──────────┘
+                    ┌──────┴──────┐
+                    │Risk Manager │
+                    │  (안전장치)  │
+                    └──────┬──────┘
+                           │
+                    ┌──────┴──────┐
+                    │  Evolution  │
+                    │ (전략 진화)  │
+                    └─────────────┘
 ```
 
-**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 모듈
 
-| 모듈 | 위치 | 설명 |
+| 모듈 | 파일 | 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) |
+| 설정 | `src/config.py` | Pydantic 기반 환경변수 로딩 및 타입 검증 |
+| 브로커 | `src/broker/kis_api.py` | KIS API 비동기 래퍼 (토큰 갱신, 레이트 리미터, 해시키) |
+| 두뇌 | `src/brain/gemini_client.py` | Gemini 프롬프트 구성 및 JSON 응답 파싱 |
+| 방패 | `src/core/risk_manager.py` | 서킷 브레이커 + 팻 핑거 체크 |
+| 알림 | `src/notifications/telegram_client.py` | 텔레그램 실시간 거래 알림 (선택사항) |
+| 진화 | `src/evolution/optimizer.py` | 실패 패턴 분석 → 새 전략 생성 → 테스트 → PR |
+| DB | `src/db.py` | SQLite 거래 로그 기록 |
 
 ## 안전장치
 
@@ -55,7 +42,6 @@ KIS(한국투자증권) API로 매매하고, Google Gemini로 판단하며, 자
 | 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
 
@@ -81,11 +67,7 @@ pytest -v --cov=src --cov-report=term-missing
 ### 4. 실행 (모의투자)
 
 ```bash
-# 기본 실행
 python -m src.main --mode=paper
-
-# 대시보드 활성화
-python -m src.main --mode=paper --dashboard
 ```
 
 ### 5. Docker 실행
@@ -94,20 +76,7 @@ python -m src.main --mode=paper --dashboard
 docker compose up -d ouroboros
 ```
 
-## 지원 시장
-
-| 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 |
-
-`ENABLED_MARKETS` 환경변수로 활성 시장 선택 (기본: `KR,US`).
-
-## 텔레그램 (선택사항)
+## 텔레그램 알림 (선택사항)
 
 거래 실행, 서킷 브레이커 발동, 시스템 상태 등을 텔레그램으로 실시간 알림 받을 수 있습니다.
 
@@ -133,51 +102,25 @@ docker compose up -d ouroboros
 - 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.
+**안전장치**: 알림 실패해도 거래는 계속 진행됩니다. 텔레그램 API 오류나 설정 누락이 있어도 거래 시스템은 정상 작동합니다.
 
 ## 테스트
 
-551개 테스트가 25개 파일에 걸쳐 구현되어 있습니다. 최소 커버리지 80%.
+35개 테스트가 TDD 방식으로 구현 전에 먼저 작성되었습니다.
 
 ```
-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
+tests/test_risk.py   — 서킷 브레이커, 팻 핑거, 통합 검증 (11개)
+tests/test_broker.py — 토큰 관리, 타임아웃, HTTP 에러, 해시키 (6개)
+tests/test_brain.py  — JSON 파싱, 신뢰도 임계값, 비정상 응답 처리 (15개)
 ```
 
-**상세**: [docs/testing.md](docs/testing.md)
-
 ## 기술 스택
 
 - **언어**: Python 3.11+ (asyncio 기반)
-- **브로커**: KIS Open API (REST, 국내+해외)
+- **브로커**: KIS Open API (REST)
 - **AI**: Google Gemini Pro
-- **DB**: SQLite (5개 테이블: trades, contexts, decision_logs, playbooks, context_metadata)
-- **대시보드**: FastAPI + uvicorn
-- **검증**: pytest + coverage (551 tests)
+- **DB**: SQLite
+- **검증**: pytest + coverage
 - **CI/CD**: GitHub Actions
 - **배포**: Docker + Docker Compose
 
@@ -185,50 +128,27 @@ tests/test_telegram.py           — 텔레그램 알림 (25개)
 
 ```
 The-Ouroboros/
+├── .github/workflows/ci.yml     # CI 파이프라인
 ├── 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
+│   ├── agents.md                # AI 에이전트 페르소나 정의
+│   └── skills.md                # 사용 가능한 도구 목록
 ├── 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)
+│   ├── config.py                      # Pydantic 설정
+│   ├── logging_config.py              # JSON 구조화 로깅
+│   ├── db.py                          # SQLite 거래 기록
+│   ├── main.py                        # 비동기 거래 루프
+│   ├── broker/kis_api.py              # KIS API 클라이언트
+│   ├── brain/gemini_client.py         # Gemini 의사결정 엔진
+│   ├── core/risk_manager.py           # 리스크 관리
+│   ├── notifications/telegram_client.py # 텔레그램 알림
+│   ├── evolution/optimizer.py         # 전략 진화 엔진
+│   └── strategies/base.py             # 전략 베이스 클래스
+├── tests/                       # TDD 테스트 스위트
 ├── Dockerfile                   # 멀티스테이지 빌드
 ├── docker-compose.yml           # 서비스 오케스트레이션
 └── pyproject.toml               # 의존성 및 도구 설정
 ```
 
-## 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.

docs/architecture.md

@@ -2,9 +2,7 @@
 
 ## 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).
-
-**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.
+Self-evolving AI trading agent for global stock markets via KIS (Korea Investment & Securities) API. The main loop in `src/main.py` orchestrates four components across multiple markets with two trading modes: daily (batch API calls) or realtime (per-stock decisions).
 
 ## Trading Modes
 
@@ -48,11 +46,9 @@ High-frequency trading with individual stock analysis:
 **KISBroker** (`kis_api.py`) — Async KIS API client for domestic Korean market
 
 - Automatic OAuth token refresh (valid for 24 hours)
-- Leaky-bucket rate limiter (configurable RPS, default 2.0)
+- Leaky-bucket rate limiter (10 requests per second)
 - 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
 
 **OverseasBroker** (`overseas.py`) — KIS overseas stock API wrapper
 
@@ -67,7 +63,10 @@ High-frequency trading with individual stock analysis:
 - `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)
+
+**New API Methods** (added in v0.9.0):
+- `fetch_market_rankings()` — Fetch volume surge rankings from KIS API
+- `get_daily_prices()` — Fetch OHLCV history for technical analysis
 
 **Overseas Ranking API Methods** (added in v0.10.x):
 - `fetch_overseas_rankings()` — Fetch overseas ranking universe (fluctuation / volume)
@@ -105,9 +104,9 @@ High-frequency trading with individual stock analysis:
 - Fast Python-based filtering before expensive AI judgment
 - Logs selection context (RSI-compatible proxy, volume_ratio, signal, score) for Evolution system
 
-### 3. Brain (`src/brain/`)
+### 3. Brain (`src/brain/gemini_client.py`)
 
-**GeminiClient** (`gemini_client.py`) — AI decision engine powered by Google Gemini
+**GeminiClient** — AI decision engine powered by Google Gemini
 
 - Constructs structured prompts from market data
 - Parses JSON responses into `TradeDecision` objects (`action`, `confidence`, `rationale`)
@@ -115,20 +114,11 @@ High-frequency trading with individual stock analysis:
 - Falls back to safe HOLD on any parse/API error
 - Handles markdown-wrapped JSON, malformed responses, invalid actions
 
-**PromptOptimizer** (`prompt_optimizer.py`) — Token efficiency optimization
-
-- Reduces prompt size while preserving decision quality
-- Caches optimized prompts
-
-**ContextSelector** (`context_selector.py`) — Relevant context selection for prompts
-
-- Selects appropriate context layers for current market conditions
-
 ### 4. Risk Manager (`src/core/risk_manager.py`)
 
 **RiskManager** — Safety circuit breaker and order validation
 
-> **READ-ONLY by policy** (see [`docs/agents.md`](./agents.md))
+⚠️ **READ-ONLY by policy** (see [`docs/agents.md`](./agents.md))
 
 - **Circuit Breaker**: Halts all trading via `SystemExit` when daily P&L drops below -3.0%
   - Threshold may only be made stricter, never relaxed
@@ -136,79 +126,7 @@ High-frequency trading with individual stock analysis:
 - **Fat-Finger Protection**: Rejects orders exceeding 30% of available cash
   - Must always be enforced, cannot be disabled
 
-### 5. Strategy (`src/strategy/`)
-
-**Pre-Market Planner** (`pre_market_planner.py`) — AI playbook generation
-
-- 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
-
-**Scenario Engine** (`scenario_engine.py`) — Local scenario matching
-
-- 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)
-
-**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`)
+### 5. Notifications (`src/notifications/telegram_client.py`)
 
 **TelegramClient** — Real-time event notifications via Telegram Bot API
 
@@ -216,13 +134,7 @@ High-frequency trading with individual stock analysis:
 - 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)
+- Gracefully handles API errors, network timeouts, invalid tokens
 
 **Notification Types:**
 - Trade execution (BUY/SELL with confidence)
@@ -230,12 +142,12 @@ High-frequency trading with individual stock analysis:
 - 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/`)
+**Setup:** See [src/notifications/README.md](../src/notifications/README.md) for bot creation and configuration.
 
-**StrategyOptimizer** (`optimizer.py`) — Self-improvement loop
+### 6. Evolution (`src/evolution/optimizer.py`)
+
+**StrategyOptimizer** — Self-improvement loop
 
 - Analyzes high-confidence losing trades from SQLite
 - Asks Gemini to generate new `BaseStrategy` subclasses
@@ -243,136 +155,22 @@ High-frequency trading with individual stock analysis:
 - 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)                            │
+│ Main Loop (60s cycle per market)                           │
 └─────────────────────────────────────────────────────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Market Schedule Check            │
-        │ - Get open markets               │
-        │ - Filter by enabled markets      │
-        │ - Wait if all closed             │
-        └──────────────────┬───────────────┘
+        │ Market Schedule Check             │
+        │ - Get open markets                │
+        │ - Filter by enabled markets       │
+        │ - Wait if all closed              │
+        └──────────────────┬────────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
@@ -384,57 +182,74 @@ High-frequency trading with individual stock analysis:
         │   + volatility-first scoring     │
         │ - Fallback: dynamic universe     │
         │ - Return top 3 qualified stocks  │
-        └──────────────────┬───────────────┘
+        └──────────────────┬────────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ For Each Qualified Candidate     │
-        └──────────────────┬───────────────┘
+        │ 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           │
-        └──────────────────┬───────────────┘
+        │ Calculate P&L                     │
+        │ pnl_pct = (eval - cost) / cost   │
+        └──────────────────┬────────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Risk Manager: Validate Order     │
-        │ - Check circuit breaker          │
-        │ - Check fat-finger limit         │
-        └──────────────────┬───────────────┘
+        │ Brain: Get Decision (AI)          │
+        │ - Build prompt with market data   │
+        │ - Call Gemini API                 │
+        │ - Parse JSON response             │
+        │ - Return TradeDecision            │
+        └──────────────────┬────────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Broker: Execute Order            │
-        │ - Domestic: send_order()         │
-        │ - Overseas: send_overseas_order()│
-        └──────────────────┬───────────────┘
+        │ Risk Manager: Validate Order      │
+        │ - Check circuit breaker           │
+        │ - Check fat-finger limit          │
+        │ - Raise if validation fails       │
+        └──────────────────┬────────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Decision Logger + Notifications  │
-        │ - Log trade to SQLite            │
-        │ - selection_context (JSON)       │
-        │ - Telegram notification          │
-        └──────────────────────────────────┘
+        │ Broker: Execute Order             │
+        │ - Domestic: send_order()          │
+        │ - Overseas: send_overseas_order() │
+        └──────────────────┬────────────────┘
+                           │
+                           ▼
+        ┌──────────────────────────────────┐
+        │ Notifications: Send Alert         │
+        │ - Trade execution notification    │
+        │ - Non-blocking (errors logged)    │
+        │ - Rate-limited to 1/sec           │
+        └──────────────────┬────────────────┘
+                           │
+                           ▼
+        ┌──────────────────────────────────┐
+        │ Database: Log Trade               │
+        │ - SQLite (data/trades.db)         │
+        │ - Track: action, confidence,      │
+        │   rationale, market, exchange     │
+        │ - NEW: selection_context (JSON)   │
+        │   - RSI, volume_ratio, signal     │
+        │   - For Evolution optimization    │
+        └───────────────────────────────────┘
 ```
 
 ## Database Schema
 
-**SQLite** (`src/db.py`) — Database: `data/trades.db`
+**SQLite** (`src/db.py`)
 
-### trades
 ```sql
 CREATE TABLE trades (
     id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -446,73 +261,25 @@ CREATE TABLE trades (
     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
+    market TEXT DEFAULT 'KR',       -- KR | US_NASDAQ | JP | etc.
+    exchange_code TEXT DEFAULT 'KRX', -- KRX | NASD | NYSE | etc.
+    selection_context TEXT          -- JSON: {rsi, volume_ratio, signal, score}
 );
 ```
 
-### 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
+**Selection Context** (new in v0.9.0): Stores scanner selection criteria as JSON:
+```json
+{
+  "rsi": 28.5,
+  "volume_ratio": 2.7,
+  "signal": "oversold",
+  "score": 85.2
+}
 ```
 
-### 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
-```
+Enables Evolution system to analyze correlation between selection criteria and trade outcomes.
 
-### 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
-);
-```
+Auto-migration: Adds `market`, `exchange_code`, and `selection_context` columns if missing for backward compatibility.
 
 ## Configuration
 
@@ -527,70 +294,31 @@ KIS_APP_SECRET=your_app_secret
 KIS_ACCOUNT_NO=XXXXXXXX-XX
 GEMINI_API_KEY=your_gemini_key
 
-# Optional — Trading Mode
+# Optional
 MODE=paper                    # paper | live
+DB_PATH=data/trades.db
+CONFIDENCE_THRESHOLD=80
+MAX_LOSS_PCT=3.0
+MAX_ORDER_PCT=30.0
+ENABLED_MARKETS=KR,US_NASDAQ  # Comma-separated market codes
+
+# Trading Mode (API efficiency)
 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 Notifications (optional)
 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)
+# Smart Scanner (optional, realtime mode only)
+SCANNER_TOP_N=3              # Max qualified candidates per scan
 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
@@ -635,9 +363,4 @@ Tests use in-memory SQLite (`DB_PATH=":memory:"`) and dummy credentials via `tes
 - 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.
+**Guarantee**: Notification failures never interrupt trading operations.

docs/commands.md

@@ -119,7 +119,7 @@ No decorator needed for async tests.
 # Install all dependencies (production + dev)
 pip install -e ".[dev]"
 
-# Run full test suite with coverage (551 tests across 25 files)
+# Run full test suite with coverage
 pytest -v --cov=src --cov-report=term-missing
 
 # Run a single test file
@@ -137,82 +137,11 @@ mypy src/ --strict
 # Run the trading agent
 python -m src.main --mode=paper
 
-# Run with dashboard enabled
-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
 ```
 
-## Dashboard
-
-The FastAPI dashboard provides read-only monitoring of the trading system.
-
-### Starting the Dashboard
-
-```bash
-# Via CLI flag
-python -m src.main --mode=paper --dashboard
-
-# Via environment variable
-DASHBOARD_ENABLED=true python -m src.main --mode=paper
-```
-
-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`.
-
-## KIS API TR_ID 참조 문서
-
-**TR_ID를 추가하거나 수정할 때 반드시 공식 문서를 먼저 확인할 것.**
-
-공식 문서: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx`
-
-> ⚠️ 커뮤니티 블로그, GitHub 예제 등 비공식 자료의 TR_ID는 오래되거나 틀릴 수 있음.
-> 실제로 `VTTT1006U`(미국 매도 — 잘못됨)가 오랫동안 코드에 남아있던 사례가 있음 (Issue #189).
-
-### 주요 TR_ID 목록
-
-| 구분 | 모의투자 TR_ID | 실전투자 TR_ID | 시트명 |
-|------|---------------|---------------|--------|
-| 해외주식 매수 (미국) | `VTTT1002U` | `TTTT1002U` | 해외주식 주문 |
-| 해외주식 매도 (미국) | `VTTT1001U` | `TTTT1006U` | 해외주식 주문 |
-
-새로운 TR_ID가 필요할 때:
-1. 위 xlsx 파일에서 해당 거래 유형의 시트를 찾는다.
-2. 모의투자(`VTTT`) / 실전투자(`TTTT`) 컬럼을 구분하여 정확한 값을 사용한다.
-3. 코드에 출처 주석을 남긴다: `# Source: 한국투자증권_오픈API_전체문서 — '<시트명>' 시트`
-
 ## Environment Setup
 
 ```bash

docs/live-trading-checklist.md

@@ -1,131 +0,0 @@
-# 실전 전환 체크리스트
-
-모의 거래(paper)에서 실전(live)으로 전환하기 전에 아래 항목을 **순서대로** 모두 확인하세요.
-
----
-
-## 1. 사전 조건
-
-### 1-1. KIS OpenAPI 실전 계좌 준비
-- [ ] 한국투자증권 계좌 개설 완료 (일반 위탁 계좌)
-- [ ] OpenAPI 실전 사용 신청 (KIS 홈페이지 → Open API → 서비스 신청)
-- [ ] 실전용 APP_KEY / APP_SECRET 발급 완료
-- [ ] KIS_ACCOUNT_NO 형식 확인: `XXXXXXXX-XX` (8자리-2자리)
-
-### 1-2. 리스크 파라미터 검토
-- [ ] `CIRCUIT_BREAKER_PCT` 확인: 기본값 -3.0% (더 엄격하게 조정 권장)
-- [ ] `FAT_FINGER_PCT` 확인: 기본값 30.0% (1회 주문 최대 잔고 대비 %)
-- [ ] `CONFIDENCE_THRESHOLD` 확인: BEARISH ≥ 90, NEUTRAL ≥ 80, BULLISH ≥ 75
-- [ ] 초기 투자금 결정 및 해외 주식 운용 한도 설정
-
-### 1-3. 시스템 요건
-- [ ] 커버리지 80% 이상 유지 확인: `pytest --cov=src`
-- [ ] 타입 체크 통과: `mypy src/ --strict`
-- [ ] Lint 통과: `ruff check src/ tests/`
-
----
-
-## 2. 환경 설정
-
-### 2-1. `.env` 파일 수정
-
-```bash
-# 1. KIS 실전 URL로 변경 (모의: openapivts 포트 29443)
-KIS_BASE_URL=https://openapi.koreainvestment.com:9443
-
-# 2. 실전 APP_KEY / APP_SECRET으로 교체
-KIS_APP_KEY=<실전_APP_KEY>
-KIS_APP_SECRET=<실전_APP_SECRET>
-KIS_ACCOUNT_NO=<실전_계좌번호>
-
-# 3. 모드를 live로 변경
-MODE=live
-
-# 4. PAPER_OVERSEAS_CASH 비활성화 (live 모드에선 무시되지만 명시적으로 0 설정)
-PAPER_OVERSEAS_CASH=0
-```
-
-> ⚠️ `KIS_BASE_URL` 포트 주의:
-> - **모의(VTS)**: `https://openapivts.koreainvestment.com:29443`
-> - **실전**: `https://openapi.koreainvestment.com:9443`
-
-### 2-2. TR_ID 자동 분기 확인
-
-아래 TR_ID는 `MODE` 값에 따라 코드에서 **자동으로 선택**됩니다.
-별도 설정 불필요하나, 문제 발생 시 아래 표를 참조하세요.
-
-| 구분 | 모의 TR_ID | 실전 TR_ID |
-|------|-----------|-----------|
-| 국내 잔고 조회 | `VTTC8434R` | `TTTC8434R` |
-| 국내 현금 매수 | `VTTC0012U` | `TTTC0012U` |
-| 국내 현금 매도 | `VTTC0011U` | `TTTC0011U` |
-| 해외 잔고 조회 | `VTTS3012R` | `TTTS3012R` |
-| 해외 매수 | `VTTT1002U` | `TTTT1002U` |
-| 해외 매도 | `VTTT1001U` | `TTTT1006U` |
-
-> **출처**: `docs/한국투자증권_오픈API_전체문서_20260221_030000.xlsx` (공식 문서 기준)
-
----
-
-## 3. 최종 확인
-
-### 3-1. 실전 시작 전 점검
-- [ ] DB 백업 완료: `data/trade_logs.db` → `data/backups/`
-- [ ] Telegram 알림 설정 확인 (실전에서는 알림이 더욱 중요)
-- [ ] 소액으로 첫 거래 진행 후 TR_ID/계좌 정상 동작 확인
-
-### 3-2. 실행 명령
-
-```bash
-# 실전 모드로 실행
-python -m src.main --mode=live
-
-# 대시보드 함께 실행 (별도 터미널에서 모니터링)
-python -m src.main --mode=live --dashboard
-```
-
-### 3-3. 실전 시작 직후 확인 사항
-- [ ] 로그에 `MODE=live` 출력 확인
-- [ ] 첫 잔고 조회 성공 (ConnectionError 없음)
-- [ ] Telegram 알림 수신 확인 ("System started")
-- [ ] 첫 주문 후 KIS 앱에서 체결 내역 확인
-
----
-
-## 4. 비상 정지 방법
-
-### 즉각 정지
-```bash
-# 터미널에서 Ctrl+C (정상 종료 트리거)
-# 또는 Telegram 봇 명령:
-/stop
-```
-
-### Circuit Breaker 발동 시
-- CB가 발동되면 자동으로 거래 중단 및 Telegram 알림 전송
-- CB 임계값: `CIRCUIT_BREAKER_PCT` (기본 -3.0%)
-- **임계값은 엄격하게만 조정 가능** (더 낮은 음수 값으로만 변경)
-
----
-
-## 5. 롤백 절차
-
-실전 전환 후 문제 발생 시:
-
-```bash
-# 1. 즉시 .env에서 MODE=paper로 복원
-# 2. 재시작
-python -m src.main --mode=paper
-
-# 3. DB에서 최근 거래 확인
-sqlite3 data/trade_logs.db "SELECT * FROM trades ORDER BY id DESC LIMIT 20;"
-```
-
----
-
-## 관련 문서
-
-- [시스템 아키텍처](architecture.md)
-- [워크플로우 가이드](workflow.md)
-- [재해 복구](disaster_recovery.md)
-- [Agent 제약 조건](agents.md)

docs/requirements-log.md

@@ -7,32 +7,6 @@
 
 ---
 
-## 2026-02-21
-
-### 거래 상태 확인 중 발견된 버그 (#187)
-
-- 거래 상태 점검 요청 → SELL 주문(손절/익절)이 Fat Finger에 막혀 전혀 실행 안 됨 발견
-- **#187 (Critical)**: SELL 주문에서 Fat Finger 오탐 — `order_amount/total_cash > 30%`가 SELL에도 적용되어 대형 포지션 매도 불가
-  - JELD stop-loss -6.20% → 차단, RXT take-profit +46.13% → 차단
-  - 수정: SELL은 `check_circuit_breaker`만 호출, `validate_order`(Fat Finger 포함) 미호출
-
----
-
-## 2026-02-20
-
-### 지속적 모니터링 및 개선점 도출 (이슈 #178~#182)
-
-- Dashboard 포함해서 실행하며 간헐적 문제 모니터링 및 개선점 자동 도출 요청
-- 모니터링 결과 발견된 이슈 목록:
-  - **#178**: uvicorn 미설치 → dashboard 미작동 + 오해의 소지 있는 시작 로그 → uvicorn 설치 완료
-  - **#179 (Critical)**: 잔액 부족 주문 실패 후 매 사이클마다 무한 재시도 (MLECW 20분 이상 반복)
-  - **#180**: 다중 인스턴스 실행 시 Telegram 409 충돌
-  - **#181**: implied_rsi 공식 포화 문제 (change_rate≥12.5% → RSI=100)
-  - **#182 (Critical)**: 보유 종목이 SmartScanner 변동성 필터에 걸려 SELL 신호 미생성 → SELL 체결 0건, 잔고 소진
-- 요구사항: 모니터링 자동화 및 주기적 개선점 리포트 도출
-
----
-
 ## 2026-02-05
 
 ### API 효율화
@@ -117,27 +91,6 @@
 
 ## 2026-02-16
 
-### 문서 v2 동기화 (전체 문서 현행화)
-
-**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
-
-**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
-
-**구현 결과:**
-- 6개 문서 파일 업데이트
-- 이전 시도(2개 커밋)는 기존 내용을 과도하게 삭제하여 폐기, main 기준으로 재작업
-
-**이슈/PR:** #131, PR #134
-
 ### 해외 스캐너 개선: 랭킹 연동 + 변동성 우선 선별
 
 **배경:**
@@ -191,167 +144,3 @@
 **효과:**
 - 국내/해외 스캐너 기준이 변동성 중심으로 일관화
 - 고변동 구간에서 자동 익스포저 축소, 저변동 구간에서 과소진입 완화
-
-## 2026-02-18
-
-### KIS 해외 랭킹 API 404 에러 수정
-
-**배경:**
-- KIS 해외주식 랭킹 API(`fetch_overseas_rankings`)가 모든 거래소에서 HTTP 404를 반환
-- Smart Scanner가 해외 시장 후보 종목을 찾지 못해 거래가 전혀 실행되지 않음
-
-**근본 원인:**
-- TR_ID, API 경로, 거래소 코드가 모두 KIS 공식 문서와 불일치
-
-**구현 결과:**
-- `src/config.py`: TR_ID/Path 기본값을 KIS 공식 스펙으로 수정
-- `src/broker/overseas.py`: 랭킹 API 전용 거래소 코드 매핑 추가 (NASD→NAS, NYSE→NYS, AMEX→AMS), 올바른 API 파라미터 사용
-- `tests/test_overseas_broker.py`: 19개 단위 테스트 추가
-
-**효과:**
-- 해외 시장 랭킹 스캔이 정상 동작하여 Smart Scanner가 후보 종목 탐지 가능
-
-### Gemini prompt_override 미적용 버그 수정
-
-**배경:**
-- `run_overnight` 실행 시 모든 시장에서 Playbook 생성 실패 (`JSONDecodeError`)
-- defensive playbook으로 폴백되어 모든 종목이 HOLD 처리
-
-**근본 원인:**
-- `pre_market_planner.py`가 `market_data["prompt_override"]`에 Playbook 전용 프롬프트를 넣어 `gemini.decide()` 호출
-- `gemini_client.py`의 `decide()` 메서드가 `prompt_override` 키를 전혀 확인하지 않고 항상 일반 트레이드 결정 프롬프트 생성
-- Gemini가 Playbook JSON 대신 일반 트레이드 결정을 반환하여 파싱 실패
-
-**구현 결과:**
-- `src/brain/gemini_client.py`: `decide()` 메서드에서 `prompt_override` 우선 사용 로직 추가
-- `tests/test_brain.py`: 3개 테스트 추가 (override 전달, optimization 우회, 미지정 시 기존 동작 유지)
-
-**이슈/PR:** #143
-
-### 미국장 거래 미실행 근본 원인 분석 및 수정 (자율 실행 세션)
-
-**배경:**
-- 사용자 요청: "미국장 열면 프로그램 돌려서 거래 한 번도 못 한 거 꼭 원인 찾아서 해결해줘"
-- 프로그램을 미국장 개장(9:30 AM EST) 전부터 실행하여 실시간 로그를 분석
-
-**발견된 근본 원인 #1: Defensive Playbook — BUY 조건 없음**
-
-- Gemini free tier (20 RPD) 소진 → `generate_playbook()` 실패 → `_defensive_playbook()` 폴백
-- Defensive playbook은 `price_change_pct_below: -3.0 → SELL` 조건만 존재, BUY 조건 없음
-- ScenarioEngine이 항상 HOLD 반환 → 거래 0건
-
-**수정 #1 (PR #146, Issue #145):**
-- `src/strategy/pre_market_planner.py`: `_smart_fallback_playbook()` 메서드 추가
-  - 스캐너 signal 기반 BUY 조건 생성: `momentum → volume_ratio_above`, `oversold → rsi_below`
-  - 기존 defensive stop-loss SELL 조건 유지
-- Gemini 실패 시 defensive → smart fallback으로 전환
-- 테스트 10개 추가
-
-**발견된 근본 원인 #2: 가격 API 거래소 코드 불일치 + VTS 잔고 API 오류**
-
-실제 로그:
-```
-Scenario matched for MRNX: BUY (confidence=80)  ✓
-Decision for EWUS (NYSE American): BUY (confidence=80)  ✓
-Skip BUY APLZ (NYSE American): no affordable quantity (cash=0.00, price=0.00)  ✗
-```
-
-- `get_overseas_price()`: `NASD`/`NYSE`/`AMEX` 전송 → API가 `NAS`/`NYS`/`AMS` 기대 → 빈 응답 → `price=0`
-- `VTTS3012R` 잔고 API: "ERROR : INPUT INVALID_CHECK_ACNO" → `total_cash=0`
-- 결과: `_determine_order_quantity()` 가 0 반환 → 주문 건너뜀
-
-**수정 #2 (PR #148, Issue #147):**
-- `src/broker/overseas.py`: `_PRICE_EXCHANGE_MAP = _RANKING_EXCHANGE_MAP` 추가, 가격 API에 매핑 적용
-- `src/config.py`: `PAPER_OVERSEAS_CASH: float = Field(default=50000.0)` — paper 모드 시뮬레이션 잔고
-- `src/main.py`: 잔고 0일 때 PAPER_OVERSEAS_CASH 폴백, 가격 0일 때 candidate.price 폴백
-- 테스트 8개 추가
-
-**효과:**
-- BUY 결정 → 실제 주문 전송까지의 파이프라인이 완전히 동작
-- Paper 모드에서 KIS VTS 해외 잔고 API 오류에 관계없이 시뮬레이션 거래 가능
-
-**이슈/PR:** #145, #146, #147, #148
-
-### 해외주식 시장가 주문 거부 수정 (Fix #3, 연속 발견)
-
-**배경:**
-- Fix #147 적용 후 주문 전송 시작 → KIS VTS가 거부: "지정가만 가능한 상품입니다"
-
-**근본 원인:**
-- `trading_cycle()`, `run_daily_session()` 양쪽에서 `send_overseas_order(price=0.0)` 하드코딩
-- `price=0` → `ORD_DVSN="01"` (시장가) 전송 → KIS VTS 거부
-- Fix #147에서 이미 `current_price`를 올바르게 계산했으나 주문 시 미사용
-
-**구현 결과:**
-- `src/main.py`: 두 곳에서 `price=0.0` → `price=current_price`/`price=stock_data["current_price"]`
-- `tests/test_main.py`: 회귀 테스트 `test_overseas_buy_order_uses_limit_price` 추가
-
-**최종 확인 로그:**
-```
-Order result: 모의투자 매수주문이 완료 되었습니다.  ✓
-```
-
-**이슈/PR:** #149, #150
-
----
-
-## 2026-02-23
-
-### 국내주식 지정가 전환 및 미체결 처리 (#232)
-
-**배경:**
-- 해외주식은 #211에서 지정가로 전환했으나 국내주식은 여전히 `price=0` (시장가)
-- KRX도 지정가 주문 사용 시 동일한 미체결 위험이 존재
-- 지정가 전환 + 미체결 처리를 함께 구현
-
-**구현 내용:**
-
-1. `src/broker/kis_api.py`
-   - `get_domestic_pending_orders()`: 모의 즉시 `[]`, 실전 `TTTC0084R` GET
-   - `cancel_domestic_order()`: 실전 `TTTC0013U` / 모의 `VTTC0013U`, hashkey 필수
-
-2. `src/main.py`
-   - import `kr_round_down` 추가
-   - `trading_cycle`, `run_daily_session` 국내 주문 `price=0` → 지정가:
-     BUY +0.2% / SELL -0.2%, `kr_round_down` KRX 틱 반올림 적용
-   - `handle_domestic_pending_orders` 함수: BUY→취소+쿨다운, SELL→취소+재주문(-0.4%, 최대1회)
-   - daily/realtime 두 모드에서 domestic pending 체크 호출 추가
-
-3. 테스트 14개 추가:
-   - `TestGetDomesticPendingOrders` (3), `TestCancelDomesticOrder` (5)
-   - `TestHandleDomesticPendingOrders` (4), `TestDomesticLimitOrderPrice` (2)
-
-**이슈/PR:** #232, PR #233
-
----
-
-## 2026-02-24
-
-### 해외잔고 ghost position 수정 — '모의투자 잔고내역이 없습니다' 반복 방지 (#235)
-
-**배경:**
-- 모의투자 실행 시 MLECW, KNRX, NBY, SNSE 등 만료/정지된 종목에 대해
-  `모의투자 잔고내역이 없습니다` 오류가 매 사이클 반복됨
-
-**근본 원인:**
-1. `ovrs_cblc_qty` (해외잔고수량, 총 보유) vs `ord_psbl_qty` (주문가능수량, 실제 매도 가능)
-   - 기존 코드: `ovrs_cblc_qty` 우선 사용 → 만료 Warrant가 `ovrs_cblc_qty=289456`이지만 실제 `ord_psbl_qty=0`
-   - startup sync / build_overseas_symbol_universe가 이 종목들을 포지션으로 기록
-2. SELL 실패 시 DB 포지션이 닫히지 않아 다음 사이클에서도 재시도 (무한 반복)
-
-**구현 내용:**
-
-1. `src/main.py` — `_extract_held_codes_from_balance`, `_extract_held_qty_from_balance`
-   - 해외 잔고 필드 우선순위 변경: `ord_psbl_qty` → `ovrs_cblc_qty` → `hldg_qty` (fallback 유지)
-   - KIS 공식 문서(VTTS3012R) 기준: `ord_psbl_qty`가 실제 매도 가능 수량
-
-2. `src/main.py` — `trading_cycle` ghost-close 처리
-   - 해외 SELL이 `잔고내역이 없습니다`로 실패 시 DB 포지션을 `[ghost-close]` SELL로 종료
-   - exchange code 불일치 등 예외 상황에서 무한 반복 방지
-
-3. 테스트 7개 추가:
-   - `TestExtractHeldQtyFromBalance` 3개: ord_psbl_qty 우선, 0이면 0 반환, fallback
-   - `TestExtractHeldCodesFromBalance` 2개: ord_psbl_qty=0인 종목 제외, fallback
-   - `TestOverseasGhostPositionClose` 2개: ghost-close 로그 확인, 일반 오류 무시
-
-**이슈/PR:** #235, PR #236

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)

docs/testing.md

@@ -2,29 +2,51 @@
 
 ## Test Structure
 
-**551 tests** across **25 files**. `asyncio_mode = "auto"` in pyproject.toml — async tests need no special decorator.
+**54 tests** across four 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
+#### `tests/test_risk.py` (11 tests)
+- Circuit breaker boundaries
+- Fat-finger edge cases
 - P&L calculation edge cases
 - Order validation logic
 
-##### `tests/test_broker.py` (11 tests)
+**Example:**
+```python
+def test_circuit_breaker_exact_threshold(risk_manager):
+    """Circuit breaker should trip at exactly -3.0%."""
+    with pytest.raises(CircuitBreakerTripped):
+        risk_manager.validate_order(
+            current_pnl_pct=-3.0,
+            order_amount=1000,
+            total_cash=10000
+        )
+```
+
+#### `tests/test_broker.py` (6 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
+**Example:**
+```python
+async def test_rate_limiter(broker):
+    """Rate limiter should delay requests to stay under 10 RPS."""
+    start = time.monotonic()
+    for _ in range(15):  # 15 requests
+        await broker._rate_limiter.acquire()
+    elapsed = time.monotonic() - start
+    assert elapsed >= 1.0  # Should take at least 1 second
+```
+
+#### `tests/test_brain.py` (18 tests)
+- Valid JSON parsing
+- Markdown-wrapped JSON handling
 - Malformed JSON fallback
 - Missing fields handling
 - Invalid action validation
@@ -32,143 +54,33 @@ The `settings` fixture in `conftest.py` provides safe defaults with test credent
 - Empty response handling
 - Prompt construction for different markets
 
-##### `tests/test_market_schedule.py` (24 tests)
+**Example:**
+```python
+async def test_confidence_below_threshold_forces_hold(brain):
+    """Decisions below confidence threshold should force HOLD."""
+    decision = brain.parse_response('{"action":"BUY","confidence":70,"rationale":"test"}')
+    assert decision.action == "HOLD"
+    assert decision.confidence == 70
+```
+
+#### `tests/test_market_schedule.py` (19 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
+- Weekend handling
+- 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
+**Example:**
+```python
+def test_is_market_open_during_trading_hours():
+    """Market should be open during regular trading hours."""
+    # KRX: 9:00-15:30 KST, no lunch break
+    market = MARKETS["KR"]
+    trading_time = datetime(2026, 2, 3, 10, 0, tzinfo=ZoneInfo("Asia/Seoul"))  # Monday 10:00
+    assert is_market_open(market, trading_time) is True
+```
 
 ## Coverage Requirements
 
@@ -179,6 +91,20 @@ Check coverage:
 pytest -v --cov=src --cov-report=term-missing
 ```
 
+Expected output:
+```
+Name                          Stmts   Miss  Cover   Missing
+-----------------------------------------------------------
+src/brain/gemini_client.py       85      5    94%   165-169
+src/broker/kis_api.py           120     12    90%   ...
+src/core/risk_manager.py         35      2    94%   ...
+src/db.py                        25      1    96%   ...
+src/main.py                     150     80    47%   (excluded from CI)
+src/markets/schedule.py          95      3    97%   ...
+-----------------------------------------------------------
+TOTAL                           510     103   80%
+```
+
 **Note:** `main.py` has lower coverage as it contains the main loop which is tested via integration/manual testing.
 
 ## Test Configuration

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

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

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"

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

src/analysis/smart_scanner.py

@@ -175,7 +175,7 @@ class SmartVolatilityScanner:
                 liquidity_score = volume_rank_bonus.get(stock_code, 0.0)
                 score = min(100.0, volatility_score + liquidity_score)
                 signal = "momentum" if change_rate >= 0 else "oversold"
-                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
+                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
 
                 candidates.append(
                     ScanCandidate(
@@ -282,7 +282,7 @@ class SmartVolatilityScanner:
             liquidity_score = volume_rank_bonus.get(stock_code, 0.0)
             score = min(100.0, volatility_score + liquidity_score)
             signal = "momentum" if change_rate >= 0 else "oversold"
-            implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
+            implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
             candidates.append(
                 ScanCandidate(
                     stock_code=stock_code,
@@ -315,11 +315,6 @@ class SmartVolatilityScanner:
             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:
@@ -338,7 +333,7 @@ class SmartVolatilityScanner:
 
                 score = min(volatility_pct / 10.0, 1.0) * 100.0
                 signal = "momentum" if change_rate >= 0 else "oversold"
-                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 2.0)))
+                implied_rsi = max(0.0, min(100.0, 50.0 + (change_rate * 4.0)))
                 candidates.append(
                     ScanCandidate(
                         stock_code=stock_code,
@@ -355,11 +350,6 @@ class SmartVolatilityScanner:
                 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]:

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)

src/broker/kis_api.py

@@ -8,7 +8,7 @@ from __future__ import annotations
 import asyncio
 import logging
 import ssl
-from typing import Any, cast
+from typing import Any
 
 import aiohttp
 
@@ -20,39 +20,6 @@ _KIS_VTS_HOST = "openapivts.koreainvestment.com"
 logger = logging.getLogger(__name__)
 
 
-def kr_tick_unit(price: float) -> int:
-    """Return KRX tick size for the given price level.
-
-    KRX price tick rules (domestic stocks):
-        price < 2,000        →   1원
-        2,000  ≤ price < 5,000     →   5원
-        5,000  ≤ price < 20,000    →  10원
-        20,000 ≤ price < 50,000    →  50원
-        50,000 ≤ price < 200,000   → 100원
-        200,000 ≤ price < 500,000  → 500원
-        500,000 ≤ price            → 1,000원
-    """
-    if price < 2_000:
-        return 1
-    if price < 5_000:
-        return 5
-    if price < 20_000:
-        return 10
-    if price < 50_000:
-        return 50
-    if price < 200_000:
-        return 100
-    if price < 500_000:
-        return 500
-    return 1_000
-
-
-def kr_round_down(price: float) -> int:
-    """Round *down* price to the nearest KRX tick unit."""
-    tick = kr_tick_unit(price)
-    return int(price // tick * tick)
-
-
 class LeakyBucket:
     """Simple leaky-bucket rate limiter for async code."""
 
@@ -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
@@ -231,64 +196,12 @@ class KISBroker:
         except (TimeoutError, aiohttp.ClientError) as exc:
             raise ConnectionError(f"Network error fetching orderbook: {exc}") from exc
 
-    async def get_current_price(
-        self, stock_code: str
-    ) -> tuple[float, float, float]:
-        """Fetch current price data for a domestic stock.
-
-        Uses the ``inquire-price`` API (FHKST01010100), which works in both
-        real and VTS environments and returns the actual last-traded price.
-
-        Returns:
-            (current_price, prdy_ctrt, frgn_ntby_qty)
-            - current_price: Last traded price in KRW.
-            - prdy_ctrt: Day change rate (%).
-            - frgn_ntby_qty: Foreigner net buy quantity.
-        """
-        await self._rate_limiter.acquire()
-        session = self._get_session()
-
-        headers = await self._auth_headers("FHKST01010100")
-        params = {
-            "FID_COND_MRKT_DIV_CODE": "J",
-            "FID_INPUT_ISCD": stock_code,
-        }
-        url = f"{self._base_url}/uapi/domestic-stock/v1/quotations/inquire-price"
-
-        def _f(val: str | None) -> float:
-            try:
-                return float(val or "0")
-            except ValueError:
-                return 0.0
-
-        try:
-            async with session.get(url, headers=headers, params=params) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ConnectionError(
-                        f"get_current_price failed ({resp.status}): {text}"
-                    )
-                data = await resp.json()
-                out = data.get("output", {})
-                return (
-                    _f(out.get("stck_prpr")),
-                    _f(out.get("prdy_ctrt")),
-                    _f(out.get("frgn_ntby_qty")),
-                )
-        except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
-                f"Network error fetching current price: {exc}"
-            ) from exc
-
     async def get_balance(self) -> dict[str, Any]:
         """Fetch current account balance and holdings."""
         await self._rate_limiter.acquire()
         session = self._get_session()
 
-        # TR_ID: 실전 TTTC8434R, 모의 VTTC8434R
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '국내주식 잔고조회' 시트
-        tr_id = "TTTC8434R" if self._settings.MODE == "live" else "VTTC8434R"
-        headers = await self._auth_headers(tr_id)
+        headers = await self._auth_headers("VTTC8434R")  # 모의투자 잔고조회
         params = {
             "CANO": self._account_no,
             "ACNT_PRDT_CD": self._product_cd,
@@ -333,30 +246,14 @@ class KISBroker:
         await self._rate_limiter.acquire()
         session = self._get_session()
 
-        # TR_ID: 실전 BUY=TTTC0012U SELL=TTTC0011U, 모의 BUY=VTTC0012U SELL=VTTC0011U
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식주문(현금)' 시트
-        # ※ TTTC0802U/VTTC0802U는 미수매수(증거금40% 계좌 전용) — 현금주문에 사용 금지
-        if self._settings.MODE == "live":
-            tr_id = "TTTC0012U" if order_type == "BUY" else "TTTC0011U"
-        else:
-            tr_id = "VTTC0012U" if order_type == "BUY" else "VTTC0011U"
-
-        # KRX requires limit orders to be rounded down to the tick unit.
-        # ORD_DVSN: "00"=지정가, "01"=시장가
-        if price > 0:
-            ord_dvsn = "00"  # 지정가
-            ord_price = kr_round_down(price)
-        else:
-            ord_dvsn = "01"  # 시장가
-            ord_price = 0
-
+        tr_id = "VTTC0802U" if order_type == "BUY" else "VTTC0801U"
         body = {
             "CANO": self._account_no,
             "ACNT_PRDT_CD": self._product_cd,
             "PDNO": stock_code,
-            "ORD_DVSN": ord_dvsn,
+            "ORD_DVSN": "01" if price > 0 else "06",  # 01=지정가, 06=시장가
             "ORD_QTY": str(quantity),
-            "ORD_UNPR": str(ord_price),
+            "ORD_UNPR": str(price),
         }
 
         hash_key = await self._get_hash_key(body)
@@ -405,46 +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:
@@ -478,112 +355,6 @@ class KISBroker:
         except (TimeoutError, aiohttp.ClientError) as exc:
             raise ConnectionError(f"Network error fetching rankings: {exc}") from exc
 
-    async def get_domestic_pending_orders(self) -> list[dict[str, Any]]:
-        """Fetch unfilled (pending) domestic limit orders.
-
-        The KIS pending-orders API (TTTC0084R) is unsupported in paper (VTS)
-        mode, so this method returns an empty list immediately when MODE is
-        not "live".
-
-        Returns:
-            List of pending order dicts from the KIS ``output`` field.
-            Each dict includes keys such as ``odno``, ``orgn_odno``,
-            ``ord_gno_brno``, ``psbl_qty``, ``sll_buy_dvsn_cd``, ``pdno``.
-        """
-        if self._settings.MODE != "live":
-            logger.debug(
-                "get_domestic_pending_orders: paper mode — TTTC0084R unsupported, returning []"
-            )
-            return []
-
-        await self._rate_limiter.acquire()
-        session = self._get_session()
-
-        # TR_ID: 실전 TTTC0084R (모의 미지원)
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식 미체결조회' 시트
-        headers = await self._auth_headers("TTTC0084R")
-        params = {
-            "CANO": self._account_no,
-            "ACNT_PRDT_CD": self._product_cd,
-            "INQR_DVSN_1": "0",
-            "INQR_DVSN_2": "0",
-            "CTX_AREA_FK100": "",
-            "CTX_AREA_NK100": "",
-        }
-        url = f"{self._base_url}/uapi/domestic-stock/v1/trading/inquire-psbl-rvsecncl"
-
-        try:
-            async with session.get(url, headers=headers, params=params) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ConnectionError(
-                        f"get_domestic_pending_orders failed ({resp.status}): {text}"
-                    )
-                data = await resp.json()
-                return data.get("output", []) or []
-        except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
-                f"Network error fetching domestic pending orders: {exc}"
-            ) from exc
-
-    async def cancel_domestic_order(
-        self,
-        stock_code: str,
-        orgn_odno: str,
-        krx_fwdg_ord_orgno: str,
-        qty: int,
-    ) -> dict[str, Any]:
-        """Cancel an unfilled domestic limit order.
-
-        Args:
-            stock_code: 6-digit domestic stock code (``pdno``).
-            orgn_odno: Original order number from pending-orders response
-                (``orgn_odno`` field).
-            krx_fwdg_ord_orgno: KRX forwarding order branch number from
-                pending-orders response (``ord_gno_brno`` field).
-            qty: Quantity to cancel (use ``psbl_qty`` from pending order).
-
-        Returns:
-            Raw KIS API response dict (check ``rt_cd == "0"`` for success).
-        """
-        await self._rate_limiter.acquire()
-        session = self._get_session()
-
-        # TR_ID: 실전 TTTC0013U, 모의 VTTC0013U
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '주식주문(정정취소)' 시트
-        tr_id = "TTTC0013U" if self._settings.MODE == "live" else "VTTC0013U"
-
-        body = {
-            "CANO": self._account_no,
-            "ACNT_PRDT_CD": self._product_cd,
-            "KRX_FWDG_ORD_ORGNO": krx_fwdg_ord_orgno,
-            "ORGN_ODNO": orgn_odno,
-            "ORD_DVSN": "00",
-            "ORD_QTY": str(qty),
-            "ORD_UNPR": "0",
-            "RVSE_CNCL_DVSN_CD": "02",
-            "QTY_ALL_ORD_YN": "Y",
-        }
-
-        hash_key = await self._get_hash_key(body)
-        headers = await self._auth_headers(tr_id)
-        headers["hashkey"] = hash_key
-
-        url = f"{self._base_url}/uapi/domestic-stock/v1/trading/order-rvsecncl"
-
-        try:
-            async with session.post(url, headers=headers, json=body) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ConnectionError(
-                        f"cancel_domestic_order failed ({resp.status}): {text}"
-                    )
-                return cast(dict[str, Any], await resp.json())
-        except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
-                f"Network error cancelling domestic order: {exc}"
-            ) from exc
-
     async def get_daily_prices(
         self,
         stock_code: str,

src/broker/overseas.py

@@ -12,38 +12,6 @@ from src.broker.kis_api import KISBroker
 logger = logging.getLogger(__name__)
 
 
-# Ranking API uses different exchange codes than order/quote APIs.
-_RANKING_EXCHANGE_MAP: dict[str, str] = {
-    "NASD": "NAS",
-    "NYSE": "NYS",
-    "AMEX": "AMS",
-    "SEHK": "HKS",
-    "SHAA": "SHS",
-    "SZAA": "SZS",
-    "HSX": "HSX",
-    "HNX": "HNX",
-    "TSE": "TSE",
-}
-
-# Price inquiry API (HHDFS00000300) uses the same short exchange codes as rankings.
-# NASD → NAS, NYSE → NYS, AMEX → AMS (confirmed: AMEX returns empty, AMS returns price).
-_PRICE_EXCHANGE_MAP: dict[str, str] = _RANKING_EXCHANGE_MAP
-
-# Cancel order TR_IDs per exchange code — (live_tr_id, paper_tr_id).
-# Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문취소' 시트
-_CANCEL_TR_ID_MAP: dict[str, tuple[str, str]] = {
-    "NASD": ("TTTT1004U", "VTTT1004U"),
-    "NYSE": ("TTTT1004U", "VTTT1004U"),
-    "AMEX": ("TTTT1004U", "VTTT1004U"),
-    "SEHK": ("TTTS1003U", "VTTS1003U"),
-    "TSE":  ("TTTS0309U", "VTTS0309U"),
-    "SHAA": ("TTTS0302U", "VTTS0302U"),
-    "SZAA": ("TTTS0306U", "VTTS0306U"),
-    "HNX":  ("TTTS0312U", "VTTS0312U"),
-    "HSX":  ("TTTS0312U", "VTTS0312U"),
-}
-
-
 class OverseasBroker:
     """KIS Overseas Stock API wrapper that reuses KISBroker infrastructure."""
 
@@ -76,11 +44,9 @@ class OverseasBroker:
         session = self._broker._get_session()
 
         headers = await self._broker._auth_headers("HHDFS00000300")
-        # Map internal exchange codes to the short form expected by the price API.
-        price_excd = _PRICE_EXCHANGE_MAP.get(exchange_code, exchange_code)
         params = {
             "AUTH": "",
-            "EXCD": price_excd,
+            "EXCD": exchange_code,
             "SYMB": stock_code,
         }
         url = f"{self._broker._base_url}/uapi/overseas-price/v1/quotations/price"
@@ -104,7 +70,7 @@ class OverseasBroker:
         ranking_type: str = "fluctuation",
         limit: int = 30,
     ) -> list[dict[str, Any]]:
-        """Fetch overseas rankings (price change or volume surge).
+        """Fetch overseas rankings (price change or volume amount).
 
         Ranking API specs may differ by account/product. Endpoint paths and
         TR_IDs are configurable via settings and can be overridden in .env.
@@ -115,63 +81,47 @@ class OverseasBroker:
         await self._broker._rate_limiter.acquire()
         session = self._broker._get_session()
 
-        ranking_excd = _RANKING_EXCHANGE_MAP.get(exchange_code, exchange_code)
-
         if ranking_type == "volume":
             tr_id = self._broker._settings.OVERSEAS_RANKING_VOLUME_TR_ID
             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:
+        # Try common param variants used by KIS overseas quotation APIs.
+        param_variants = [
+            {"AUTH": "", "EXCD": exchange_code, "NREC": str(max(limit, 30))},
+            {"AUTH": "", "OVRS_EXCG_CD": exchange_code, "NREC": str(max(limit, 30))},
+            {"AUTH": "", "EXCD": exchange_code},
+            {"AUTH": "", "OVRS_EXCG_CD": exchange_code},
+        ]
+
+        last_error: str | None = None
+        for params in param_variants:
+            try:
+                async with session.get(url, headers=headers, params=params) as resp:
                     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}"
-                    )
+                    if resp.status != 200:
+                        last_error = f"HTTP {resp.status}: {text}"
+                        continue
 
-                data = await resp.json()
-                rows = self._extract_ranking_rows(data)
-                if rows:
-                    return rows[:limit]
+                    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
+                    # keep trying another param variant if response has no usable rows
+                    last_error = f"empty output (keys={list(data.keys())})"
+            except (TimeoutError, aiohttp.ClientError) as exc:
+                last_error = str(exc)
+                continue
+
+        raise ConnectionError(
+            f"fetch_overseas_rankings failed for {exchange_code}/{ranking_type}: {last_error}"
+        )
 
     async def get_overseas_balance(self, exchange_code: str) -> dict[str, Any]:
         """
@@ -189,12 +139,8 @@ class OverseasBroker:
         await self._broker._rate_limiter.acquire()
         session = self._broker._get_session()
 
-        # TR_ID: 실전 TTTS3012R, 모의 VTTS3012R
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 잔고조회' 시트
-        balance_tr_id = (
-            "TTTS3012R" if self._broker._settings.MODE == "live" else "VTTS3012R"
-        )
-        headers = await self._broker._auth_headers(balance_tr_id)
+        # Virtual trading TR_ID for overseas balance inquiry
+        headers = await self._broker._auth_headers("VTTS3012R")
         params = {
             "CANO": self._broker._account_no,
             "ACNT_PRDT_CD": self._broker._product_cd,
@@ -247,12 +193,8 @@ class OverseasBroker:
         await self._broker._rate_limiter.acquire()
         session = self._broker._get_session()
 
-        # TR_ID: 실전 BUY=TTTT1002U SELL=TTTT1006U, 모의 BUY=VTTT1002U SELL=VTTT1001U
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 주문' 시트
-        if self._broker._settings.MODE == "live":
-            tr_id = "TTTT1002U" if order_type == "BUY" else "TTTT1006U"
-        else:
-            tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1001U"
+        # Virtual trading TR_IDs for overseas orders
+        tr_id = "VTTT1002U" if order_type == "BUY" else "VTTT1006U"
 
         body = {
             "CANO": self._broker._account_no,
@@ -279,158 +221,20 @@ 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(
                 f"Network error sending overseas order: {exc}"
             ) from exc
 
-    async def get_overseas_pending_orders(
-        self, exchange_code: str
-    ) -> list[dict[str, Any]]:
-        """Fetch unfilled (pending) overseas orders for a given exchange.
-
-        Args:
-            exchange_code: Exchange code (e.g., "NASD", "SEHK").
-                For US markets, NASD returns all US pending orders (NASD/NYSE/AMEX).
-
-        Returns:
-            List of pending order dicts with fields: odno, pdno, sll_buy_dvsn_cd,
-            ft_ord_qty, nccs_qty, ft_ord_unpr3, ovrs_excg_cd.
-            Always returns [] in paper mode (TTTS3018R is live-only).
-
-        Raises:
-            ConnectionError: On network or API errors (live mode only).
-        """
-        if self._broker._settings.MODE != "live":
-            logger.debug(
-                "Pending orders API (TTTS3018R) not supported in paper mode; returning []"
-            )
-            return []
-
-        await self._broker._rate_limiter.acquire()
-        session = self._broker._get_session()
-
-        # TTTS3018R: 해외주식 미체결내역조회 (실전 전용)
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 미체결조회' 시트
-        headers = await self._broker._auth_headers("TTTS3018R")
-        params = {
-            "CANO": self._broker._account_no,
-            "ACNT_PRDT_CD": self._broker._product_cd,
-            "OVRS_EXCG_CD": exchange_code,
-            "SORT_SQN": "DS",
-            "CTX_AREA_FK200": "",
-            "CTX_AREA_NK200": "",
-        }
-        url = (
-            f"{self._broker._base_url}/uapi/overseas-stock/v1/trading/inquire-nccs"
-        )
-
-        try:
-            async with session.get(url, headers=headers, params=params) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ConnectionError(
-                        f"get_overseas_pending_orders failed ({resp.status}): {text}"
-                    )
-                data = await resp.json()
-                output = data.get("output", [])
-                if isinstance(output, list):
-                    return output
-                return []
-        except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
-                f"Network error fetching pending orders: {exc}"
-            ) from exc
-
-    async def cancel_overseas_order(
-        self,
-        exchange_code: str,
-        stock_code: str,
-        odno: str,
-        qty: int,
-    ) -> dict[str, Any]:
-        """Cancel an overseas limit order.
-
-        Args:
-            exchange_code: Exchange code (e.g., "NASD", "SEHK").
-            stock_code: Stock ticker symbol.
-            odno: Original order number to cancel.
-            qty: Unfilled quantity to cancel.
-
-        Returns:
-            API response dict containing rt_cd and msg1.
-
-        Raises:
-            ValueError: If exchange_code has no cancel TR_ID mapping.
-            ConnectionError: On network or API errors.
-        """
-        tr_ids = _CANCEL_TR_ID_MAP.get(exchange_code)
-        if tr_ids is None:
-            raise ValueError(f"No cancel TR_ID mapping for exchange: {exchange_code}")
-        live_tr_id, paper_tr_id = tr_ids
-        tr_id = live_tr_id if self._broker._settings.MODE == "live" else paper_tr_id
-
-        await self._broker._rate_limiter.acquire()
-        session = self._broker._get_session()
-
-        # RVSE_CNCL_DVSN_CD="02" means cancel (not revision).
-        # OVRS_ORD_UNPR must be "0" for cancellations.
-        # Source: 한국투자증권 오픈API 전체문서 (20260221) — '해외주식 정정취소주문' 시트
-        body = {
-            "CANO": self._broker._account_no,
-            "ACNT_PRDT_CD": self._broker._product_cd,
-            "OVRS_EXCG_CD": exchange_code,
-            "PDNO": stock_code,
-            "ORGN_ODNO": odno,
-            "RVSE_CNCL_DVSN_CD": "02",
-            "ORD_QTY": str(qty),
-            "OVRS_ORD_UNPR": "0",
-            "ORD_SVR_DVSN_CD": "0",
-        }
-
-        hash_key = await self._broker._get_hash_key(body)
-        headers = await self._broker._auth_headers(tr_id)
-        headers["hashkey"] = hash_key
-
-        url = (
-            f"{self._broker._base_url}/uapi/overseas-stock/v1/trading/order-rvsecncl"
-        )
-
-        try:
-            async with session.post(url, headers=headers, json=body) as resp:
-                if resp.status != 200:
-                    text = await resp.text()
-                    raise ConnectionError(
-                        f"cancel_overseas_order failed ({resp.status}): {text}"
-                    )
-                return await resp.json()
-        except (TimeoutError, aiohttp.ClientError) as exc:
-            raise ConnectionError(
-                f"Network error cancelling overseas order: {exc}"
-            ) from exc
-
     def _get_currency_code(self, exchange_code: str) -> str:
         """
         Map exchange code to currency code.

src/config.py

@@ -13,11 +13,11 @@ class Settings(BaseSettings):
     KIS_APP_KEY: str
     KIS_APP_SECRET: str
     KIS_ACCOUNT_NO: str  # format: "XXXXXXXX-XX"
-    KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:29443"
+    KIS_BASE_URL: str = "https://openapivts.koreainvestment.com:9443"
 
     # Google Gemini
     GEMINI_API_KEY: str
-    GEMINI_MODEL: str = "gemini-2.0-flash"
+    GEMINI_MODEL: str = "gemini-pro"
 
     # External Data APIs (optional — for data-driven decisions)
     NEWS_API_KEY: str | None = None
@@ -55,11 +55,6 @@ class Settings(BaseSettings):
     # Trading mode
     MODE: str = Field(default="paper", pattern="^(paper|live)$")
 
-    # Simulated USD cash for VTS (paper) overseas trading.
-    # KIS VTS overseas balance API returns errors for most accounts.
-    # This value is used as a fallback when the balance API returns 0 in paper mode.
-    PAPER_OVERSEAS_CASH: float = Field(default=50000.0, ge=0.0)
-
     # Trading frequency mode (daily = batch API calls, realtime = per-stock calls)
     TRADE_MODE: str = Field(default="daily", pattern="^(daily|realtime)$")
     DAILY_SESSIONS: int = Field(default=4, ge=1, le=10)
@@ -93,26 +88,16 @@ class Settings(BaseSettings):
     TELEGRAM_COMMANDS_ENABLED: bool = True
     TELEGRAM_POLLING_INTERVAL: float = 1.0  # seconds
 
-    # Telegram notification type filters (granular control)
-    # circuit_breaker is always sent regardless — safety-critical
-    TELEGRAM_NOTIFY_TRADES: bool = True           # BUY/SELL execution alerts
-    TELEGRAM_NOTIFY_MARKET_OPEN_CLOSE: bool = True  # Market open/close alerts
-    TELEGRAM_NOTIFY_FAT_FINGER: bool = True       # Fat-finger rejection alerts
-    TELEGRAM_NOTIFY_SYSTEM_EVENTS: bool = True    # System start/shutdown alerts
-    TELEGRAM_NOTIFY_PLAYBOOK: bool = True         # Playbook generated/failed alerts
-    TELEGRAM_NOTIFY_SCENARIO_MATCH: bool = True   # Scenario matched alerts (most frequent)
-    TELEGRAM_NOTIFY_ERRORS: bool = True           # Error alerts
-
     # Overseas ranking API (KIS endpoint/TR_ID may vary by account/product)
     # Override these from .env if your account uses different specs.
     OVERSEAS_RANKING_ENABLED: bool = True
-    OVERSEAS_RANKING_FLUCT_TR_ID: str = "HHDFS76290000"
-    OVERSEAS_RANKING_VOLUME_TR_ID: str = "HHDFS76270000"
+    OVERSEAS_RANKING_FLUCT_TR_ID: str = "HHDFS76200100"
+    OVERSEAS_RANKING_VOLUME_TR_ID: str = "HHDFS76200200"
     OVERSEAS_RANKING_FLUCT_PATH: str = (
-        "/uapi/overseas-stock/v1/ranking/updown-rate"
+        "/uapi/overseas-price/v1/quotations/inquire-updown-rank"
     )
     OVERSEAS_RANKING_VOLUME_PATH: str = (
-        "/uapi/overseas-stock/v1/ranking/volume-surge"
+        "/uapi/overseas-price/v1/quotations/inquire-volume-rank"
     )
 
     # Dashboard (optional)

src/dashboard/app.py

@@ -3,9 +3,8 @@
 from __future__ import annotations
 
 import json
-import os
 import sqlite3
-from datetime import UTC, datetime, timezone
+from datetime import UTC, datetime
 from pathlib import Path
 from typing import Any
 
@@ -80,49 +79,14 @@ def create_dashboard_app(db_path: str) -> FastAPI:
                 total_pnl += market_status[market]["total_pnl"]
                 total_decisions += market_status[market]["decision_count"]
 
-            cb_threshold = float(os.getenv("CIRCUIT_BREAKER_PCT", "-3.0"))
-            pnl_pct_rows = conn.execute(
-                """
-                SELECT key, value
-                FROM system_metrics
-                WHERE key LIKE 'portfolio_pnl_pct_%'
-                ORDER BY updated_at DESC
-                LIMIT 20
-                """
-            ).fetchall()
-            current_pnl_pct: float | None = None
-            if pnl_pct_rows:
-                values = [
-                    json.loads(row["value"]).get("pnl_pct")
-                    for row in pnl_pct_rows
-                    if json.loads(row["value"]).get("pnl_pct") is not None
-                ]
-                if values:
-                    current_pnl_pct = round(min(values), 4)
-
-            if current_pnl_pct is None:
-                cb_status = "unknown"
-            elif current_pnl_pct <= cb_threshold:
-                cb_status = "tripped"
-            elif current_pnl_pct <= cb_threshold + 1.0:
-                cb_status = "warning"
-            else:
-                cb_status = "ok"
-
             return {
                 "date": today,
-                "mode": os.getenv("MODE", "paper"),
                 "markets": market_status,
                 "totals": {
                     "trade_count": total_trades,
                     "total_pnl": round(total_pnl, 2),
                     "decision_count": total_decisions,
                 },
-                "circuit_breaker": {
-                    "threshold_pct": cb_threshold,
-                    "current_pnl_pct": current_pnl_pct,
-                    "status": cb_status,
-                },
             }
 
     @app.get("/api/playbook/{date_str}")
@@ -295,50 +259,6 @@ 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"),
@@ -377,68 +297,12 @@ def create_dashboard_app(db_path: str) -> FastAPI:
                 )
             return {"market": market, "date": date_str, "count": len(matches), "matches": matches}
 
-    @app.get("/api/positions")
-    def get_positions() -> dict[str, Any]:
-        """Return all currently open positions (last trade per symbol is BUY)."""
-        with _connect(db_path) as conn:
-            rows = conn.execute(
-                """
-                SELECT stock_code, market, exchange_code,
-                       price AS entry_price, quantity, timestamp AS entry_time,
-                       decision_id
-                FROM (
-                    SELECT stock_code, market, exchange_code, price, quantity,
-                           timestamp, decision_id, action,
-                           ROW_NUMBER() OVER (
-                               PARTITION BY stock_code, market
-                               ORDER BY timestamp DESC
-                           ) AS rn
-                    FROM trades
-                )
-                WHERE rn = 1 AND action = 'BUY'
-                ORDER BY entry_time DESC
-                """
-            ).fetchall()
-
-            now = datetime.now(timezone.utc)
-            positions = []
-            for row in rows:
-                entry_time_str = row["entry_time"]
-                try:
-                    entry_dt = datetime.fromisoformat(entry_time_str.replace("Z", "+00:00"))
-                    held_seconds = int((now - entry_dt).total_seconds())
-                    held_hours = held_seconds // 3600
-                    held_minutes = (held_seconds % 3600) // 60
-                    if held_hours >= 1:
-                        held_display = f"{held_hours}h {held_minutes}m"
-                    else:
-                        held_display = f"{held_minutes}m"
-                except (ValueError, TypeError):
-                    held_display = "--"
-
-                positions.append(
-                    {
-                        "stock_code": row["stock_code"],
-                        "market": row["market"],
-                        "exchange_code": row["exchange_code"],
-                        "entry_price": row["entry_price"],
-                        "quantity": row["quantity"],
-                        "entry_time": entry_time_str,
-                        "held": held_display,
-                        "decision_id": row["decision_id"],
-                    }
-                )
-
-            return {"count": len(positions), "positions": positions}
-
     return app
 
 
 def _connect(db_path: str) -> sqlite3.Connection:
     conn = sqlite3.connect(db_path)
     conn.row_factory = sqlite3.Row
-    conn.execute("PRAGMA journal_mode=WAL")
-    conn.execute("PRAGMA busy_timeout=8000")
     return conn
 
 

src/dashboard/static/index.html

@@ -1,10 +1,9 @@
 <!doctype html>
-<html lang="ko">
+<html lang="en">
   <head>
     <meta charset="UTF-8" />
     <meta name="viewport" content="width=device-width, initial-scale=1.0" />
     <title>The Ouroboros Dashboard</title>
-    <script src="https://cdn.jsdelivr.net/npm/chart.js@4.4.0/dist/chart.umd.min.js"></script>
     <style>
       :root {
         --bg: #0b1724;
@@ -12,787 +11,51 @@
         --fg: #e6eef7;
         --muted: #9fb3c8;
         --accent: #3cb371;
-        --red: #e05555;
-        --warn: #e8a040;
-        --border: #28455f;
       }
-      * { box-sizing: border-box; margin: 0; padding: 0; }
       body {
+        margin: 0;
         font-family: ui-monospace, SFMono-Regular, Menlo, monospace;
         background: radial-gradient(circle at top left, #173b58, var(--bg));
         color: var(--fg);
-        min-height: 100vh;
-        font-size: 13px;
       }
-      .wrap { max-width: 1100px; margin: 0 auto; padding: 20px 16px; }
-
-      /* 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); }
-      .mode-badge {
-        padding: 3px 10px; border-radius: 5px; font-size: 12px; font-weight: 700;
-        letter-spacing: 0.5px;
-      }
-      .mode-badge.live {
-        background: rgba(224, 85, 85, 0.15); color: var(--red);
-        border: 1px solid rgba(224, 85, 85, 0.4);
-        animation: pulse-warn 2s ease-in-out infinite;
-      }
-      .mode-badge.paper {
-        background: rgba(232, 160, 64, 0.15); color: var(--warn);
-        border: 1px solid rgba(232, 160, 64, 0.4);
-      }
-
-      /* CB Gauge */
-      .cb-gauge-wrap {
-        display: flex; align-items: center; gap: 8px;
-        font-size: 11px; color: var(--muted);
-      }
-      .cb-dot {
-        width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0;
-      }
-      .cb-dot.ok      { background: var(--accent); }
-      .cb-dot.warning { background: var(--warn); animation: pulse-warn 1.2s ease-in-out infinite; }
-      .cb-dot.tripped { background: var(--red);  animation: pulse-warn 0.6s ease-in-out infinite; }
-      .cb-dot.unknown { background: var(--border); }
-      @keyframes pulse-warn {
-        0%, 100% { opacity: 1; }
-        50%       { opacity: 0.35; }
-      }
-      .cb-bar-wrap { width: 64px; height: 5px; background: rgba(255,255,255,0.08); border-radius: 3px; overflow: hidden; }
-      .cb-bar-fill { height: 100%; border-radius: 3px; transition: width 0.4s, background 0.4s; }
-
-      /* Summary cards */
-      .cards { display: grid; grid-template-columns: repeat(4, 1fr); gap: 12px; margin-bottom: 20px; }
-      @media (max-width: 700px) { .cards { grid-template-columns: repeat(2, 1fr); } }
       .card {
-        background: var(--panel);
-        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; }
-
-      /* Positions panel */
-      .positions-panel {
-        background: var(--panel);
-        border: 1px solid var(--border);
-        border-radius: 10px;
-        padding: 16px;
-        margin-bottom: 20px;
-      }
-      .positions-table { width: 100%; border-collapse: collapse; margin-top: 14px; }
-      .positions-table th {
-        text-align: left; color: var(--muted); font-size: 11px; font-weight: 600;
-        padding: 6px 8px; border-bottom: 1px solid var(--border); white-space: nowrap;
-      }
-      .positions-table td {
-        padding: 8px 8px; border-bottom: 1px solid rgba(40, 69, 95, 0.5);
-        vertical-align: middle; white-space: nowrap;
-      }
-      .positions-table tr:last-child td { border-bottom: none; }
-      .positions-table tr:hover td { background: rgba(255,255,255,0.02); }
-      .pos-empty { color: var(--muted); text-align: center; padding: 20px 0; font-size: 12px; }
-      .pos-count {
-        display: inline-block; background: rgba(60, 179, 113, 0.12);
-        color: var(--accent); font-size: 11px; font-weight: 700;
-        padding: 2px 8px; border-radius: 10px; margin-left: 8px;
-      }
-
-      /* Spinner */
-      .spinner { display: inline-block; width: 12px; height: 12px; border: 2px solid var(--border); border-top-color: var(--accent); border-radius: 50%; animation: spin 0.8s linear infinite; }
-      @keyframes spin { to { transform: rotate(360deg); } }
-
-      /* Generic panel */
-      .panel {
-        background: var(--panel);
-        border: 1px solid var(--border);
-        border-radius: 10px;
-        padding: 16px;
-        margin-top: 20px;
-      }
-
-      /* Playbook panel - details/summary accordion */
-      .playbook-panel details { border: 1px solid var(--border); border-radius: 4px; margin-bottom: 6px; }
-      .playbook-panel summary { padding: 8px 12px; cursor: pointer; font-weight: 600; background: var(--bg); color: var(--fg); }
-      .playbook-panel summary:hover { color: var(--accent); }
-      .playbook-panel pre { margin: 0; padding: 12px; background: var(--bg); overflow-x: auto;
-                            font-size: 11px; color: #a0c4ff; white-space: pre-wrap; }
-
-      /* Scorecard KPI card grid */
-      .scorecard-grid { display: grid; grid-template-columns: repeat(auto-fill, minmax(140px, 1fr)); gap: 10px; }
-      .kpi-card { background: var(--bg); border: 1px solid var(--border); border-radius: 6px; padding: 12px; text-align: center; }
-      .kpi-card .kpi-label { font-size: 11px; color: var(--muted); margin-bottom: 4px; }
-      .kpi-card .kpi-value { font-size: 20px; font-weight: 700; color: var(--fg); }
-
-      /* Scenarios table */
-      .scenarios-table { width: 100%; border-collapse: collapse; font-size: 13px; }
-      .scenarios-table th { background: var(--bg); padding: 8px; text-align: left; border-bottom: 1px solid var(--border);
-                            color: var(--muted); font-size: 11px; font-weight: 600; white-space: nowrap; }
-      .scenarios-table td { padding: 7px 8px; border-bottom: 1px solid rgba(40,69,95,0.5); }
-      .scenarios-table tr:hover td { background: rgba(255,255,255,0.02); }
-
-      /* Context table */
-      .context-table { width: 100%; border-collapse: collapse; font-size: 12px; }
-      .context-table th { background: var(--bg); padding: 8px; text-align: left; border-bottom: 1px solid var(--border);
-                          color: var(--muted); font-size: 11px; font-weight: 600; white-space: nowrap; }
-      .context-table td { padding: 6px 8px; border-bottom: 1px solid rgba(40,69,95,0.5); vertical-align: top; }
-      .context-value { max-height: 60px; overflow-y: auto; color: #a0c4ff; word-break: break-all; }
-
-      /* Common panel select controls */
-      .panel-controls { display: flex; gap: 8px; align-items: center; flex-wrap: wrap; }
-      .panel-controls select, .panel-controls input[type="number"] {
-        background: var(--bg); color: var(--fg); border: 1px solid var(--border);
-        border-radius: 4px; padding: 4px 8px; font-size: 13px; font-family: inherit;
-      }
-      .panel-date { color: var(--muted); font-size: 12px; }
-      .empty-msg { color: var(--muted); text-align: center; padding: 20px 0; font-size: 12px; }
     </style>
   </head>
   <body>
     <div class="wrap">
-      <!-- Header -->
-      <header>
-        <h1>&#x1F40D; The Ouroboros</h1>
-        <div class="header-right">
-          <span class="mode-badge" id="mode-badge">--</span>
-          <div class="cb-gauge-wrap" id="cb-gauge" title="Circuit Breaker">
-            <span class="cb-dot unknown" id="cb-dot"></span>
-            <span id="cb-label">CB --</span>
-            <div class="cb-bar-wrap">
-              <div class="cb-bar-fill" id="cb-bar" style="width:0%;background:var(--accent)"></div>
-            </div>
-          </div>
-          <span id="last-updated">--</span>
-          <button class="refresh-btn" onclick="refreshAll()">&#x21BA; 새로고침</button>
-        </div>
-      </header>
-
-      <!-- Summary cards -->
-      <div class="cards">
-        <div class="card">
-          <div class="card-label">오늘 거래</div>
-          <div class="card-value neutral" id="card-trades">--</div>
-          <div class="card-sub" id="card-trades-sub">거래 건수</div>
-        </div>
-        <div class="card">
-          <div class="card-label">오늘 P&amp;L</div>
-          <div class="card-value" id="card-pnl">--</div>
-          <div class="card-sub" id="card-pnl-sub">실현 손익</div>
-        </div>
-        <div class="card">
-          <div class="card-label">승률</div>
-          <div class="card-value neutral" id="card-winrate">--</div>
-          <div class="card-sub">전체 누적</div>
-        </div>
-        <div class="card">
-          <div class="card-label">누적 거래</div>
-          <div class="card-value neutral" id="card-total">--</div>
-          <div class="card-sub">전체 기간</div>
-        </div>
-      </div>
-
-      <!-- Open Positions -->
-      <div class="positions-panel">
-        <div class="panel-header">
-          <span class="panel-title">
-            현재 보유 포지션
-            <span class="pos-count" id="positions-count">0</span>
-          </span>
-        </div>
-        <table class="positions-table">
-          <thead>
-            <tr>
-              <th>종목</th>
-              <th>시장</th>
-              <th>수량</th>
-              <th>진입가</th>
-              <th>보유 시간</th>
-            </tr>
-          </thead>
-          <tbody id="positions-body">
-            <tr><td colspan="5" class="pos-empty"><span class="spinner"></span></td></tr>
-          </tbody>
-        </table>
-      </div>
-
-      <!-- P&L Chart -->
-      <div class="chart-panel">
-        <div class="panel-header">
-          <span class="panel-title">P&amp;L 추이</span>
-          <div class="days-selector">
-            <button class="day-btn active" data-days="7" onclick="selectDays(this)">7일</button>
-            <button class="day-btn" data-days="30" onclick="selectDays(this)">30일</button>
-            <button class="day-btn" data-days="90" onclick="selectDays(this)">90일</button>
-          </div>
-        </div>
-        <div class="chart-container">
-          <canvas id="pnl-chart"></canvas>
-          <div class="chart-error" id="chart-error" style="display:none">데이터 없음</div>
-        </div>
-      </div>
-
-      <!-- Decisions log -->
-      <div class="decisions-panel">
-        <div class="panel-header">
-          <span class="panel-title">최근 결정 로그</span>
-          <div class="market-tabs" id="market-tabs">
-            <button class="tab-btn active" data-market="KR" onclick="selectMarket(this)">KR</button>
-            <button class="tab-btn" data-market="US_NASDAQ" onclick="selectMarket(this)">US_NASDAQ</button>
-            <button class="tab-btn" data-market="US_NYSE" onclick="selectMarket(this)">US_NYSE</button>
-            <button class="tab-btn" data-market="JP" onclick="selectMarket(this)">JP</button>
-            <button class="tab-btn" data-market="HK" onclick="selectMarket(this)">HK</button>
-          </div>
-        </div>
-        <table class="decisions-table">
-          <thead>
-            <tr>
-              <th>시각</th>
-              <th>종목</th>
-              <th>액션</th>
-              <th>신뢰도</th>
-              <th>사유</th>
-            </tr>
-          </thead>
-          <tbody id="decisions-body">
-            <tr class="empty-row"><td colspan="5"><span class="spinner"></span></td></tr>
-          </tbody>
-        </table>
-      </div>
-
-      <!-- playbook panel -->
-      <div class="panel playbook-panel">
-        <div class="panel-header">
-          <span class="panel-title">&#x1F4CB; 프리마켓 플레이북</span>
-          <div class="panel-controls">
-            <select id="pb-market-select" onchange="fetchPlaybook()">
-              <option value="KR">KR</option>
-              <option value="US_NASDAQ">US_NASDAQ</option>
-              <option value="US_NYSE">US_NYSE</option>
-            </select>
-            <span id="pb-date" class="panel-date"></span>
-          </div>
-        </div>
-        <div id="playbook-content"><p class="empty-msg">데이터 없음</p></div>
-      </div>
-
-      <!-- scorecard panel -->
-      <div class="panel">
-        <div class="panel-header">
-          <span class="panel-title">&#x1F4CA; 일간 스코어카드</span>
-          <div class="panel-controls">
-            <select id="sc-market-select" onchange="fetchScorecard()">
-              <option value="KR">KR</option>
-              <option value="US_NASDAQ">US_NASDAQ</option>
-            </select>
-            <span id="sc-date" class="panel-date"></span>
-          </div>
-        </div>
-        <div id="scorecard-grid" class="scorecard-grid"><p class="empty-msg">데이터 없음</p></div>
-      </div>
-
-      <!-- scenarios panel -->
-      <div class="panel">
-        <div class="panel-header">
-          <span class="panel-title">&#x1F3AF; 활성 시나리오 매칭</span>
-          <div class="panel-controls">
-            <select id="scen-market-select" onchange="fetchScenarios()">
-              <option value="KR">KR</option>
-              <option value="US_NASDAQ">US_NASDAQ</option>
-            </select>
-          </div>
-        </div>
-        <div id="scenarios-content"><p class="empty-msg">데이터 없음</p></div>
-      </div>
-
-      <!-- context layer panel -->
-      <div class="panel">
-        <div class="panel-header">
-          <span class="panel-title">&#x1F9E0; 컨텍스트 트리</span>
-          <div class="panel-controls">
-            <select id="ctx-layer-select" onchange="fetchContext()">
-              <option value="L7_REALTIME">L7_REALTIME</option>
-              <option value="L6_DAILY">L6_DAILY</option>
-              <option value="L5_WEEKLY">L5_WEEKLY</option>
-              <option value="L4_MONTHLY">L4_MONTHLY</option>
-              <option value="L3_QUARTERLY">L3_QUARTERLY</option>
-              <option value="L2_YEARLY">L2_YEARLY</option>
-              <option value="L1_LIFETIME">L1_LIFETIME</option>
-            </select>
-            <input id="ctx-limit" type="number" value="20" min="1" max="200"
-                   style="width:60px;" onchange="fetchContext()">
-          </div>
-        </div>
-        <div id="context-content"><p class="empty-msg">데이터 없음</p></div>
+      <div 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>`;
-      }
-
-      function fmtPrice(v, market) {
-        if (v === null || v === undefined) return '--';
-        const n = parseFloat(v);
-        const sym = market === 'KR' ? '₩' : market === 'JP' ? '¥' : market === 'HK' ? 'HK$' : '$';
-        return sym + n.toLocaleString('en-US', { minimumFractionDigits: 0, maximumFractionDigits: 4 });
-      }
-
-      async function fetchPositions() {
-        const tbody = document.getElementById('positions-body');
-        const countEl = document.getElementById('positions-count');
-        try {
-          const r = await fetch('/api/positions');
-          if (!r.ok) throw new Error('fetch failed');
-          const d = await r.json();
-          countEl.textContent = d.count ?? 0;
-          if (!d.positions || d.positions.length === 0) {
-            tbody.innerHTML = '<tr><td colspan="5" class="pos-empty">현재 보유 중인 포지션 없음</td></tr>';
-            return;
-          }
-          tbody.innerHTML = d.positions.map(p => `
-            <tr>
-              <td><strong>${p.stock_code || '--'}</strong></td>
-              <td><span style="color:var(--muted);font-size:11px">${p.market || '--'}</span></td>
-              <td>${p.quantity ?? '--'}</td>
-              <td>${fmtPrice(p.entry_price, p.market)}</td>
-              <td style="color:var(--muted);font-size:11px">${p.held || '--'}</td>
-            </tr>
-          `).join('');
-        } catch {
-          tbody.innerHTML = '<tr><td colspan="5" class="pos-empty">데이터 로드 실패</td></tr>';
-        }
-      }
-
-      function renderCbGauge(cb) {
-        if (!cb) return;
-        const dot = document.getElementById('cb-dot');
-        const label = document.getElementById('cb-label');
-        const bar = document.getElementById('cb-bar');
-
-        const status = cb.status || 'unknown';
-        const threshold = cb.threshold_pct ?? -3.0;
-        const current = cb.current_pnl_pct;
-
-        // dot color
-        dot.className = `cb-dot ${status}`;
-
-        // label
-        if (current !== null && current !== undefined) {
-          const sign = current > 0 ? '+' : '';
-          label.textContent = `CB ${sign}${current.toFixed(2)}%`;
-        } else {
-          label.textContent = 'CB --';
-        }
-
-        // bar: fill = how much of the threshold has been consumed (0%=safe, 100%=tripped)
-        const colorMap = { ok: 'var(--accent)', warning: 'var(--warn)', tripped: 'var(--red)', unknown: 'var(--border)' };
-        bar.style.background = colorMap[status] || 'var(--border)';
-        if (current !== null && current !== undefined && threshold < 0) {
-          const fillPct = Math.min(Math.max((current / threshold) * 100, 0), 100);
-          bar.style.width = `${fillPct}%`;
-        } else {
-          bar.style.width = '0%';
-        }
-      }
-
-      async function fetchStatus() {
-        try {
-          const r = await fetch('/api/status');
-          if (!r.ok) return;
-          const d = await r.json();
-          const t = d.totals || {};
-          document.getElementById('card-trades').textContent = t.trade_count ?? '--';
-          const pnlEl = document.getElementById('card-pnl');
-          const pnlV = t.total_pnl;
-          if (pnlV !== undefined) {
-            const n = parseFloat(pnlV);
-            const sign = n > 0 ? '+' : '';
-            pnlEl.textContent = `${sign}${n.toFixed(2)}`;
-            pnlEl.className = `card-value ${n > 0 ? 'positive' : n < 0 ? 'negative' : 'neutral'}`;
-          }
-          document.getElementById('card-pnl-sub').textContent = `결정 ${t.decision_count ?? 0}건`;
-          renderCbGauge(d.circuit_breaker);
-          renderModeBadge(d.mode);
-        } catch {}
-      }
-
-      function renderModeBadge(mode) {
-        const el = document.getElementById('mode-badge');
-        if (!el) return;
-        if (mode === 'live') {
-          el.textContent = '🔴 실전투자';
-          el.className = 'mode-badge live';
-        } else {
-          el.textContent = '🟡 모의투자';
-          el.className = 'mode-badge paper';
-        }
-      }
-
-      async function fetchPerformance() {
-        try {
-          const r = await fetch('/api/performance?market=all');
-          if (!r.ok) return;
-          const d = await r.json();
-          const c = d.combined || {};
-          document.getElementById('card-winrate').textContent = c.win_rate !== undefined ? `${c.win_rate}%` : '--';
-          document.getElementById('card-total').textContent = c.total_trades ?? '--';
-        } catch {}
-      }
-
-      async function fetchPnlHistory(days) {
-        try {
-          const r = await fetch(`/api/pnl/history?days=${days}`);
-          if (!r.ok) throw new Error('fetch failed');
-          const d = await r.json();
-          renderChart(d);
-        } catch {
-          document.getElementById('chart-error').style.display = 'block';
-        }
-      }
-
-      function renderChart(data) {
-        const errEl = document.getElementById('chart-error');
-        if (!data.labels || data.labels.length === 0) {
-          errEl.style.display = 'block';
-          return;
-        }
-        errEl.style.display = 'none';
-
-        const colors = data.pnl.map(v => v >= 0 ? 'rgba(60,179,113,0.75)' : 'rgba(224,85,85,0.75)');
-        const borderColors = data.pnl.map(v => v >= 0 ? '#3cb371' : '#e05555');
-
-        if (pnlChart) { pnlChart.destroy(); pnlChart = null; }
-        const ctx = document.getElementById('pnl-chart').getContext('2d');
-        pnlChart = new Chart(ctx, {
-          type: 'bar',
-          data: {
-            labels: data.labels,
-            datasets: [{
-              label: 'Daily P&L',
-              data: data.pnl,
-              backgroundColor: colors,
-              borderColor: borderColors,
-              borderWidth: 1,
-              borderRadius: 3,
-            }]
-          },
-          options: {
-            responsive: true,
-            maintainAspectRatio: false,
-            plugins: {
-              legend: { display: false },
-              tooltip: {
-                callbacks: {
-                  label: ctx => {
-                    const v = ctx.parsed.y;
-                    const sign = v >= 0 ? '+' : '';
-                    const trades = data.trades[ctx.dataIndex];
-                    return [`P&L: ${sign}${v.toFixed(2)}`, `거래: ${trades}건`];
-                  }
-                }
-              }
-            },
-            scales: {
-              x: {
-                ticks: { color: '#9fb3c8', font: { size: 10 }, maxRotation: 0 },
-                grid: { color: 'rgba(40,69,95,0.4)' }
-              },
-              y: {
-                ticks: { color: '#9fb3c8', font: { size: 10 } },
-                grid: { color: 'rgba(40,69,95,0.4)' }
-              }
-            }
-          }
-        });
-      }
-
-      async function fetchDecisions(market) {
-        const tbody = document.getElementById('decisions-body');
-        tbody.innerHTML = '<tr class="empty-row"><td colspan="5"><span class="spinner"></span></td></tr>';
-        try {
-          const r = await fetch(`/api/decisions?market=${market}&limit=50`);
-          if (!r.ok) throw new Error('fetch failed');
-          const d = await r.json();
-          if (!d.decisions || d.decisions.length === 0) {
-            tbody.innerHTML = '<tr class="empty-row"><td colspan="5">결정 로그 없음</td></tr>';
-            return;
-          }
-          tbody.innerHTML = d.decisions.map(dec => `
-            <tr>
-              <td>${fmt(dec.timestamp)}</td>
-              <td>${dec.stock_code || '--'}</td>
-              <td>${badge(dec.action)}</td>
-              <td>${confBar(dec.confidence)}</td>
-              <td class="rationale-cell" title="${(dec.rationale || '').replace(/"/g, '&quot;')}">${dec.rationale || '--'}</td>
-            </tr>
-          `).join('');
-        } catch {
-          tbody.innerHTML = '<tr class="empty-row"><td colspan="5">데이터 로드 실패</td></tr>';
-        }
-      }
-
-      function selectDays(btn) {
-        document.querySelectorAll('.day-btn').forEach(b => b.classList.remove('active'));
-        btn.classList.add('active');
-        currentDays = parseInt(btn.dataset.days, 10);
-        fetchPnlHistory(currentDays);
-      }
-
-      function selectMarket(btn) {
-        document.querySelectorAll('.tab-btn').forEach(b => b.classList.remove('active'));
-        btn.classList.add('active');
-        currentMarket = btn.dataset.market;
-        fetchDecisions(currentMarket);
-      }
-
-      function todayStr() {
-        return new Date().toISOString().slice(0, 10);
-      }
-
-      function esc(s) {
-        return String(s ?? '').replace(/&/g, '&amp;').replace(/</g, '&lt;').replace(/>/g, '&gt;').replace(/"/g, '&quot;');
-      }
-
-      async function fetchJSON(url) {
-        const r = await fetch(url);
-        if (!r.ok) throw new Error(`HTTP ${r.status}`);
-        return r.json();
-      }
-
-      async function fetchPlaybook() {
-        const market = document.getElementById('pb-market-select').value;
-        const date = todayStr();
-        document.getElementById('pb-date').textContent = date;
-        const el = document.getElementById('playbook-content');
-        try {
-          const data = await fetchJSON(`/api/playbook/${date}?market=${market}`);
-          const stocks = data.stock_playbooks ?? [];
-          if (stocks.length === 0) {
-            el.innerHTML = '<p class="empty-msg">오늘 플레이북 없음</p>';
-            return;
-          }
-          el.innerHTML = stocks.map(sp =>
-            `<details><summary>${esc(sp.stock_code ?? '?')} — ${esc(sp.signal ?? '')}</summary>` +
-            `<pre>${esc(JSON.stringify(sp, null, 2))}</pre></details>`
-          ).join('');
-        } catch {
-          el.innerHTML = '<p class="empty-msg">플레이북 없음 (오늘 미생성 또는 API 오류)</p>';
-        }
-      }
-
-      async function fetchScorecard() {
-        const market = document.getElementById('sc-market-select').value;
-        const date = todayStr();
-        document.getElementById('sc-date').textContent = date;
-        const el = document.getElementById('scorecard-grid');
-        try {
-          const data = await fetchJSON(`/api/scorecard/${date}?market=${market}`);
-          const sc = data.scorecard ?? {};
-          const entries = Object.entries(sc);
-          if (entries.length === 0) {
-            el.innerHTML = '<p class="empty-msg">스코어카드 없음</p>';
-            return;
-          }
-          el.className = 'scorecard-grid';
-          el.innerHTML = entries.map(([k, v]) => `
-            <div class="kpi-card">
-              <div class="kpi-label">${esc(k)}</div>
-              <div class="kpi-value">${typeof v === 'number' ? v.toFixed(2) : esc(String(v))}</div>
-            </div>`).join('');
-        } catch {
-          el.innerHTML = '<p class="empty-msg">스코어카드 없음 (오늘 미생성 또는 API 오류)</p>';
-        }
-      }
-
-      async function fetchScenarios() {
-        const market = document.getElementById('scen-market-select').value;
-        const date = todayStr();
-        const el = document.getElementById('scenarios-content');
-        try {
-          const data = await fetchJSON(`/api/scenarios/active?market=${market}&date_str=${date}&limit=50`);
-          const matches = data.matches ?? [];
-          if (matches.length === 0) {
-            el.innerHTML = '<p class="empty-msg">활성 시나리오 없음</p>';
-            return;
-          }
-          el.innerHTML = `<table class="scenarios-table">
-            <thead><tr><th>종목</th><th>신호</th><th>신뢰도</th><th>매칭 조건</th></tr></thead>
-            <tbody>${matches.map(m => `
-              <tr>
-                <td>${esc(m.stock_code)}</td>
-                <td>${esc(m.signal ?? '-')}</td>
-                <td>${esc(m.confidence ?? '-')}</td>
-                <td><code style="font-size:11px">${esc(JSON.stringify(m.scenario_match ?? {}))}</code></td>
-              </tr>`).join('')}
-            </tbody></table>`;
-        } catch {
-          el.innerHTML = '<p class="empty-msg">데이터 없음</p>';
-        }
-      }
-
-      async function fetchContext() {
-        const layer = document.getElementById('ctx-layer-select').value;
-        const limit = Math.min(Math.max(parseInt(document.getElementById('ctx-limit').value, 10) || 20, 1), 200);
-        const el = document.getElementById('context-content');
-        try {
-          const data = await fetchJSON(`/api/context/${layer}?limit=${limit}`);
-          const entries = data.entries ?? [];
-          if (entries.length === 0) {
-            el.innerHTML = '<p class="empty-msg">컨텍스트 없음</p>';
-            return;
-          }
-          el.innerHTML = `<table class="context-table">
-            <thead><tr><th>timeframe</th><th>key</th><th>value</th><th>updated</th></tr></thead>
-            <tbody>${entries.map(e => `
-              <tr>
-                <td>${esc(e.timeframe)}</td>
-                <td>${esc(e.key)}</td>
-                <td><div class="context-value">${esc(JSON.stringify(e.value ?? e.raw_value))}</div></td>
-                <td style="font-size:11px;color:var(--muted)">${esc((e.updated_at ?? '').slice(0, 16))}</td>
-              </tr>`).join('')}
-            </tbody></table>`;
-        } catch {
-          el.innerHTML = '<p class="empty-msg">데이터 없음</p>';
-        }
-      }
-
-      async function refreshAll() {
-        document.getElementById('last-updated').textContent = '업데이트 중...';
-        await Promise.all([
-          fetchStatus(),
-          fetchPerformance(),
-          fetchPositions(),
-          fetchPnlHistory(currentDays),
-          fetchDecisions(currentMarket),
-          fetchPlaybook(),
-          fetchScorecard(),
-          fetchScenarios(),
-          fetchContext(),
-        ]);
-        const now = new Date();
-        const timeStr = now.toLocaleTimeString('ko-KR', { hour: '2-digit', minute: '2-digit', second: '2-digit', hour12: false });
-        document.getElementById('last-updated').textContent = `마지막 업데이트: ${timeStr}`;
-      }
-
-      // Initial load
-      refreshAll();
-
-      // Auto-refresh every 30 seconds
-      setInterval(refreshAll, 30000);
-    </script>
   </body>
 </html>

src/db.py

@@ -14,11 +14,6 @@ def init_db(db_path: str) -> sqlite3.Connection:
     if db_path != ":memory:":
         Path(db_path).parent.mkdir(parents=True, exist_ok=True)
     conn = sqlite3.connect(db_path)
-    # Enable WAL mode for concurrent read/write (dashboard + trading loop).
-    # WAL does not apply to in-memory databases.
-    if db_path != ":memory:":
-        conn.execute("PRAGMA journal_mode=WAL")
-        conn.execute("PRAGMA busy_timeout=5000")
     conn.execute(
         """
         CREATE TABLE IF NOT EXISTS trades (
@@ -33,13 +28,12 @@ def init_db(db_path: str) -> sqlite3.Connection:
             pnl REAL DEFAULT 0.0,
             market TEXT DEFAULT 'KR',
             exchange_code TEXT DEFAULT 'KRX',
-            decision_id TEXT,
-            mode TEXT DEFAULT 'paper'
+            decision_id TEXT
         )
         """
     )
 
-    # Migration: Add columns if they don't exist (backward-compatible schema upgrades)
+    # Migration: Add market and exchange_code columns if they don't exist
     cursor = conn.execute("PRAGMA table_info(trades)")
     columns = {row[1] for row in cursor.fetchall()}
 
@@ -51,8 +45,6 @@ def init_db(db_path: str) -> sqlite3.Connection:
         conn.execute("ALTER TABLE trades ADD COLUMN selection_context TEXT")
     if "decision_id" not in columns:
         conn.execute("ALTER TABLE trades ADD COLUMN decision_id TEXT")
-    if "mode" not in columns:
-        conn.execute("ALTER TABLE trades ADD COLUMN mode TEXT DEFAULT 'paper'")
 
     # Context tree tables for multi-layered memory management
     conn.execute(
@@ -139,25 +131,6 @@ def init_db(db_path: str) -> sqlite3.Connection:
     conn.execute(
         "CREATE INDEX IF NOT EXISTS idx_decision_logs_confidence ON decision_logs(confidence)"
     )
-
-    # Index for open-position queries (partition by stock_code, market, ordered by timestamp)
-    conn.execute(
-        "CREATE INDEX IF NOT EXISTS idx_trades_stock_market_ts"
-        " ON trades (stock_code, market, timestamp DESC)"
-    )
-
-    # Lightweight key-value store for trading system runtime metrics (dashboard use only)
-    # Intentionally separate from the AI context tree to preserve separation of concerns.
-    conn.execute(
-        """
-        CREATE TABLE IF NOT EXISTS system_metrics (
-            key        TEXT PRIMARY KEY,
-            value      TEXT NOT NULL,
-            updated_at TEXT NOT NULL
-        )
-        """
-    )
-
     conn.commit()
     return conn
 
@@ -175,7 +148,6 @@ def log_trade(
     exchange_code: str = "KRX",
     selection_context: dict[str, any] | None = None,
     decision_id: str | None = None,
-    mode: str = "paper",
 ) -> None:
     """Insert a trade record into the database.
 
@@ -191,8 +163,6 @@ def log_trade(
         market: Market code
         exchange_code: Exchange code
         selection_context: Scanner selection data (RSI, volume_ratio, signal, score)
-        decision_id: Unique decision identifier for audit linking
-        mode: Trading mode ('paper' or 'live') for data separation
     """
     # Serialize selection context to JSON
     context_json = json.dumps(selection_context) if selection_context else None
@@ -201,10 +171,9 @@ def log_trade(
         """
         INSERT INTO trades (
             timestamp, stock_code, action, confidence, rationale,
-            quantity, price, pnl, market, exchange_code, selection_context, decision_id,
-            mode
+            quantity, price, pnl, market, exchange_code, selection_context, decision_id
         )
-        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
         """,
         (
             datetime.now(UTC).isoformat(),
@@ -219,7 +188,6 @@ def log_trade(
             exchange_code,
             context_json,
             decision_id,
-            mode,
         ),
     )
     conn.commit()

src/notifications/telegram_client.py

@@ -4,9 +4,8 @@ import asyncio
 import logging
 import time
 from collections.abc import Awaitable, Callable
-from dataclasses import dataclass, fields
+from dataclasses import dataclass
 from enum import Enum
-from typing import ClassVar
 
 import aiohttp
 
@@ -59,45 +58,6 @@ class LeakyBucket:
                 self._tokens -= 1.0
 
 
-@dataclass
-class NotificationFilter:
-    """Granular on/off flags for each notification type.
-
-    circuit_breaker is intentionally omitted — it is always sent regardless.
-    """
-
-    # Maps user-facing command keys to dataclass field names
-    KEYS: ClassVar[dict[str, str]] = {
-        "trades": "trades",
-        "market": "market_open_close",
-        "fatfinger": "fat_finger",
-        "system": "system_events",
-        "playbook": "playbook",
-        "scenario": "scenario_match",
-        "errors": "errors",
-    }
-
-    trades: bool = True
-    market_open_close: bool = True
-    fat_finger: bool = True
-    system_events: bool = True
-    playbook: bool = True
-    scenario_match: bool = True
-    errors: bool = True
-
-    def set_flag(self, key: str, value: bool) -> bool:
-        """Set a filter flag by user-facing key. Returns False if key is unknown."""
-        field = self.KEYS.get(key.lower())
-        if field is None:
-            return False
-        setattr(self, field, value)
-        return True
-
-    def as_dict(self) -> dict[str, bool]:
-        """Return {user_key: current_value} for display."""
-        return {k: getattr(self, field) for k, field in self.KEYS.items()}
-
-
 @dataclass
 class NotificationMessage:
     """Internal notification message structure."""
@@ -119,7 +79,6 @@ class TelegramClient:
         chat_id: str | None = None,
         enabled: bool = True,
         rate_limit: float = DEFAULT_RATE,
-        notification_filter: NotificationFilter | None = None,
     ) -> None:
         """
         Initialize Telegram client.
@@ -129,14 +88,12 @@ class TelegramClient:
             chat_id: Target chat ID (user or group)
             enabled: Enable/disable notifications globally
             rate_limit: Maximum messages per second
-            notification_filter: Granular per-type on/off flags
         """
         self._bot_token = bot_token
         self._chat_id = chat_id
         self._enabled = enabled
         self._rate_limiter = LeakyBucket(rate=rate_limit)
         self._session: aiohttp.ClientSession | None = None
-        self._filter = notification_filter if notification_filter is not None else NotificationFilter()
 
         if not enabled:
             logger.info("Telegram notifications disabled via configuration")
@@ -161,26 +118,6 @@ class TelegramClient:
         if self._session is not None and not self._session.closed:
             await self._session.close()
 
-    def set_notification(self, key: str, value: bool) -> bool:
-        """Toggle a notification type by user-facing key at runtime.
-
-        Args:
-            key: User-facing key (e.g. "scenario", "market", "all")
-            value: True to enable, False to disable
-
-        Returns:
-            True if key was valid, False if unknown.
-        """
-        if key == "all":
-            for k in NotificationFilter.KEYS:
-                self._filter.set_flag(k, value)
-            return True
-        return self._filter.set_flag(key, value)
-
-    def filter_status(self) -> dict[str, bool]:
-        """Return current per-type filter state keyed by user-facing names."""
-        return self._filter.as_dict()
-
     async def send_message(self, text: str, parse_mode: str = "HTML") -> bool:
         """
         Send a generic text message to Telegram.
@@ -256,8 +193,6 @@ class TelegramClient:
             price: Execution price
             confidence: AI confidence level (0-100)
         """
-        if not self._filter.trades:
-            return
         emoji = "🟢" if action == "BUY" else "🔴"
         message = (
             f"<b>{emoji} {action}</b>\n"
@@ -277,8 +212,6 @@ class TelegramClient:
         Args:
             market_name: Name of the market (e.g., "Korea", "United States")
         """
-        if not self._filter.market_open_close:
-            return
         message = f"<b>Market Open</b>\n{market_name} trading session started"
         await self._send_notification(
             NotificationMessage(priority=NotificationPriority.LOW, message=message)
@@ -292,8 +225,6 @@ class TelegramClient:
             market_name: Name of the market
             pnl_pct: Final P&L percentage for the session
         """
-        if not self._filter.market_open_close:
-            return
         pnl_sign = "+" if pnl_pct >= 0 else ""
         pnl_emoji = "📈" if pnl_pct >= 0 else "📉"
         message = (
@@ -340,8 +271,6 @@ class TelegramClient:
             total_cash: Total available cash
             max_pct: Maximum allowed percentage
         """
-        if not self._filter.fat_finger:
-            return
         attempted_pct = (order_amount / total_cash) * 100 if total_cash > 0 else 0
         message = (
             f"<b>Fat-Finger Protection</b>\n"
@@ -364,8 +293,6 @@ class TelegramClient:
             mode: Trading mode ("paper" or "live")
             enabled_markets: List of enabled market codes
         """
-        if not self._filter.system_events:
-            return
         mode_emoji = "📝" if mode == "paper" else "💰"
         markets_str = ", ".join(enabled_markets)
         message = (
@@ -393,8 +320,6 @@ class TelegramClient:
             scenario_count: Total number of scenarios
             token_count: Gemini token usage for the playbook
         """
-        if not self._filter.playbook:
-            return
         message = (
             f"<b>Playbook Generated</b>\n"
             f"Market: {market}\n"
@@ -422,8 +347,6 @@ class TelegramClient:
             condition_summary: Short summary of the matched condition
             confidence: Scenario confidence (0-100)
         """
-        if not self._filter.scenario_match:
-            return
         message = (
             f"<b>Scenario Matched</b>\n"
             f"Symbol: <code>{stock_code}</code>\n"
@@ -443,8 +366,6 @@ class TelegramClient:
             market: Market code (e.g., "KR", "US")
             reason: Failure reason summary
         """
-        if not self._filter.playbook:
-            return
         message = (
             f"<b>Playbook Failed</b>\n"
             f"Market: {market}\n"
@@ -461,8 +382,6 @@ class TelegramClient:
         Args:
             reason: Reason for shutdown (e.g., "Normal shutdown", "Circuit breaker")
         """
-        if not self._filter.system_events:
-            return
         message = f"<b>System Shutdown</b>\n{reason}"
         priority = (
             NotificationPriority.CRITICAL
@@ -473,48 +392,6 @@ class TelegramClient:
             NotificationMessage(priority=priority, message=message)
         )
 
-    async def notify_unfilled_order(
-        self,
-        stock_code: str,
-        market: str,
-        action: str,
-        quantity: int,
-        outcome: str,
-        new_price: float | None = None,
-    ) -> None:
-        """Notify about an unfilled overseas order that was cancelled or resubmitted.
-
-        Args:
-            stock_code: Stock ticker symbol.
-            market: Exchange/market code (e.g., "NASD", "SEHK").
-            action: "BUY" or "SELL".
-            quantity: Unfilled quantity.
-            outcome: "cancelled" or "resubmitted".
-            new_price: New order price if resubmitted (None if only cancelled).
-        """
-        if not self._filter.trades:
-            return
-        # SELL resubmit is high priority — position liquidation at risk.
-        # BUY cancel is medium priority — only cash is freed.
-        priority = (
-            NotificationPriority.HIGH
-            if action == "SELL"
-            else NotificationPriority.MEDIUM
-        )
-        outcome_emoji = "🔄" if outcome == "resubmitted" else "❌"
-        outcome_label = "재주문" if outcome == "resubmitted" else "취소됨"
-        action_emoji = "🔴" if action == "SELL" else "🟢"
-        lines = [
-            f"<b>{outcome_emoji} 미체결 주문 {outcome_label}</b>",
-            f"Symbol: <code>{stock_code}</code> ({market})",
-            f"Action: {action_emoji} {action}",
-            f"Quantity: {quantity:,} shares",
-        ]
-        if new_price is not None:
-            lines.append(f"New Price: {new_price:.4f}")
-        message = "\n".join(lines)
-        await self._send_notification(NotificationMessage(priority=priority, message=message))
-
     async def notify_error(
         self, error_type: str, error_msg: str, context: str
     ) -> None:
@@ -526,8 +403,6 @@ class TelegramClient:
             error_msg: Error message
             context: Error context (e.g., stock code, market)
         """
-        if not self._filter.errors:
-            return
         message = (
             f"<b>Error: {error_type}</b>\n"
             f"Context: {context}\n"
@@ -554,7 +429,6 @@ class TelegramCommandHandler:
         self._client = client
         self._polling_interval = polling_interval
         self._commands: dict[str, Callable[[], Awaitable[None]]] = {}
-        self._commands_with_args: dict[str, Callable[[list[str]], Awaitable[None]]] = {}
         self._last_update_id = 0
         self._polling_task: asyncio.Task[None] | None = None
         self._running = False
@@ -563,7 +437,7 @@ class TelegramCommandHandler:
         self, command: str, handler: Callable[[], Awaitable[None]]
     ) -> None:
         """
-        Register a command handler (no arguments).
+        Register a command handler.
 
         Args:
             command: Command name (without leading slash, e.g., "start")
@@ -572,19 +446,6 @@ class TelegramCommandHandler:
         self._commands[command] = handler
         logger.debug("Registered command handler: /%s", command)
 
-    def register_command_with_args(
-        self, command: str, handler: Callable[[list[str]], Awaitable[None]]
-    ) -> None:
-        """
-        Register a command handler that receives trailing arguments.
-
-        Args:
-            command: Command name (without leading slash, e.g., "notify")
-            handler: Async function receiving list of argument tokens
-        """
-        self._commands_with_args[command] = handler
-        logger.debug("Registered command handler (with args): /%s", command)
-
     async def start_polling(self) -> None:
         """Start long polling for commands."""
         if self._running:
@@ -646,19 +507,9 @@ class TelegramCommandHandler:
             async with session.post(url, json=payload) as resp:
                 if resp.status != 200:
                     error_text = await resp.text()
-                    if resp.status == 409:
-                        # Another bot instance is already polling — stop this poller entirely.
-                        # Retrying would keep conflicting with the other instance.
-                        self._running = False
-                        logger.warning(
-                            "Telegram conflict (409): another instance is already polling. "
-                            "Disabling Telegram commands for this process. "
-                            "Ensure only one instance of The Ouroboros is running at a time.",
-                        )
-                    else:
-                        logger.error(
-                            "getUpdates API error (status=%d): %s", resp.status, error_text
-                        )
+                    logger.error(
+                        "getUpdates API error (status=%d): %s", resp.status, error_text
+                    )
                     return []
 
                 data = await resp.json()
@@ -715,14 +566,11 @@ class TelegramCommandHandler:
             # Remove @botname suffix if present (for group chats)
             command_name = command_parts[0].split("@")[0]
 
-            # Execute handler (args-aware handlers take priority)
-            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(

src/strategies/v20260220_210124_evolved.py

@@ -1,114 +0,0 @@
-"""Auto-generated strategy: v20260220_210124
-
-Generated at: 2026-02-20T21:01:24.706847+00:00
-Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
-"""
-
-from __future__ import annotations
-from typing import Any
-from src.strategies.base import BaseStrategy
-
-
-class Strategy_v20260220_210124(BaseStrategy):
-    """Strategy: v20260220_210124"""
-
-    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
-        import datetime
-
-        # --- Strategy Constants ---
-        # Minimum price for a stock to be considered for trading (avoids penny stocks)
-        MIN_PRICE = 5.0
-
-        # Momentum signal thresholds (stricter than previous failures)
-        MOMENTUM_PRICE_CHANGE_THRESHOLD = 7.0  # % price change
-        MOMENTUM_VOLUME_RATIO_THRESHOLD = 4.0  # X times average volume
-
-        # Oversold signal thresholds (more conservative)
-        OVERSOLD_RSI_THRESHOLD = 25.0  # RSI value (lower means more oversold)
-
-        # Confidence levels
-        CONFIDENCE_HOLD = 30
-        CONFIDENCE_BUY_OVERSOLD = 65
-        CONFIDENCE_BUY_MOMENTUM = 85
-        CONFIDENCE_BUY_STRONG_MOMENTUM = 90  # For higher-priced stocks with strong momentum
-
-        # Market hours in UTC (9:30 AM ET to 4:00 PM ET)
-        MARKET_OPEN_UTC = datetime.time(14, 30)
-        MARKET_CLOSE_UTC = datetime.time(21, 0)
-
-        # Volatile periods within market hours (UTC) to avoid
-        # First hour after open (14:30 UTC - 15:30 UTC)
-        VOLATILE_OPEN_END_UTC = datetime.time(15, 30)
-        # Last 30 minutes before close (20:30 UTC - 21:00 UTC)
-        VOLATILE_CLOSE_START_UTC = datetime.time(20, 30)
-
-        current_price = market_data.get('current_price')
-        price_change_pct = market_data.get('price_change_pct')
-        volume_ratio = market_data.get('volume_ratio')  # Assumed pre-computed indicator
-        rsi = market_data.get('rsi')                    # Assumed pre-computed indicator
-        timestamp_str = market_data.get('timestamp')
-
-        action = "HOLD"
-        confidence = CONFIDENCE_HOLD
-        rationale = "Initial HOLD: No clear signal or conditions not met."
-
-        # --- 1. Basic Data Validation ---
-        if current_price is None or price_change_pct is None:
-            return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
-                    "rationale": "Insufficient core data (price or price change) to evaluate."}
-
-        # --- 2. Price Filter: Avoid low-priced/penny stocks ---
-        if current_price < MIN_PRICE:
-            return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
-                    "rationale": f"Avoiding low-priced stock (${current_price:.2f} < ${MIN_PRICE:.2f})."}
-
-        # --- 3. Time Filter: Only trade during core market hours ---
-        if timestamp_str:
-            try:
-                dt_object = datetime.datetime.fromisoformat(timestamp_str)
-                current_time_utc = dt_object.time()
-
-                if not (MARKET_OPEN_UTC <= current_time_utc < MARKET_CLOSE_UTC):
-                    return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
-                            "rationale": f"Avoiding trade outside core market hours ({current_time_utc} UTC)."}
-
-                if (MARKET_OPEN_UTC <= current_time_utc < VOLATILE_OPEN_END_UTC) or \
-                   (VOLATILE_CLOSE_START_UTC <= current_time_utc < MARKET_CLOSE_UTC):
-                    return {"action": "HOLD", "confidence": CONFIDENCE_HOLD,
-                            "rationale": f"Avoiding trade during volatile market open/close periods ({current_time_utc} UTC)."}
-
-            except ValueError:
-                rationale += " (Warning: Malformed timestamp, time filters skipped)"
-
-        # --- Initialize signal states ---
-        has_momentum_buy_signal = False
-        has_oversold_buy_signal = False
-
-        # --- 4. Evaluate Enhanced Buy Signals ---
-
-        # Momentum Buy Signal
-        if volume_ratio is not None and \
-           price_change_pct > MOMENTUM_PRICE_CHANGE_THRESHOLD and \
-           volume_ratio > MOMENTUM_VOLUME_RATIO_THRESHOLD:
-            has_momentum_buy_signal = True
-            rationale = f"Momentum BUY: Price change {price_change_pct:.2f}%, Volume {volume_ratio:.2f}x."
-            confidence = CONFIDENCE_BUY_MOMENTUM
-            if current_price >= 10.0:
-                confidence = CONFIDENCE_BUY_STRONG_MOMENTUM
-
-        # Oversold Buy Signal
-        if rsi is not None and rsi < OVERSOLD_RSI_THRESHOLD:
-            has_oversold_buy_signal = True
-            if not has_momentum_buy_signal:
-                rationale = f"Oversold BUY: RSI {rsi:.2f}."
-                confidence = CONFIDENCE_BUY_OVERSOLD
-                if current_price >= 10.0:
-                    confidence = min(CONFIDENCE_BUY_OVERSOLD + 5, 80)
-
-        # --- 5. Decision Logic ---
-        if has_momentum_buy_signal:
-            action = "BUY"
-        elif has_oversold_buy_signal:
-            action = "BUY"
-
-        return {"action": action, "confidence": confidence, "rationale": rationale}

src/strategies/v20260220_210159_evolved.py

@@ -1,97 +0,0 @@
-"""Auto-generated strategy: v20260220_210159
-
-Generated at: 2026-02-20T21:01:59.391523+00:00
-Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
-"""
-
-from __future__ import annotations
-from typing import Any
-from src.strategies.base import BaseStrategy
-
-
-class Strategy_v20260220_210159(BaseStrategy):
-    """Strategy: v20260220_210159"""
-
-    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
-        import datetime
-
-        current_price = market_data.get('current_price')
-        price_change_pct = market_data.get('price_change_pct')
-        volume_ratio = market_data.get('volume_ratio')
-        rsi = market_data.get('rsi')
-        timestamp_str = market_data.get('timestamp')
-        market_name = market_data.get('market')
-
-        # Default action
-        action = "HOLD"
-        confidence = 0
-        rationale = "No strong signal or conditions not met."
-
-        # --- FAILURE PATTERN AVOIDANCE ---
-
-        # 1. Avoid low-priced/penny stocks
-        MIN_PRICE_THRESHOLD = 5.0  # USD
-        if current_price is not None and current_price < MIN_PRICE_THRESHOLD:
-            rationale = (
-                f"HOLD: Stock price (${current_price:.2f}) is below minimum threshold "
-                f"(${MIN_PRICE_THRESHOLD:.2f}). Past failures consistently involved low-priced stocks."
-            )
-            return {"action": action, "confidence": confidence, "rationale": rationale}
-
-        # 2. Avoid early market hour volatility
-        if timestamp_str:
-            try:
-                dt_obj = datetime.datetime.fromisoformat(timestamp_str)
-                utc_hour = dt_obj.hour
-                utc_minute = dt_obj.minute
-
-                if (utc_hour == 14 and utc_minute < 45) or (utc_hour == 13 and utc_minute >= 30):
-                    rationale = (
-                        f"HOLD: Trading during early market hours (UTC {utc_hour}:{utc_minute}), "
-                        f"a period identified with past failures due to high volatility."
-                    )
-                    return {"action": action, "confidence": confidence, "rationale": rationale}
-            except ValueError:
-                pass
-
-        # --- IMPROVED BUY STRATEGY ---
-
-        # Momentum BUY signal
-        if volume_ratio is not None and price_change_pct is not None:
-            if price_change_pct > 7.0 and volume_ratio > 3.0:
-                action = "BUY"
-                confidence = 70
-                rationale = "Improved BUY: Momentum signal with high volume and above price threshold."
-
-                if market_name == 'US_AMEX':
-                    confidence = max(55, confidence - 5)
-                    rationale += " (Adjusted lower for AMEX market's higher risk profile)."
-                elif market_name == 'US_NASDAQ' and price_change_pct > 20:
-                    confidence = max(50, confidence - 10)
-                    rationale += " (Adjusted lower for aggressive NASDAQ momentum volatility)."
-
-                if price_change_pct > 15.0:
-                    confidence = max(50, confidence - 5)
-                    rationale += " (Caution: Very high daily price change, potential for reversal)."
-
-                return {"action": action, "confidence": confidence, "rationale": rationale}
-
-        # Oversold BUY signal
-        if rsi is not None and price_change_pct is not None:
-            if rsi < 30 and price_change_pct < -3.0:
-                action = "BUY"
-                confidence = 65
-                rationale = "Improved BUY: Oversold signal with recent decline and above price threshold."
-
-                if market_name == 'US_AMEX':
-                    confidence = max(50, confidence - 5)
-                    rationale += " (Adjusted lower for AMEX market's higher risk on oversold assets)."
-
-                if price_change_pct < -10.0:
-                    confidence = max(45, confidence - 10)
-                    rationale += " (Caution: Very steep decline, potential falling knife)."
-
-                return {"action": action, "confidence": confidence, "rationale": rationale}
-
-        # If no specific BUY signal, default to HOLD
-        return {"action": action, "confidence": confidence, "rationale": rationale}

src/strategies/v20260220_210244_evolved.py

@@ -1,88 +0,0 @@
-"""Auto-generated strategy: v20260220_210244
-
-Generated at: 2026-02-20T21:02:44.387355+00:00
-Rationale: Auto-evolved from 6 failures. Primary failure markets: ['US_AMEX', 'US_NYSE', 'US_NASDAQ']. Average loss: -194.69
-"""
-
-from __future__ import annotations
-from typing import Any
-from src.strategies.base import BaseStrategy
-
-
-class Strategy_v20260220_210244(BaseStrategy):
-    """Strategy: v20260220_210244"""
-
-    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
-        from datetime import datetime
-
-        # Extract required data points safely
-        current_price = market_data.get("current_price")
-        price_change_pct = market_data.get("price_change_pct")
-        volume_ratio = market_data.get("volume_ratio")
-        rsi = market_data.get("rsi")
-        timestamp_str = market_data.get("timestamp")
-        market_name = market_data.get("market")
-        stock_code = market_data.get("stock_code", "UNKNOWN")
-
-        # Default action is HOLD with conservative confidence and rationale
-        action = "HOLD"
-        confidence = 50
-        rationale = f"No strong BUY signal for {stock_code} or awaiting more favorable conditions after avoiding known failure patterns."
-
-        # --- 1. Failure Pattern Avoidance Filters ---
-
-        # A. Avoid low-priced (penny) stocks
-        if current_price is not None and current_price < 5.0:
-            return {
-                "action": "HOLD",
-                "confidence": 50,
-                "rationale": f"AVOID {stock_code}: Stock price (${current_price:.2f}) is below minimum threshold ($5.00) for BUY action. Identified past failures on highly volatile, low-priced stocks."
-            }
-
-        # B. Avoid initiating BUY trades during identified high-volatility hours
-        if timestamp_str:
-            try:
-                trade_hour = datetime.fromisoformat(timestamp_str).hour
-                if trade_hour in [14, 20]:
-                    return {
-                        "action": "HOLD",
-                        "confidence": 50,
-                        "rationale": f"AVOID {stock_code}: Trading during historically volatile hour ({trade_hour} UTC) where previous BUYs resulted in losses. Prefer to observe market stability."
-                    }
-            except ValueError:
-                pass
-
-        # C. Be cautious with extreme momentum spikes
-        if volume_ratio is not None and price_change_pct is not None:
-            if volume_ratio >= 9.0 and price_change_pct >= 15.0:
-                return {
-                    "action": "HOLD",
-                    "confidence": 50,
-                    "rationale": f"AVOID {stock_code}: Extreme short-term momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Historical failures indicate buying into such rapid spikes often leads to reversals."
-                }
-
-        # D. Be cautious with "oversold" signals without further confirmation
-        if rsi is not None and rsi < 30:
-            return {
-                "action": "HOLD",
-                "confidence": 50,
-                "rationale": f"AVOID {stock_code}: Oversold signal (RSI={rsi:.1f}) detected. While often a BUY signal, historical failures on similar 'oversold' trades suggest waiting for stronger confirmation."
-            }
-
-        # --- 2. Improved BUY Signal Generation ---
-        if volume_ratio is not None and 2.0 <= volume_ratio < 9.0 and \
-           price_change_pct is not None and 2.0 <= price_change_pct < 15.0:
-
-            action = "BUY"
-            confidence = 70
-            rationale = f"BUY {stock_code}: Moderate momentum detected (price change: +{price_change_pct:.2f}%, volume ratio: {volume_ratio:.1f}x). Passed filters for price and extreme momentum, avoiding past failure patterns."
-
-            if market_name in ["US_AMEX", "US_NASDAQ"]:
-                confidence = max(60, confidence - 5)
-                rationale += f" Adjusted confidence for {market_name} market characteristics."
-            elif market_name == "US_NYSE":
-                confidence = max(65, confidence)
-
-            confidence = max(50, min(85, confidence))
-
-        return {"action": action, "confidence": confidence, "rationale": rationale}

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,
             )
         )
 

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
@@ -75,7 +74,6 @@ class PreMarketPlanner:
         market: str,
         candidates: list[ScanCandidate],
         today: date | None = None,
-        current_holdings: list[dict] | None = None,
     ) -> DayPlaybook:
         """Generate a DayPlaybook for a market using Gemini.
 
@@ -83,10 +81,6 @@ class PreMarketPlanner:
             market: Market code ("KR" or "US")
             candidates: Stock candidates from SmartVolatilityScanner
             today: Override date (defaults to date.today()). Use market-local date.
-            current_holdings: Currently held positions with entry_price and unrealized_pnl_pct.
-                Each dict: {"stock_code": str, "name": str, "qty": int,
-                            "entry_price": float, "unrealized_pnl_pct": float,
-                            "holding_days": int}
 
         Returns:
             DayPlaybook with scenarios. Empty/defensive if no candidates or failure.
@@ -111,7 +105,6 @@ class PreMarketPlanner:
                 context_data,
                 self_market_scorecard,
                 cross_market,
-                current_holdings=current_holdings,
             )
 
             # 3. Call Gemini
@@ -124,8 +117,7 @@ class PreMarketPlanner:
 
             # 4. Parse response
             playbook = self._parse_response(
-                decision.rationale, today, market, candidates, cross_market,
-                current_holdings=current_holdings,
+                decision.rationale, today, market, candidates, cross_market
             )
             playbook_with_tokens = playbook.model_copy(
                 update={"token_count": decision.token_count}
@@ -142,7 +134,7 @@ class PreMarketPlanner:
         except Exception:
             logger.exception("Playbook generation failed for %s", market)
             if self._settings.DEFENSIVE_PLAYBOOK_ON_FAILURE:
-                return self._smart_fallback_playbook(today, market, candidates, self._settings)
+                return self._defensive_playbook(today, market, candidates)
             return self._empty_playbook(today, market)
 
     def build_cross_market_context(
@@ -237,7 +229,6 @@ class PreMarketPlanner:
         context_data: dict[str, Any],
         self_market_scorecard: dict[str, Any] | None,
         cross_market: CrossMarketContext | None,
-        current_holdings: list[dict] | None = None,
     ) -> str:
         """Build a structured prompt for Gemini to generate scenario JSON."""
         max_scenarios = self._settings.MAX_SCENARIOS_PER_STOCK
@@ -249,26 +240,6 @@ class PreMarketPlanner:
             for c in candidates
         )
 
-        holdings_text = ""
-        if current_holdings:
-            lines = []
-            for h in current_holdings:
-                code = h.get("stock_code", "")
-                name = h.get("name", "")
-                qty = h.get("qty", 0)
-                entry_price = h.get("entry_price", 0.0)
-                pnl_pct = h.get("unrealized_pnl_pct", 0.0)
-                holding_days = h.get("holding_days", 0)
-                lines.append(
-                    f"  - {code} ({name}): {qty}주 @ {entry_price:,.0f}, "
-                    f"미실현손익 {pnl_pct:+.2f}%, 보유 {holding_days}일"
-                )
-            holdings_text = (
-                "\n## Current Holdings (보유 중 — SELL/HOLD 전략 고려 필요)\n"
-                + "\n".join(lines)
-                + "\n"
-            )
-
         cross_market_text = ""
         if cross_market:
             cross_market_text = (
@@ -301,20 +272,10 @@ class PreMarketPlanner:
                     for key, value in list(layer_data.items())[:5]:
                         context_text += f"  - {key}: {value}\n"
 
-        holdings_instruction = ""
-        if current_holdings:
-            holding_codes = [h.get("stock_code", "") for h in current_holdings]
-            holdings_instruction = (
-                f"- Also include SELL/HOLD scenarios for held stocks: "
-                f"{', '.join(holding_codes)} "
-                f"(even if not in candidates list)\n"
-            )
-
         return (
             f"You are a pre-market trading strategist for the {market} market.\n"
             f"Generate structured trading scenarios for today.\n\n"
             f"## Candidates (from volatility scanner)\n{candidates_text}\n"
-            f"{holdings_text}"
             f"{self_market_text}"
             f"{cross_market_text}"
             f"{context_text}\n"
@@ -332,8 +293,7 @@ class PreMarketPlanner:
             f'      "stock_code": "...",\n'
             f'      "scenarios": [\n'
             f'        {{\n'
-            f'          "condition": {{"rsi_below": 30, "volume_ratio_above": 2.0,'
-            f' "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'
@@ -347,8 +307,7 @@ class PreMarketPlanner:
             f'}}\n\n'
             f"Rules:\n"
             f"- Max {max_scenarios} scenarios per stock\n"
-            f"- Candidates list is the primary source for BUY candidates\n"
-            f"{holdings_instruction}"
+            f"- Only use stocks from the candidates list\n"
             f"- Confidence 0-100 (80+ for actionable trades)\n"
             f"- stop_loss_pct must be <= 0, take_profit_pct must be >= 0\n"
             f"- Return ONLY the JSON, no markdown fences or explanation\n"
@@ -361,19 +320,12 @@ class PreMarketPlanner:
         market: str,
         candidates: list[ScanCandidate],
         cross_market: CrossMarketContext | None,
-        current_holdings: list[dict] | None = None,
     ) -> DayPlaybook:
         """Parse Gemini's JSON response into a validated DayPlaybook."""
         cleaned = self._extract_json(response_text)
         data = json.loads(cleaned)
 
         valid_codes = {c.stock_code for c in candidates}
-        # Holdings are also valid — AI may generate SELL/HOLD scenarios for them
-        if current_holdings:
-            for h in current_holdings:
-                code = h.get("stock_code", "")
-                if code:
-                    valid_codes.add(code)
 
         # Parse market outlook
         outlook_str = data.get("market_outlook", "neutral")
@@ -437,10 +389,6 @@ class PreMarketPlanner:
                 price_below=cond_data.get("price_below"),
                 price_change_pct_above=cond_data.get("price_change_pct_above"),
                 price_change_pct_below=cond_data.get("price_change_pct_below"),
-                unrealized_pnl_pct_above=cond_data.get("unrealized_pnl_pct_above"),
-                unrealized_pnl_pct_below=cond_data.get("unrealized_pnl_pct_below"),
-                holding_days_above=cond_data.get("holding_days_above"),
-                holding_days_below=cond_data.get("holding_days_below"),
             )
 
             if not condition.has_any_condition():
@@ -522,99 +470,3 @@ class PreMarketPlanner:
                 ),
             ],
         )
-
-    @staticmethod
-    def _smart_fallback_playbook(
-        today: date,
-        market: str,
-        candidates: list[ScanCandidate],
-        settings: Settings,
-    ) -> DayPlaybook:
-        """Rule-based fallback playbook when Gemini is unavailable.
-
-        Uses scanner signals (RSI, volume_ratio) to generate meaningful BUY
-        conditions instead of the all-SELL defensive playbook.  Candidates are
-        already pre-qualified by SmartVolatilityScanner, so we trust their
-        signals and build actionable scenarios from them.
-
-        Scenario logic per candidate:
-        - momentum signal: BUY when volume_ratio exceeds scanner threshold
-        - oversold signal: BUY when RSI is below oversold threshold
-        - always: SELL stop-loss at -3.0% as guard
-        """
-        stock_playbooks = []
-        for c in candidates:
-            scenarios: list[StockScenario] = []
-
-            if c.signal == "momentum":
-                scenarios.append(
-                    StockScenario(
-                        condition=StockCondition(
-                            volume_ratio_above=settings.VOL_MULTIPLIER,
-                        ),
-                        action=ScenarioAction.BUY,
-                        confidence=80,
-                        allocation_pct=10.0,
-                        stop_loss_pct=-3.0,
-                        take_profit_pct=5.0,
-                        rationale=(
-                            f"Rule-based BUY: momentum signal, "
-                            f"volume={c.volume_ratio:.1f}x (fallback planner)"
-                        ),
-                    )
-                )
-            elif c.signal == "oversold":
-                scenarios.append(
-                    StockScenario(
-                        condition=StockCondition(
-                            rsi_below=settings.RSI_OVERSOLD_THRESHOLD,
-                        ),
-                        action=ScenarioAction.BUY,
-                        confidence=80,
-                        allocation_pct=10.0,
-                        stop_loss_pct=-3.0,
-                        take_profit_pct=5.0,
-                        rationale=(
-                            f"Rule-based BUY: oversold signal, "
-                            f"RSI={c.rsi:.0f} (fallback planner)"
-                        ),
-                    )
-                )
-
-            # Always add stop-loss guard
-            scenarios.append(
-                StockScenario(
-                    condition=StockCondition(price_change_pct_below=-3.0),
-                    action=ScenarioAction.SELL,
-                    confidence=90,
-                    stop_loss_pct=-3.0,
-                    rationale="Rule-based stop-loss (fallback planner)",
-                )
-            )
-
-            stock_playbooks.append(
-                StockPlaybook(
-                    stock_code=c.stock_code,
-                    scenarios=scenarios,
-                )
-            )
-
-        logger.info(
-            "Smart fallback playbook for %s: %d stocks with rule-based BUY/SELL conditions",
-            market,
-            len(stock_playbooks),
-        )
-        return DayPlaybook(
-            date=today,
-            market=market,
-            market_outlook=MarketOutlook.NEUTRAL,
-            default_action=ScenarioAction.HOLD,
-            stock_playbooks=stock_playbooks,
-            global_rules=[
-                GlobalRule(
-                    condition="portfolio_pnl_pct < -2.0",
-                    action=ScenarioAction.REDUCE_ALL,
-                    rationale="Defensive: reduce on loss threshold",
-                ),
-            ],
-        )

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

tests/test_backup.py

@@ -3,11 +3,9 @@
 from __future__ import annotations
 
 import sqlite3
-import sys
 import tempfile
 from datetime import UTC, datetime, timedelta
 from pathlib import Path
-from unittest.mock import MagicMock, patch
 
 import pytest
 
@@ -365,435 +363,3 @@ class TestHealthMonitor:
         assert "timestamp" in report
         assert "checks" in report
         assert len(report["checks"]) == 3
-
-
-# ---------------------------------------------------------------------------
-# BackupExporter — additional coverage for previously uncovered branches
-# ---------------------------------------------------------------------------
-
-
-@pytest.fixture
-def empty_db(tmp_path: Path) -> Path:
-    """Create a temporary database with NO trade records."""
-    db_path = tmp_path / "empty_trades.db"
-    conn = sqlite3.connect(str(db_path))
-    conn.execute(
-        """CREATE TABLE trades (
-            id INTEGER PRIMARY KEY AUTOINCREMENT,
-            timestamp TEXT NOT NULL,
-            stock_code TEXT NOT NULL,
-            action TEXT NOT NULL,
-            quantity INTEGER NOT NULL,
-            price REAL NOT NULL,
-            confidence INTEGER NOT NULL,
-            rationale TEXT,
-            pnl REAL DEFAULT 0.0
-        )"""
-    )
-    conn.commit()
-    conn.close()
-    return db_path
-
-
-class TestBackupExporterAdditional:
-    """Cover branches missed in the original TestBackupExporter suite."""
-
-    def test_export_all_default_formats(self, temp_db: Path, tmp_path: Path) -> None:
-        """export_all with formats=None must default to JSON+CSV+Parquet path."""
-        exporter = BackupExporter(str(temp_db))
-        # formats=None triggers the default list assignment (line 62)
-        results = exporter.export_all(tmp_path / "out", formats=None, compress=False)
-        # JSON and CSV must always succeed; Parquet needs pyarrow
-        assert ExportFormat.JSON in results
-        assert ExportFormat.CSV in results
-
-    def test_export_all_logs_error_on_failure(
-        self, temp_db: Path, tmp_path: Path
-    ) -> None:
-        """export_all must log an error and continue when one format fails."""
-        exporter = BackupExporter(str(temp_db))
-        # Patch _export_format to raise on JSON, succeed on CSV
-        original = exporter._export_format
-
-        def failing_export(fmt, *args, **kwargs):  # type: ignore[no-untyped-def]
-            if fmt == ExportFormat.JSON:
-                raise RuntimeError("simulated failure")
-            return original(fmt, *args, **kwargs)
-
-        exporter._export_format = failing_export  # type: ignore[method-assign]
-        results = exporter.export_all(
-            tmp_path / "out",
-            formats=[ExportFormat.JSON, ExportFormat.CSV],
-            compress=False,
-        )
-        # JSON failed → not in results; CSV succeeded → in results
-        assert ExportFormat.JSON not in results
-        assert ExportFormat.CSV in results
-
-    def test_export_csv_empty_trades_no_compress(
-        self, empty_db: Path, tmp_path: Path
-    ) -> None:
-        """CSV export with no trades and compress=False must write header row only."""
-        exporter = BackupExporter(str(empty_db))
-        results = exporter.export_all(
-            tmp_path / "out",
-            formats=[ExportFormat.CSV],
-            compress=False,
-        )
-        assert ExportFormat.CSV in results
-        out = results[ExportFormat.CSV]
-        assert out.exists()
-        content = out.read_text()
-        assert "timestamp" in content
-
-    def test_export_csv_empty_trades_compressed(
-        self, empty_db: Path, tmp_path: Path
-    ) -> None:
-        """CSV export with no trades and compress=True must write gzipped header."""
-        import gzip
-
-        exporter = BackupExporter(str(empty_db))
-        results = exporter.export_all(
-            tmp_path / "out",
-            formats=[ExportFormat.CSV],
-            compress=True,
-        )
-        assert ExportFormat.CSV in results
-        out = results[ExportFormat.CSV]
-        assert out.suffix == ".gz"
-        with gzip.open(out, "rt", encoding="utf-8") as f:
-            content = f.read()
-        assert "timestamp" in content
-
-    def test_export_csv_with_data_compressed(
-        self, temp_db: Path, tmp_path: Path
-    ) -> None:
-        """CSV export with data and compress=True must write gzipped rows."""
-        import gzip
-
-        exporter = BackupExporter(str(temp_db))
-        results = exporter.export_all(
-            tmp_path / "out",
-            formats=[ExportFormat.CSV],
-            compress=True,
-        )
-        assert ExportFormat.CSV in results
-        out = results[ExportFormat.CSV]
-        with gzip.open(out, "rt", encoding="utf-8") as f:
-            lines = f.readlines()
-        # Header + 3 data rows
-        assert len(lines) == 4
-
-    def test_export_parquet_raises_import_error_without_pyarrow(
-        self, temp_db: Path, tmp_path: Path
-    ) -> None:
-        """Parquet export must raise ImportError when pyarrow is not installed."""
-        exporter = BackupExporter(str(temp_db))
-        with patch.dict(sys.modules, {"pyarrow": None, "pyarrow.parquet": None}):
-            try:
-                import pyarrow  # noqa: F401
-                pytest.skip("pyarrow is installed; cannot test ImportError path")
-            except ImportError:
-                pass
-            results = exporter.export_all(
-                tmp_path / "out",
-                formats=[ExportFormat.PARQUET],
-                compress=False,
-            )
-            # Parquet export fails gracefully; result dict should not contain it
-            assert ExportFormat.PARQUET not in results
-
-
-# ---------------------------------------------------------------------------
-# CloudStorage — mocked boto3 tests
-# ---------------------------------------------------------------------------
-
-
-@pytest.fixture
-def mock_boto3_module():
-    """Inject a fake boto3 into sys.modules for the duration of the test."""
-    mock = MagicMock()
-    with patch.dict(sys.modules, {"boto3": mock}):
-        yield mock
-
-
-@pytest.fixture
-def s3_config():
-    """Minimal S3Config for tests."""
-    from src.backup.cloud_storage import S3Config
-
-    return S3Config(
-        endpoint_url="http://localhost:9000",
-        access_key="minioadmin",
-        secret_key="minioadmin",
-        bucket_name="test-bucket",
-        region="us-east-1",
-    )
-
-
-class TestCloudStorage:
-    """Test CloudStorage using mocked boto3."""
-
-    def test_init_creates_s3_client(self, mock_boto3_module, s3_config) -> None:
-        """CloudStorage.__init__ must call boto3.client with the correct args."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        mock_boto3_module.client.assert_called_once()
-        call_kwargs = mock_boto3_module.client.call_args[1]
-        assert call_kwargs["aws_access_key_id"] == "minioadmin"
-        assert call_kwargs["aws_secret_access_key"] == "minioadmin"
-        assert storage.config == s3_config
-
-    def test_init_raises_if_boto3_missing(self, s3_config) -> None:
-        """CloudStorage.__init__ must raise ImportError when boto3 is absent."""
-        with patch.dict(sys.modules, {"boto3": None}):  # type: ignore[dict-item]
-            with pytest.raises((ImportError, TypeError)):
-                # Re-import to trigger the try/except inside __init__
-                import importlib
-
-                import src.backup.cloud_storage as m
-
-                importlib.reload(m)
-                m.CloudStorage(s3_config)
-
-    def test_upload_file_success(
-        self, mock_boto3_module, s3_config, tmp_path: Path
-    ) -> None:
-        """upload_file must call client.upload_file and return the object key."""
-        from src.backup.cloud_storage import CloudStorage
-
-        test_file = tmp_path / "backup.json.gz"
-        test_file.write_bytes(b"data")
-
-        storage = CloudStorage(s3_config)
-        key = storage.upload_file(test_file, object_key="backups/backup.json.gz")
-
-        assert key == "backups/backup.json.gz"
-        storage.client.upload_file.assert_called_once()
-
-    def test_upload_file_default_key(
-        self, mock_boto3_module, s3_config, tmp_path: Path
-    ) -> None:
-        """upload_file without object_key must use the filename as key."""
-        from src.backup.cloud_storage import CloudStorage
-
-        test_file = tmp_path / "myfile.gz"
-        test_file.write_bytes(b"data")
-
-        storage = CloudStorage(s3_config)
-        key = storage.upload_file(test_file)
-
-        assert key == "myfile.gz"
-
-    def test_upload_file_not_found(
-        self, mock_boto3_module, s3_config, tmp_path: Path
-    ) -> None:
-        """upload_file must raise FileNotFoundError for missing files."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        with pytest.raises(FileNotFoundError):
-            storage.upload_file(tmp_path / "nonexistent.gz")
-
-    def test_upload_file_propagates_client_error(
-        self, mock_boto3_module, s3_config, tmp_path: Path
-    ) -> None:
-        """upload_file must re-raise exceptions from the boto3 client."""
-        from src.backup.cloud_storage import CloudStorage
-
-        test_file = tmp_path / "backup.gz"
-        test_file.write_bytes(b"data")
-
-        storage = CloudStorage(s3_config)
-        storage.client.upload_file.side_effect = RuntimeError("network error")
-
-        with pytest.raises(RuntimeError, match="network error"):
-            storage.upload_file(test_file)
-
-    def test_download_file_success(
-        self, mock_boto3_module, s3_config, tmp_path: Path
-    ) -> None:
-        """download_file must call client.download_file and return local path."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        dest = tmp_path / "downloads" / "backup.gz"
-
-        result = storage.download_file("backups/backup.gz", dest)
-
-        assert result == dest
-        storage.client.download_file.assert_called_once()
-
-    def test_download_file_propagates_error(
-        self, mock_boto3_module, s3_config, tmp_path: Path
-    ) -> None:
-        """download_file must re-raise exceptions from the boto3 client."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.download_file.side_effect = RuntimeError("timeout")
-
-        with pytest.raises(RuntimeError, match="timeout"):
-            storage.download_file("key", tmp_path / "dest.gz")
-
-    def test_list_files_returns_objects(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """list_files must return parsed file metadata from S3 response."""
-        from datetime import timezone
-
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.list_objects_v2.return_value = {
-            "Contents": [
-                {
-                    "Key": "backups/a.gz",
-                    "Size": 1024,
-                    "LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
-                    "ETag": '"abc123"',
-                }
-            ]
-        }
-
-        files = storage.list_files(prefix="backups/")
-        assert len(files) == 1
-        assert files[0]["key"] == "backups/a.gz"
-        assert files[0]["size_bytes"] == 1024
-
-    def test_list_files_empty_bucket(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """list_files must return empty list when bucket has no objects."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.list_objects_v2.return_value = {}
-
-        files = storage.list_files()
-        assert files == []
-
-    def test_list_files_propagates_error(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """list_files must re-raise exceptions from the boto3 client."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.list_objects_v2.side_effect = RuntimeError("auth error")
-
-        with pytest.raises(RuntimeError):
-            storage.list_files()
-
-    def test_delete_file_success(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """delete_file must call client.delete_object with the correct key."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.delete_file("backups/old.gz")
-        storage.client.delete_object.assert_called_once_with(
-            Bucket="test-bucket", Key="backups/old.gz"
-        )
-
-    def test_delete_file_propagates_error(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """delete_file must re-raise exceptions from the boto3 client."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.delete_object.side_effect = RuntimeError("permission denied")
-
-        with pytest.raises(RuntimeError):
-            storage.delete_file("backups/old.gz")
-
-    def test_get_storage_stats_success(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """get_storage_stats must aggregate file sizes correctly."""
-        from datetime import timezone
-
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.list_objects_v2.return_value = {
-            "Contents": [
-                {
-                    "Key": "a.gz",
-                    "Size": 1024 * 1024,
-                    "LastModified": datetime(2026, 1, 1, tzinfo=timezone.utc),
-                    "ETag": '"x"',
-                },
-                {
-                    "Key": "b.gz",
-                    "Size": 1024 * 1024,
-                    "LastModified": datetime(2026, 1, 2, tzinfo=timezone.utc),
-                    "ETag": '"y"',
-                },
-            ]
-        }
-
-        stats = storage.get_storage_stats()
-        assert stats["total_files"] == 2
-        assert stats["total_size_bytes"] == 2 * 1024 * 1024
-        assert stats["total_size_mb"] == pytest.approx(2.0)
-
-    def test_get_storage_stats_on_error(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """get_storage_stats must return error dict without raising on failure."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.list_objects_v2.side_effect = RuntimeError("no connection")
-
-        stats = storage.get_storage_stats()
-        assert "error" in stats
-        assert stats["total_files"] == 0
-
-    def test_verify_connection_success(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """verify_connection must return True when head_bucket succeeds."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        result = storage.verify_connection()
-        assert result is True
-
-    def test_verify_connection_failure(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """verify_connection must return False when head_bucket raises."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.head_bucket.side_effect = RuntimeError("no such bucket")
-
-        result = storage.verify_connection()
-        assert result is False
-
-    def test_enable_versioning(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """enable_versioning must call put_bucket_versioning."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.enable_versioning()
-        storage.client.put_bucket_versioning.assert_called_once()
-
-    def test_enable_versioning_propagates_error(
-        self, mock_boto3_module, s3_config
-    ) -> None:
-        """enable_versioning must re-raise exceptions from the boto3 client."""
-        from src.backup.cloud_storage import CloudStorage
-
-        storage = CloudStorage(s3_config)
-        storage.client.put_bucket_versioning.side_effect = RuntimeError("denied")
-
-        with pytest.raises(RuntimeError):
-            storage.enable_versioning()

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

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()
@@ -296,624 +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"
-
-
-# ---------------------------------------------------------------------------
-# TR_ID live/paper branching (issues #201, #202, #203)
-# ---------------------------------------------------------------------------
-
-
-class TestTRIDBranchingDomestic:
-    """get_balance and send_order must use correct TR_ID for live vs paper mode."""
-
-    def _make_broker(self, settings, mode: str) -> KISBroker:
-        from src.config import Settings
-
-        s = Settings(
-            KIS_APP_KEY=settings.KIS_APP_KEY,
-            KIS_APP_SECRET=settings.KIS_APP_SECRET,
-            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
-            GEMINI_API_KEY=settings.GEMINI_API_KEY,
-            DB_PATH=":memory:",
-            ENABLED_MARKETS="KR",
-            MODE=mode,
-        )
-        b = KISBroker(s)
-        b._access_token = "tok"
-        b._token_expires_at = float("inf")
-        b._rate_limiter.acquire = AsyncMock()
-        return b
-
-    @pytest.mark.asyncio
-    async def test_get_balance_paper_uses_vttc8434r(self, settings) -> None:
-        broker = self._make_broker(settings, "paper")
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(
-            return_value={"output1": [], "output2": {}}
-        )
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
-            await broker.get_balance()
-
-        headers = mock_get.call_args[1].get("headers", {})
-        assert headers["tr_id"] == "VTTC8434R"
-
-    @pytest.mark.asyncio
-    async def test_get_balance_live_uses_tttc8434r(self, settings) -> None:
-        broker = self._make_broker(settings, "live")
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(
-            return_value={"output1": [], "output2": {}}
-        )
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
-            await broker.get_balance()
-
-        headers = mock_get.call_args[1].get("headers", {})
-        assert headers["tr_id"] == "TTTC8434R"
-
-    @pytest.mark.asyncio
-    async def test_send_order_buy_paper_uses_vttc0012u(self, settings) -> None:
-        broker = self._make_broker(settings, "paper")
-        mock_hash = AsyncMock()
-        mock_hash.status = 200
-        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
-        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
-        mock_hash.__aexit__ = AsyncMock(return_value=False)
-
-        mock_order = AsyncMock()
-        mock_order.status = 200
-        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
-        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
-        mock_order.__aexit__ = AsyncMock(return_value=False)
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.send_order("005930", "BUY", 1)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert order_headers["tr_id"] == "VTTC0012U"
-
-    @pytest.mark.asyncio
-    async def test_send_order_buy_live_uses_tttc0012u(self, settings) -> None:
-        broker = self._make_broker(settings, "live")
-        mock_hash = AsyncMock()
-        mock_hash.status = 200
-        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
-        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
-        mock_hash.__aexit__ = AsyncMock(return_value=False)
-
-        mock_order = AsyncMock()
-        mock_order.status = 200
-        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
-        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
-        mock_order.__aexit__ = AsyncMock(return_value=False)
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.send_order("005930", "BUY", 1)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert order_headers["tr_id"] == "TTTC0012U"
-
-    @pytest.mark.asyncio
-    async def test_send_order_sell_paper_uses_vttc0011u(self, settings) -> None:
-        broker = self._make_broker(settings, "paper")
-        mock_hash = AsyncMock()
-        mock_hash.status = 200
-        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
-        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
-        mock_hash.__aexit__ = AsyncMock(return_value=False)
-
-        mock_order = AsyncMock()
-        mock_order.status = 200
-        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
-        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
-        mock_order.__aexit__ = AsyncMock(return_value=False)
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.send_order("005930", "SELL", 1)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert order_headers["tr_id"] == "VTTC0011U"
-
-    @pytest.mark.asyncio
-    async def test_send_order_sell_live_uses_tttc0011u(self, settings) -> None:
-        broker = self._make_broker(settings, "live")
-        mock_hash = AsyncMock()
-        mock_hash.status = 200
-        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
-        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
-        mock_hash.__aexit__ = AsyncMock(return_value=False)
-
-        mock_order = AsyncMock()
-        mock_order.status = 200
-        mock_order.json = AsyncMock(return_value={"rt_cd": "0"})
-        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
-        mock_order.__aexit__ = AsyncMock(return_value=False)
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.send_order("005930", "SELL", 1)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert order_headers["tr_id"] == "TTTC0011U"
-
-
-# ---------------------------------------------------------------------------
-# Domestic Pending Orders (get_domestic_pending_orders)
-# ---------------------------------------------------------------------------
-
-
-class TestGetDomesticPendingOrders:
-    """get_domestic_pending_orders must return [] in paper mode and call TTTC0084R in live."""
-
-    def _make_broker(self, settings, mode: str) -> KISBroker:
-        from src.config import Settings
-
-        s = Settings(
-            KIS_APP_KEY=settings.KIS_APP_KEY,
-            KIS_APP_SECRET=settings.KIS_APP_SECRET,
-            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
-            GEMINI_API_KEY=settings.GEMINI_API_KEY,
-            DB_PATH=":memory:",
-            ENABLED_MARKETS="KR",
-            MODE=mode,
-        )
-        b = KISBroker(s)
-        b._access_token = "tok"
-        b._token_expires_at = float("inf")
-        b._rate_limiter.acquire = AsyncMock()
-        return b
-
-    @pytest.mark.asyncio
-    async def test_paper_mode_returns_empty(self, settings) -> None:
-        """Paper mode must return [] immediately without any API call."""
-        broker = self._make_broker(settings, "paper")
-
-        with patch("aiohttp.ClientSession.get") as mock_get:
-            result = await broker.get_domestic_pending_orders()
-
-        assert result == []
-        mock_get.assert_not_called()
-
-    @pytest.mark.asyncio
-    async def test_live_mode_calls_tttc0084r_with_correct_params(
-        self, settings
-    ) -> None:
-        """Live mode must call TTTC0084R with INQR_DVSN_1/2 and paging params."""
-        broker = self._make_broker(settings, "live")
-        pending = [{"odno": "001", "pdno": "005930", "psbl_qty": "10"}]
-        mock_resp = AsyncMock()
-        mock_resp.status = 200
-        mock_resp.json = AsyncMock(return_value={"output": pending})
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        with patch("aiohttp.ClientSession.get", return_value=mock_resp) as mock_get:
-            result = await broker.get_domestic_pending_orders()
-
-        assert result == pending
-        headers = mock_get.call_args[1].get("headers", {})
-        assert headers["tr_id"] == "TTTC0084R"
-        params = mock_get.call_args[1].get("params", {})
-        assert params["INQR_DVSN_1"] == "0"
-        assert params["INQR_DVSN_2"] == "0"
-
-    @pytest.mark.asyncio
-    async def test_live_mode_connection_error(self, settings) -> None:
-        """Network error must raise ConnectionError."""
-        import aiohttp as _aiohttp
-
-        broker = self._make_broker(settings, "live")
-
-        with patch(
-            "aiohttp.ClientSession.get",
-            side_effect=_aiohttp.ClientError("timeout"),
-        ):
-            with pytest.raises(ConnectionError):
-                await broker.get_domestic_pending_orders()
-
-
-# ---------------------------------------------------------------------------
-# Domestic Order Cancellation (cancel_domestic_order)
-# ---------------------------------------------------------------------------
-
-
-class TestCancelDomesticOrder:
-    """cancel_domestic_order must use correct TR_ID and build body correctly."""
-
-    def _make_broker(self, settings, mode: str) -> KISBroker:
-        from src.config import Settings
-
-        s = Settings(
-            KIS_APP_KEY=settings.KIS_APP_KEY,
-            KIS_APP_SECRET=settings.KIS_APP_SECRET,
-            KIS_ACCOUNT_NO=settings.KIS_ACCOUNT_NO,
-            GEMINI_API_KEY=settings.GEMINI_API_KEY,
-            DB_PATH=":memory:",
-            ENABLED_MARKETS="KR",
-            MODE=mode,
-        )
-        b = KISBroker(s)
-        b._access_token = "tok"
-        b._token_expires_at = float("inf")
-        b._rate_limiter.acquire = AsyncMock()
-        return b
-
-    def _make_post_mocks(self, order_payload: dict) -> tuple:
-        mock_hash = AsyncMock()
-        mock_hash.status = 200
-        mock_hash.json = AsyncMock(return_value={"HASH": "h"})
-        mock_hash.__aenter__ = AsyncMock(return_value=mock_hash)
-        mock_hash.__aexit__ = AsyncMock(return_value=False)
-
-        mock_order = AsyncMock()
-        mock_order.status = 200
-        mock_order.json = AsyncMock(return_value=order_payload)
-        mock_order.__aenter__ = AsyncMock(return_value=mock_order)
-        mock_order.__aexit__ = AsyncMock(return_value=False)
-
-        return mock_hash, mock_order
-
-    @pytest.mark.asyncio
-    async def test_live_uses_tttc0013u(self, settings) -> None:
-        """Live mode must use TR_ID TTTC0013U."""
-        broker = self._make_broker(settings, "live")
-        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 5)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert order_headers["tr_id"] == "TTTC0013U"
-
-    @pytest.mark.asyncio
-    async def test_paper_uses_vttc0013u(self, settings) -> None:
-        """Paper mode must use TR_ID VTTC0013U."""
-        broker = self._make_broker(settings, "paper")
-        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 5)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert order_headers["tr_id"] == "VTTC0013U"
-
-    @pytest.mark.asyncio
-    async def test_cancel_sets_rvse_cncl_dvsn_cd_02(self, settings) -> None:
-        """Body must have RVSE_CNCL_DVSN_CD='02' (취소) and QTY_ALL_ORD_YN='Y'."""
-        broker = self._make_broker(settings, "live")
-        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 5)
-
-        body = mock_post.call_args_list[1][1].get("json", {})
-        assert body["RVSE_CNCL_DVSN_CD"] == "02"
-        assert body["QTY_ALL_ORD_YN"] == "Y"
-        assert body["ORD_UNPR"] == "0"
-
-    @pytest.mark.asyncio
-    async def test_cancel_sets_krx_fwdg_ord_orgno_in_body(self, settings) -> None:
-        """Body must include KRX_FWDG_ORD_ORGNO and ORGN_ODNO from arguments."""
-        broker = self._make_broker(settings, "live")
-        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.cancel_domestic_order("005930", "ORD123", "BRN456", 3)
-
-        body = mock_post.call_args_list[1][1].get("json", {})
-        assert body["KRX_FWDG_ORD_ORGNO"] == "BRN456"
-        assert body["ORGN_ODNO"] == "ORD123"
-        assert body["ORD_QTY"] == "3"
-
-    @pytest.mark.asyncio
-    async def test_cancel_sets_hashkey_header(self, settings) -> None:
-        """Request must include hashkey header (same pattern as send_order)."""
-        broker = self._make_broker(settings, "live")
-        mock_hash, mock_order = self._make_post_mocks({"rt_cd": "0"})
-
-        with patch(
-            "aiohttp.ClientSession.post", side_effect=[mock_hash, mock_order]
-        ) as mock_post:
-            await broker.cancel_domestic_order("005930", "ORD001", "BRNO01", 2)
-
-        order_headers = mock_post.call_args_list[1][1].get("headers", {})
-        assert "hashkey" in order_headers
-        assert order_headers["hashkey"] == "h"

tests/test_context.py

@@ -10,7 +10,6 @@ import pytest
 from src.context.aggregator import ContextAggregator
 from src.context.layer import LAYER_CONFIG, ContextLayer
 from src.context.store import ContextStore
-from src.context.summarizer import ContextSummarizer
 from src.db import init_db, log_trade
 
 
@@ -371,259 +370,3 @@ class TestLayerMetadata:
 
         # L1 aggregates from L2
         assert LAYER_CONFIG[ContextLayer.L1_LEGACY].aggregation_source == ContextLayer.L2_ANNUAL
-
-
-# ---------------------------------------------------------------------------
-# ContextSummarizer tests
-# ---------------------------------------------------------------------------
-
-
-@pytest.fixture
-def summarizer(db_conn: sqlite3.Connection) -> ContextSummarizer:
-    """Provide a ContextSummarizer backed by an in-memory store."""
-    return ContextSummarizer(ContextStore(db_conn))
-
-
-class TestContextSummarizer:
-    """Test suite for ContextSummarizer."""
-
-    # ------------------------------------------------------------------
-    # summarize_numeric_values
-    # ------------------------------------------------------------------
-
-    def test_summarize_empty_values(self, summarizer: ContextSummarizer) -> None:
-        """Empty list must return SummaryStats with count=0 and no other fields."""
-        stats = summarizer.summarize_numeric_values([])
-        assert stats.count == 0
-        assert stats.mean is None
-        assert stats.min is None
-        assert stats.max is None
-
-    def test_summarize_single_value(self, summarizer: ContextSummarizer) -> None:
-        """Single-element list must return correct stats with std=0 and trend=flat."""
-        stats = summarizer.summarize_numeric_values([42.0])
-        assert stats.count == 1
-        assert stats.mean == 42.0
-        assert stats.std == 0.0
-        assert stats.trend == "flat"
-
-    def test_summarize_upward_trend(self, summarizer: ContextSummarizer) -> None:
-        """Increasing values must produce trend='up'."""
-        values = [1.0, 2.0, 3.0, 10.0, 20.0, 30.0]
-        stats = summarizer.summarize_numeric_values(values)
-        assert stats.trend == "up"
-
-    def test_summarize_downward_trend(self, summarizer: ContextSummarizer) -> None:
-        """Decreasing values must produce trend='down'."""
-        values = [30.0, 20.0, 10.0, 3.0, 2.0, 1.0]
-        stats = summarizer.summarize_numeric_values(values)
-        assert stats.trend == "down"
-
-    def test_summarize_flat_trend(self, summarizer: ContextSummarizer) -> None:
-        """Stable values must produce trend='flat'."""
-        values = [100.0, 100.1, 99.9, 100.0, 100.2, 99.8]
-        stats = summarizer.summarize_numeric_values(values)
-        assert stats.trend == "flat"
-
-    # ------------------------------------------------------------------
-    # summarize_layer
-    # ------------------------------------------------------------------
-
-    def test_summarize_layer_no_data(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """summarize_layer with no data must return the 'No data' sentinel."""
-        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
-        assert result["count"] == 0
-        assert "No data" in result["summary"]
-
-    def test_summarize_layer_numeric(
-        self, summarizer: ContextSummarizer, db_conn: sqlite3.Connection
-    ) -> None:
-        """summarize_layer must collect numeric values and produce stats."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "total_pnl", 100.0)
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "total_pnl", 200.0)
-
-        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
-        assert "total_entries" in result
-
-    def test_summarize_layer_with_dict_values(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """summarize_layer must handle dict values by extracting numeric subkeys."""
-        store = summarizer.store
-        # set_context serialises the value as JSON, so passing a dict works
-        store.set_context(
-            ContextLayer.L6_DAILY, "2026-02-01", "metrics",
-            {"win_rate": 65.0, "label": "good"}
-        )
-
-        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
-        assert "total_entries" in result
-        # numeric subkey "win_rate" should appear as "metrics.win_rate"
-        assert "metrics.win_rate" in result
-
-    def test_summarize_layer_with_string_values(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """summarize_layer must count string values separately."""
-        store = summarizer.store
-        # set_context stores string values as JSON-encoded strings
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "outlook", "BULLISH")
-
-        result = summarizer.summarize_layer(ContextLayer.L6_DAILY)
-        # String fields contribute a `<key>_count` entry
-        assert "outlook_count" in result
-
-    # ------------------------------------------------------------------
-    # rolling_window_summary
-    # ------------------------------------------------------------------
-
-    def test_rolling_window_summary_basic(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """rolling_window_summary must return the expected structure."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 500.0)
-
-        result = summarizer.rolling_window_summary(ContextLayer.L6_DAILY)
-        assert "window_days" in result
-        assert "recent_data" in result
-        assert "historical_summary" in result
-
-    def test_rolling_window_summary_no_older_data(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """rolling_window_summary with summarize_older=False skips history."""
-        result = summarizer.rolling_window_summary(
-            ContextLayer.L6_DAILY, summarize_older=False
-        )
-        assert result["historical_summary"] == {}
-
-    # ------------------------------------------------------------------
-    # aggregate_to_higher_layer
-    # ------------------------------------------------------------------
-
-    def test_aggregate_to_higher_layer_mean(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """aggregate_to_higher_layer with 'mean' via dict subkeys returns average."""
-        store = summarizer.store
-        # Use different outer keys but same inner metric key so get_all_contexts
-        # returns multiple rows with the target subkey.
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
-
-        result = summarizer.aggregate_to_higher_layer(
-            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "mean"
-        )
-        assert result == pytest.approx(150.0)
-
-    def test_aggregate_to_higher_layer_sum(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """aggregate_to_higher_layer with 'sum' must return the total."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
-
-        result = summarizer.aggregate_to_higher_layer(
-            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "sum"
-        )
-        assert result == pytest.approx(300.0)
-
-    def test_aggregate_to_higher_layer_max(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """aggregate_to_higher_layer with 'max' must return the maximum."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
-
-        result = summarizer.aggregate_to_higher_layer(
-            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "max"
-        )
-        assert result == pytest.approx(200.0)
-
-    def test_aggregate_to_higher_layer_min(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """aggregate_to_higher_layer with 'min' must return the minimum."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
-
-        result = summarizer.aggregate_to_higher_layer(
-            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "min"
-        )
-        assert result == pytest.approx(100.0)
-
-    def test_aggregate_to_higher_layer_no_data(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """aggregate_to_higher_layer with no matching key must return None."""
-        result = summarizer.aggregate_to_higher_layer(
-            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "nonexistent", "mean"
-        )
-        assert result is None
-
-    def test_aggregate_to_higher_layer_unknown_func_defaults_to_mean(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """Unknown aggregation function must fall back to mean."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day1", {"pnl": 100.0})
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "day2", {"pnl": 200.0})
-
-        result = summarizer.aggregate_to_higher_layer(
-            ContextLayer.L6_DAILY, ContextLayer.L5_WEEKLY, "pnl", "unknown_func"
-        )
-        assert result == pytest.approx(150.0)
-
-    # ------------------------------------------------------------------
-    # create_compact_summary + format_summary_for_prompt
-    # ------------------------------------------------------------------
-
-    def test_create_compact_summary(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """create_compact_summary must produce a dict keyed by layer value."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
-
-        result = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
-        assert ContextLayer.L6_DAILY.value in result
-
-    def test_format_summary_for_prompt_with_numeric_metrics(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """format_summary_for_prompt must render avg/trend fields."""
-        store = summarizer.store
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-01", "pnl", 100.0)
-        store.set_context(ContextLayer.L6_DAILY, "2026-02-02", "pnl", 200.0)
-
-        compact = summarizer.create_compact_summary([ContextLayer.L6_DAILY])
-        text = summarizer.format_summary_for_prompt(compact)
-        assert isinstance(text, str)
-
-    def test_format_summary_for_prompt_skips_empty_layers(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """format_summary_for_prompt must skip layers with no metrics."""
-        summary = {ContextLayer.L6_DAILY.value: {}}
-        text = summarizer.format_summary_for_prompt(summary)
-        assert text == ""
-
-    def test_format_summary_non_dict_value(
-        self, summarizer: ContextSummarizer
-    ) -> None:
-        """format_summary_for_prompt must render non-dict values as plain text."""
-        summary = {
-            "daily": {
-                "plain_count": 42,
-            }
-        }
-        text = summarizer.format_summary_for_prompt(summary)
-        assert "plain_count" in text
-        assert "42" in text

tests/test_dashboard.py

@@ -296,147 +296,3 @@ def test_scenarios_active_empty_when_no_matches(tmp_path: Path) -> None:
     get_active_scenarios = _endpoint(app, "/api/scenarios/active")
     body = get_active_scenarios(market="US", date_str="2026-02-14", limit=50)
     assert body["count"] == 0
-
-
-def test_pnl_history_all_markets(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_pnl_history = _endpoint(app, "/api/pnl/history")
-    body = get_pnl_history(days=30, market="all")
-    assert body["market"] == "all"
-    assert isinstance(body["labels"], list)
-    assert isinstance(body["pnl"], list)
-    assert len(body["labels"]) == len(body["pnl"])
-
-
-def test_pnl_history_market_filter(tmp_path: Path) -> None:
-    app = _app(tmp_path)
-    get_pnl_history = _endpoint(app, "/api/pnl/history")
-    body = get_pnl_history(days=30, market="KR")
-    assert body["market"] == "KR"
-    # KR has 1 trade with pnl=2.0
-    assert len(body["labels"]) >= 1
-    assert body["pnl"][0] == 2.0
-
-
-def test_positions_returns_open_buy(tmp_path: Path) -> None:
-    """BUY가 마지막 거래인 종목은 포지션으로 반환되어야 한다."""
-    app = _app(tmp_path)
-    get_positions = _endpoint(app, "/api/positions")
-    body = get_positions()
-    # seed_db: 005930은 BUY (오픈), AAPL은 SELL (마지막)
-    assert body["count"] == 1
-    pos = body["positions"][0]
-    assert pos["stock_code"] == "005930"
-    assert pos["market"] == "KR"
-    assert pos["quantity"] == 1
-    assert pos["entry_price"] == 70000
-
-
-def test_positions_excludes_closed_sell(tmp_path: Path) -> None:
-    """마지막 거래가 SELL인 종목은 포지션에 나타나지 않아야 한다."""
-    app = _app(tmp_path)
-    get_positions = _endpoint(app, "/api/positions")
-    body = get_positions()
-    codes = [p["stock_code"] for p in body["positions"]]
-    assert "AAPL" not in codes
-
-
-def test_positions_empty_when_no_trades(tmp_path: Path) -> None:
-    """거래 내역이 없으면 빈 포지션 목록을 반환해야 한다."""
-    db_path = tmp_path / "empty.db"
-    conn = init_db(str(db_path))
-    conn.close()
-    app = create_dashboard_app(str(db_path))
-    get_positions = _endpoint(app, "/api/positions")
-    body = get_positions()
-    assert body["count"] == 0
-    assert body["positions"] == []
-
-
-def _seed_cb_context(conn: sqlite3.Connection, pnl_pct: float, market: str = "KR") -> None:
-    import json as _json
-    conn.execute(
-        "INSERT OR REPLACE INTO system_metrics (key, value, updated_at) VALUES (?, ?, ?)",
-        (
-            f"portfolio_pnl_pct_{market}",
-            _json.dumps({"pnl_pct": pnl_pct}),
-            "2026-02-22T10:00:00+00:00",
-        ),
-    )
-    conn.commit()
-
-
-def test_status_circuit_breaker_ok(tmp_path: Path) -> None:
-    """pnl_pct가 -2.0%보다 높으면 status=ok를 반환해야 한다."""
-    db_path = tmp_path / "cb_ok.db"
-    conn = init_db(str(db_path))
-    _seed_cb_context(conn, -1.0)
-    conn.close()
-    app = create_dashboard_app(str(db_path))
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    cb = body["circuit_breaker"]
-    assert cb["status"] == "ok"
-    assert cb["current_pnl_pct"] == -1.0
-    assert cb["threshold_pct"] == -3.0
-
-
-def test_status_circuit_breaker_warning(tmp_path: Path) -> None:
-    """pnl_pct가 -2.0% 이하이면 status=warning을 반환해야 한다."""
-    db_path = tmp_path / "cb_warn.db"
-    conn = init_db(str(db_path))
-    _seed_cb_context(conn, -2.5)
-    conn.close()
-    app = create_dashboard_app(str(db_path))
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    assert body["circuit_breaker"]["status"] == "warning"
-
-
-def test_status_circuit_breaker_tripped(tmp_path: Path) -> None:
-    """pnl_pct가 임계값(-3.0%) 이하이면 status=tripped를 반환해야 한다."""
-    db_path = tmp_path / "cb_tripped.db"
-    conn = init_db(str(db_path))
-    _seed_cb_context(conn, -3.5)
-    conn.close()
-    app = create_dashboard_app(str(db_path))
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    assert body["circuit_breaker"]["status"] == "tripped"
-
-
-def test_status_circuit_breaker_unknown_when_no_data(tmp_path: Path) -> None:
-    """L7 context에 pnl_pct 데이터가 없으면 status=unknown을 반환해야 한다."""
-    app = _app(tmp_path)  # seed_db에는 portfolio_pnl_pct 없음
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    cb = body["circuit_breaker"]
-    assert cb["status"] == "unknown"
-    assert cb["current_pnl_pct"] is None
-
-
-def test_status_mode_paper(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
-    """MODE=paper일 때 status 응답에 mode=paper가 포함돼야 한다."""
-    monkeypatch.setenv("MODE", "paper")
-    app = _app(tmp_path)
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    assert body["mode"] == "paper"
-
-
-def test_status_mode_live(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
-    """MODE=live일 때 status 응답에 mode=live가 포함돼야 한다."""
-    monkeypatch.setenv("MODE", "live")
-    app = _app(tmp_path)
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    assert body["mode"] == "live"
-
-
-def test_status_mode_default_paper(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
-    """MODE 환경변수가 없으면 mode 기본값은 paper여야 한다."""
-    monkeypatch.delenv("MODE", raising=False)
-    app = _app(tmp_path)
-    get_status = _endpoint(app, "/api/status")
-    body = get_status()
-    assert body["mode"] == "paper"

tests/test_db.py

@@ -1,8 +1,5 @@
 """Tests for database helper functions."""
 
-import tempfile
-import os
-
 from src.db import get_open_position, init_db, log_trade
 
 
@@ -61,135 +58,3 @@ def test_get_open_position_returns_none_when_latest_is_sell() -> None:
 def test_get_open_position_returns_none_when_no_trades() -> None:
     conn = init_db(":memory:")
     assert get_open_position(conn, "AAPL", "US_NASDAQ") is None
-
-
-# ---------------------------------------------------------------------------
-# WAL mode tests (issue #210)
-# ---------------------------------------------------------------------------
-
-
-def test_wal_mode_applied_to_file_db() -> None:
-    """File-based DB must use WAL journal mode for dashboard concurrent reads."""
-    with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
-        db_path = f.name
-    try:
-        conn = init_db(db_path)
-        cursor = conn.execute("PRAGMA journal_mode")
-        mode = cursor.fetchone()[0]
-        assert mode == "wal", f"Expected WAL mode, got {mode}"
-        conn.close()
-    finally:
-        os.unlink(db_path)
-        # Clean up WAL auxiliary files if they exist
-        for ext in ("-wal", "-shm"):
-            path = db_path + ext
-            if os.path.exists(path):
-                os.unlink(path)
-
-
-def test_wal_mode_not_applied_to_memory_db() -> None:
-    """:memory: DB must not apply WAL (SQLite does not support WAL for in-memory)."""
-    conn = init_db(":memory:")
-    cursor = conn.execute("PRAGMA journal_mode")
-    mode = cursor.fetchone()[0]
-    # In-memory DBs default to 'memory' journal mode
-    assert mode != "wal", "WAL should not be set on in-memory database"
-    conn.close()
-
-
-# ---------------------------------------------------------------------------
-# mode column tests (issue #212)
-# ---------------------------------------------------------------------------
-
-
-def test_log_trade_stores_mode_paper() -> None:
-    """log_trade must persist mode='paper' in the trades table."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=85,
-        rationale="test",
-        mode="paper",
-    )
-    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
-    assert row is not None
-    assert row[0] == "paper"
-
-
-def test_log_trade_stores_mode_live() -> None:
-    """log_trade must persist mode='live' in the trades table."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn,
-        stock_code="005930",
-        action="BUY",
-        confidence=85,
-        rationale="test",
-        mode="live",
-    )
-    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
-    assert row is not None
-    assert row[0] == "live"
-
-
-def test_log_trade_default_mode_is_paper() -> None:
-    """log_trade without explicit mode must default to 'paper'."""
-    conn = init_db(":memory:")
-    log_trade(
-        conn=conn,
-        stock_code="005930",
-        action="HOLD",
-        confidence=50,
-        rationale="test",
-    )
-    row = conn.execute("SELECT mode FROM trades ORDER BY id DESC LIMIT 1").fetchone()
-    assert row is not None
-    assert row[0] == "paper"
-
-
-def test_mode_column_exists_in_schema() -> None:
-    """trades table must have a mode column after init_db."""
-    conn = init_db(":memory:")
-    cursor = conn.execute("PRAGMA table_info(trades)")
-    columns = {row[1] for row in cursor.fetchall()}
-    assert "mode" in columns
-
-
-def test_mode_migration_adds_column_to_existing_db() -> None:
-    """init_db must add mode column to existing DBs that lack it (migration)."""
-    import sqlite3
-
-    with tempfile.NamedTemporaryFile(suffix=".db", delete=False) as f:
-        db_path = f.name
-    try:
-        # Create DB without mode column (simulate old schema)
-        old_conn = sqlite3.connect(db_path)
-        old_conn.execute(
-            """CREATE TABLE trades (
-                id INTEGER PRIMARY KEY AUTOINCREMENT,
-                timestamp TEXT NOT NULL,
-                stock_code TEXT NOT NULL,
-                action TEXT NOT NULL,
-                confidence INTEGER NOT NULL,
-                rationale TEXT,
-                quantity INTEGER,
-                price REAL,
-                pnl REAL DEFAULT 0.0,
-                market TEXT DEFAULT 'KR',
-                exchange_code TEXT DEFAULT 'KRX',
-                decision_id TEXT
-            )"""
-        )
-        old_conn.commit()
-        old_conn.close()
-
-        # Run init_db — should add mode column via migration
-        conn = init_db(db_path)
-        cursor = conn.execute("PRAGMA table_info(trades)")
-        columns = {row[1] for row in cursor.fetchall()}
-        assert "mode" in columns
-        conn.close()
-    finally:
-        os.unlink(db_path)

tests/test_logging_config.py

@@ -1,117 +0,0 @@
-"""Tests for JSON structured logging configuration."""
-
-from __future__ import annotations
-
-import json
-import logging
-import sys
-
-from src.logging_config import JSONFormatter, setup_logging
-
-
-class TestJSONFormatter:
-    """Test JSONFormatter output."""
-
-    def test_basic_log_record(self) -> None:
-        """JSONFormatter must emit valid JSON with required fields."""
-        formatter = JSONFormatter()
-        record = logging.LogRecord(
-            name="test.logger",
-            level=logging.INFO,
-            pathname="",
-            lineno=0,
-            msg="Hello %s",
-            args=("world",),
-            exc_info=None,
-        )
-        output = formatter.format(record)
-        data = json.loads(output)
-        assert data["level"] == "INFO"
-        assert data["logger"] == "test.logger"
-        assert data["message"] == "Hello world"
-        assert "timestamp" in data
-
-    def test_includes_exception_info(self) -> None:
-        """JSONFormatter must include exception info when present."""
-        formatter = JSONFormatter()
-        try:
-            raise ValueError("test error")
-        except ValueError:
-            exc_info = sys.exc_info()
-        record = logging.LogRecord(
-            name="test",
-            level=logging.ERROR,
-            pathname="",
-            lineno=0,
-            msg="oops",
-            args=(),
-            exc_info=exc_info,
-        )
-        output = formatter.format(record)
-        data = json.loads(output)
-        assert "exception" in data
-        assert "ValueError" in data["exception"]
-
-    def test_extra_trading_fields_included(self) -> None:
-        """Extra trading fields attached to the record must appear in JSON."""
-        formatter = JSONFormatter()
-        record = logging.LogRecord(
-            name="test",
-            level=logging.INFO,
-            pathname="",
-            lineno=0,
-            msg="trade",
-            args=(),
-            exc_info=None,
-        )
-        record.stock_code = "005930"  # type: ignore[attr-defined]
-        record.action = "BUY"  # type: ignore[attr-defined]
-        record.confidence = 85  # type: ignore[attr-defined]
-        record.pnl_pct = -1.5  # type: ignore[attr-defined]
-        record.order_amount = 1_000_000  # type: ignore[attr-defined]
-        output = formatter.format(record)
-        data = json.loads(output)
-        assert data["stock_code"] == "005930"
-        assert data["action"] == "BUY"
-        assert data["confidence"] == 85
-        assert data["pnl_pct"] == -1.5
-        assert data["order_amount"] == 1_000_000
-
-    def test_none_extra_fields_excluded(self) -> None:
-        """Extra fields that are None must not appear in JSON output."""
-        formatter = JSONFormatter()
-        record = logging.LogRecord(
-            name="test",
-            level=logging.INFO,
-            pathname="",
-            lineno=0,
-            msg="no extras",
-            args=(),
-            exc_info=None,
-        )
-        output = formatter.format(record)
-        data = json.loads(output)
-        assert "stock_code" not in data
-        assert "action" not in data
-        assert "confidence" not in data
-
-
-class TestSetupLogging:
-    """Test setup_logging function."""
-
-    def test_configures_root_logger(self) -> None:
-        """setup_logging must attach a JSON handler to the root logger."""
-        setup_logging(level=logging.DEBUG)
-        root = logging.getLogger()
-        json_handlers = [
-            h for h in root.handlers if isinstance(h.formatter, JSONFormatter)
-        ]
-        assert len(json_handlers) == 1
-        assert root.level == logging.DEBUG
-
-    def test_avoids_duplicate_handlers(self) -> None:
-        """Calling setup_logging twice must not add duplicate handlers."""
-        setup_logging()
-        setup_logging()
-        root = logging.getLogger()
-        assert len(root.handlers) == 1

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:
@@ -662,339 +657,3 @@ class TestDefensivePlaybook:
         assert pb.stock_count == 0
         assert pb.market == "US"
         assert pb.market_outlook == MarketOutlook.NEUTRAL
-
-
-# ---------------------------------------------------------------------------
-# Smart fallback playbook
-# ---------------------------------------------------------------------------
-
-
-class TestSmartFallbackPlaybook:
-    """Tests for _smart_fallback_playbook — rule-based BUY/SELL on Gemini failure."""
-
-    def _make_settings(self) -> Settings:
-        return Settings(
-            KIS_APP_KEY="test",
-            KIS_APP_SECRET="test",
-            KIS_ACCOUNT_NO="12345678-01",
-            GEMINI_API_KEY="test",
-            RSI_OVERSOLD_THRESHOLD=30,
-            VOL_MULTIPLIER=2.0,
-        )
-
-    def test_momentum_candidate_gets_buy_on_volume(self) -> None:
-        candidates = [
-            _candidate(code="CHOW", signal="momentum", volume_ratio=13.64, rsi=100.0)
-        ]
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_AMEX", candidates, settings
-        )
-
-        assert pb.stock_count == 1
-        sp = pb.stock_playbooks[0]
-        assert sp.stock_code == "CHOW"
-        # First scenario: BUY with volume_ratio_above
-        buy_sc = sp.scenarios[0]
-        assert buy_sc.action == ScenarioAction.BUY
-        assert buy_sc.condition.volume_ratio_above == 2.0
-        assert buy_sc.condition.rsi_below is None
-        assert buy_sc.confidence == 80
-        # Second scenario: stop-loss SELL
-        sell_sc = sp.scenarios[1]
-        assert sell_sc.action == ScenarioAction.SELL
-        assert sell_sc.condition.price_change_pct_below == -3.0
-
-    def test_oversold_candidate_gets_buy_on_rsi(self) -> None:
-        candidates = [
-            _candidate(code="005930", signal="oversold", rsi=22.0, volume_ratio=3.5)
-        ]
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "KR", candidates, settings
-        )
-
-        sp = pb.stock_playbooks[0]
-        buy_sc = sp.scenarios[0]
-        assert buy_sc.action == ScenarioAction.BUY
-        assert buy_sc.condition.rsi_below == 30
-        assert buy_sc.condition.volume_ratio_above is None
-
-    def test_all_candidates_have_stop_loss_sell(self) -> None:
-        candidates = [
-            _candidate(code="AAA", signal="momentum", volume_ratio=5.0),
-            _candidate(code="BBB", signal="oversold", rsi=25.0),
-        ]
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_NASDAQ", candidates, settings
-        )
-
-        assert pb.stock_count == 2
-        for sp in pb.stock_playbooks:
-            sell_scenarios = [s for s in sp.scenarios if s.action == ScenarioAction.SELL]
-            assert len(sell_scenarios) == 1
-            assert sell_scenarios[0].condition.price_change_pct_below == -3.0
-            assert sell_scenarios[0].condition.price_change_pct_below == -3.0
-
-    def test_market_outlook_is_neutral(self) -> None:
-        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_AMEX", candidates, settings
-        )
-
-        assert pb.market_outlook == MarketOutlook.NEUTRAL
-
-    def test_default_action_is_hold(self) -> None:
-        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_AMEX", candidates, settings
-        )
-
-        assert pb.default_action == ScenarioAction.HOLD
-
-    def test_has_global_reduce_all_rule(self) -> None:
-        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_AMEX", candidates, settings
-        )
-
-        assert len(pb.global_rules) == 1
-        rule = pb.global_rules[0]
-        assert rule.action == ScenarioAction.REDUCE_ALL
-        assert "portfolio_pnl_pct" in rule.condition
-
-    def test_empty_candidates_returns_empty_playbook(self) -> None:
-        settings = self._make_settings()
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_AMEX", [], settings
-        )
-
-        assert pb.stock_count == 0
-
-    def test_vol_multiplier_applied_from_settings(self) -> None:
-        """VOL_MULTIPLIER=3.0 should set volume_ratio_above=3.0 for momentum."""
-        candidates = [_candidate(signal="momentum", volume_ratio=5.0)]
-        settings = self._make_settings()
-        settings = settings.model_copy(update={"VOL_MULTIPLIER": 3.0})
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "US_AMEX", candidates, settings
-        )
-
-        buy_sc = pb.stock_playbooks[0].scenarios[0]
-        assert buy_sc.condition.volume_ratio_above == 3.0
-
-    def test_rsi_oversold_threshold_applied_from_settings(self) -> None:
-        """RSI_OVERSOLD_THRESHOLD=25 should set rsi_below=25 for oversold."""
-        candidates = [_candidate(signal="oversold", rsi=22.0)]
-        settings = self._make_settings()
-        settings = settings.model_copy(update={"RSI_OVERSOLD_THRESHOLD": 25})
-
-        pb = PreMarketPlanner._smart_fallback_playbook(
-            date(2026, 2, 17), "KR", candidates, settings
-        )
-
-        buy_sc = pb.stock_playbooks[0].scenarios[0]
-        assert buy_sc.condition.rsi_below == 25
-
-    @pytest.mark.asyncio
-    async def test_generate_playbook_uses_smart_fallback_on_gemini_error(self) -> None:
-        """generate_playbook() should use smart fallback (not defensive) on API failure."""
-        planner = _make_planner()
-        planner._gemini.decide = AsyncMock(side_effect=ConnectionError("429 quota exceeded"))
-        # momentum candidate
-        candidates = [
-            _candidate(code="CHOW", signal="momentum", volume_ratio=13.64, rsi=100.0)
-        ]
-
-        pb = await planner.generate_playbook(
-            "US_AMEX", candidates, today=date(2026, 2, 18)
-        )
-
-        # Should NOT be all-SELL defensive; should have BUY for momentum
-        assert pb.stock_count == 1
-        buy_scenarios = [
-            s for s in pb.stock_playbooks[0].scenarios
-            if s.action == ScenarioAction.BUY
-        ]
-        assert len(buy_scenarios) == 1
-        assert buy_scenarios[0].condition.volume_ratio_above == 2.0  # VOL_MULTIPLIER default
-
-
-# ---------------------------------------------------------------------------
-# Holdings in prompt (#170)
-# ---------------------------------------------------------------------------
-
-
-class TestHoldingsInPrompt:
-    """Tests for current_holdings parameter in generate_playbook / _build_prompt."""
-
-    def _make_holdings(self) -> list[dict]:
-        return [
-            {
-                "stock_code": "005930",
-                "name": "Samsung",
-                "qty": 10,
-                "entry_price": 71000.0,
-                "unrealized_pnl_pct": 2.3,
-                "holding_days": 3,
-            }
-        ]
-
-    def test_build_prompt_includes_holdings_section(self) -> None:
-        """Prompt should contain a Current Holdings section when holdings are given."""
-        planner = _make_planner()
-        candidates = [_candidate()]
-        holdings = self._make_holdings()
-
-        prompt = planner._build_prompt(
-            "KR",
-            candidates,
-            context_data={},
-            self_market_scorecard=None,
-            cross_market=None,
-            current_holdings=holdings,
-        )
-
-        assert "## Current Holdings" in prompt
-        assert "005930" in prompt
-        assert "+2.30%" in prompt
-        assert "보유 3일" in prompt
-
-    def test_build_prompt_no_holdings_omits_section(self) -> None:
-        """Prompt should NOT contain a Current Holdings section when holdings=None."""
-        planner = _make_planner()
-        candidates = [_candidate()]
-
-        prompt = planner._build_prompt(
-            "KR",
-            candidates,
-            context_data={},
-            self_market_scorecard=None,
-            cross_market=None,
-            current_holdings=None,
-        )
-
-        assert "## Current Holdings" not in prompt
-
-    def test_build_prompt_empty_holdings_omits_section(self) -> None:
-        """Empty list should also omit the holdings section."""
-        planner = _make_planner()
-        candidates = [_candidate()]
-
-        prompt = planner._build_prompt(
-            "KR",
-            candidates,
-            context_data={},
-            self_market_scorecard=None,
-            cross_market=None,
-            current_holdings=[],
-        )
-
-        assert "## Current Holdings" not in prompt
-
-    def test_build_prompt_holdings_instruction_included(self) -> None:
-        """Prompt should include instruction to generate scenarios for held stocks."""
-        planner = _make_planner()
-        candidates = [_candidate()]
-        holdings = self._make_holdings()
-
-        prompt = planner._build_prompt(
-            "KR",
-            candidates,
-            context_data={},
-            self_market_scorecard=None,
-            cross_market=None,
-            current_holdings=holdings,
-        )
-
-        assert "005930" in prompt
-        assert "SELL/HOLD" in prompt
-
-    @pytest.mark.asyncio
-    async def test_generate_playbook_passes_holdings_to_prompt(self) -> None:
-        """generate_playbook should pass current_holdings through to the prompt."""
-        planner = _make_planner()
-        candidates = [_candidate()]
-        holdings = self._make_holdings()
-
-        # Capture the actual prompt sent to Gemini
-        captured_prompts: list[str] = []
-        original_decide = planner._gemini.decide
-
-        async def capture_and_call(data: dict) -> TradeDecision:
-            captured_prompts.append(data.get("prompt_override", ""))
-            return await original_decide(data)
-
-        planner._gemini.decide = capture_and_call  # type: ignore[method-assign]
-
-        await planner.generate_playbook(
-            "KR", candidates, today=date(2026, 2, 8), current_holdings=holdings
-        )
-
-        assert len(captured_prompts) == 1
-        assert "## Current Holdings" in captured_prompts[0]
-        assert "005930" in captured_prompts[0]
-
-    @pytest.mark.asyncio
-    async def test_holdings_stock_allowed_in_parse_response(self) -> None:
-        """Holdings stocks not in candidates list should be accepted in the response."""
-        holding_code = "000660"  # Not in candidates
-        stocks = [
-            {
-                "stock_code": "005930",  # candidate
-                "scenarios": [
-                    {
-                        "condition": {"rsi_below": 30},
-                        "action": "BUY",
-                        "confidence": 85,
-                        "rationale": "oversold",
-                    }
-                ],
-            },
-            {
-                "stock_code": holding_code,  # holding only
-                "scenarios": [
-                    {
-                        "condition": {"price_change_pct_below": -2.0},
-                        "action": "SELL",
-                        "confidence": 90,
-                        "rationale": "stop-loss",
-                    }
-                ],
-            },
-        ]
-        planner = _make_planner(gemini_response=_gemini_response_json(stocks=stocks))
-        candidates = [_candidate()]  # only 005930
-        holdings = [
-            {
-                "stock_code": holding_code,
-                "name": "SK Hynix",
-                "qty": 5,
-                "entry_price": 180000.0,
-                "unrealized_pnl_pct": -1.5,
-                "holding_days": 7,
-            }
-        ]
-
-        pb = await planner.generate_playbook(
-            "KR",
-            candidates,
-            today=date(2026, 2, 8),
-            current_holdings=holdings,
-        )
-
-        codes = [sp.stock_code for sp in pb.stock_playbooks]
-        assert "005930" in codes
-        assert holding_code in codes

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

tests/test_smart_scanner.py

@@ -350,42 +350,6 @@ class TestSmartVolatilityScanner:
         assert [c.stock_code for c in candidates] == ["ABCD"]
 
 
-class TestImpliedRSIFormula:
-    """Test the implied_rsi formula in SmartVolatilityScanner (issue #181)."""
-
-    def test_neutral_change_gives_neutral_rsi(self) -> None:
-        """0% change → implied_rsi = 50 (neutral)."""
-        # formula: 50 + (change_rate * 2.0)
-        rsi = max(0.0, min(100.0, 50.0 + (0.0 * 2.0)))
-        assert rsi == 50.0
-
-    def test_10pct_change_gives_rsi_70(self) -> None:
-        """10% upward change → implied_rsi = 70 (momentum signal)."""
-        rsi = max(0.0, min(100.0, 50.0 + (10.0 * 2.0)))
-        assert rsi == 70.0
-
-    def test_minus_10pct_gives_rsi_30(self) -> None:
-        """-10% change → implied_rsi = 30 (oversold signal)."""
-        rsi = max(0.0, min(100.0, 50.0 + (-10.0 * 2.0)))
-        assert rsi == 30.0
-
-    def test_saturation_at_25pct(self) -> None:
-        """Saturation occurs at >=25% change (not 12.5% as with old coefficient 4.0)."""
-        rsi_12pct = max(0.0, min(100.0, 50.0 + (12.5 * 2.0)))
-        rsi_25pct = max(0.0, min(100.0, 50.0 + (25.0 * 2.0)))
-        rsi_30pct = max(0.0, min(100.0, 50.0 + (30.0 * 2.0)))
-        # At 12.5% change: RSI = 75 (not 100, unlike old formula)
-        assert rsi_12pct == 75.0
-        # At 25%+ saturation
-        assert rsi_25pct == 100.0
-        assert rsi_30pct == 100.0  # Capped
-
-    def test_negative_saturation(self) -> None:
-        """Saturation at -25% gives RSI = 0."""
-        rsi = max(0.0, min(100.0, 50.0 + (-25.0 * 2.0)))
-        assert rsi == 0.0
-
-
 class TestRSICalculation:
     """Test RSI calculation in VolatilityAnalyzer."""
 

tests/test_strategies_base.py

@@ -1,32 +0,0 @@
-"""Tests for BaseStrategy abstract class."""
-
-from __future__ import annotations
-
-from typing import Any
-
-import pytest
-
-from src.strategies.base import BaseStrategy
-
-
-class ConcreteStrategy(BaseStrategy):
-    """Minimal concrete strategy for testing."""
-
-    def evaluate(self, market_data: dict[str, Any]) -> dict[str, Any]:
-        return {"action": "HOLD", "confidence": 50, "rationale": "test"}
-
-
-def test_base_strategy_cannot_be_instantiated() -> None:
-    """BaseStrategy cannot be instantiated directly (it's abstract)."""
-    with pytest.raises(TypeError):
-        BaseStrategy()  # type: ignore[abstract]
-
-
-def test_concrete_strategy_evaluate_returns_decision() -> None:
-    """Concrete subclass must implement evaluate and return a dict."""
-    strategy = ConcreteStrategy()
-    result = strategy.evaluate({"close": [100.0, 101.0]})
-    assert isinstance(result, dict)
-    assert result["action"] == "HOLD"
-    assert result["confidence"] == 50
-    assert "rationale" in result

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

tests/test_telegram_commands.py

@@ -875,139 +875,3 @@ class TestGetUpdates:
             updates = await handler._get_updates()
 
             assert updates == []
-
-    @pytest.mark.asyncio
-    async def test_get_updates_409_stops_polling(self) -> None:
-        """409 Conflict response stops the poller (_running = False) and returns empty list."""
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-        handler._running = True  # simulate active poller
-
-        mock_resp = AsyncMock()
-        mock_resp.status = 409
-        mock_resp.text = AsyncMock(
-            return_value='{"ok":false,"error_code":409,"description":"Conflict"}'
-        )
-        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
-        mock_resp.__aexit__ = AsyncMock(return_value=False)
-
-        with patch("aiohttp.ClientSession.post", return_value=mock_resp):
-            updates = await handler._get_updates()
-
-        assert updates == []
-        assert handler._running is False  # poller stopped
-
-    @pytest.mark.asyncio
-    async def test_poll_loop_exits_after_409(self) -> None:
-        """_poll_loop exits naturally after _running is set to False by a 409 response."""
-        import asyncio as _asyncio
-
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        call_count = 0
-
-        async def mock_get_updates_409() -> list[dict]:
-            nonlocal call_count
-            call_count += 1
-            # Simulate 409 stopping the poller
-            handler._running = False
-            return []
-
-        handler._get_updates = mock_get_updates_409  # type: ignore[method-assign]
-
-        handler._running = True
-        task = _asyncio.create_task(handler._poll_loop())
-        await _asyncio.wait_for(task, timeout=2.0)
-
-        # _get_updates called exactly once, then loop exited
-        assert call_count == 1
-        assert handler._running is False
-
-
-class TestCommandWithArgs:
-    """Test register_command_with_args and argument dispatch."""
-
-    def test_register_command_with_args_stored(self) -> None:
-        """register_command_with_args stores handler in _commands_with_args."""
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        async def my_handler(args: list[str]) -> None:
-            pass
-
-        handler.register_command_with_args("notify", my_handler)
-        assert "notify" in handler._commands_with_args
-        assert handler._commands_with_args["notify"] is my_handler
-
-    @pytest.mark.asyncio
-    async def test_args_handler_receives_arguments(self) -> None:
-        """Args handler is called with the trailing tokens."""
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        received: list[list[str]] = []
-
-        async def capture(args: list[str]) -> None:
-            received.append(args)
-
-        handler.register_command_with_args("notify", capture)
-
-        update = {
-            "message": {
-                "chat": {"id": "456"},
-                "text": "/notify scenario off",
-            }
-        }
-        await handler._handle_update(update)
-        assert received == [["scenario", "off"]]
-
-    @pytest.mark.asyncio
-    async def test_args_handler_takes_priority_over_no_args_handler(self) -> None:
-        """When both handlers exist for same command, args handler wins."""
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        no_args_called = []
-        args_called = []
-
-        async def no_args_handler() -> None:
-            no_args_called.append(True)
-
-        async def args_handler(args: list[str]) -> None:
-            args_called.append(args)
-
-        handler.register_command("notify", no_args_handler)
-        handler.register_command_with_args("notify", args_handler)
-
-        update = {
-            "message": {
-                "chat": {"id": "456"},
-                "text": "/notify all off",
-            }
-        }
-        await handler._handle_update(update)
-        assert args_called == [["all", "off"]]
-        assert no_args_called == []
-
-    @pytest.mark.asyncio
-    async def test_args_handler_with_no_trailing_args(self) -> None:
-        """/notify with no args still dispatches to args handler with empty list."""
-        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
-        handler = TelegramCommandHandler(client)
-
-        received: list[list[str]] = []
-
-        async def capture(args: list[str]) -> None:
-            received.append(args)
-
-        handler.register_command_with_args("notify", capture)
-
-        update = {
-            "message": {
-                "chat": {"id": "456"},
-                "text": "/notify",
-            }
-        }
-        await handler._handle_update(update)
-        assert received == [[]]