docs: v2 상태 반영 - 전체 문서 현행화 (#131)

- testing.md: 54 tests/4 files → 551 tests/25 files 반영, 전체 테스트 파일 설명
- architecture.md: v2 컴포넌트 추가 (Strategy, Context, Dashboard, Decision Logger 등),
  Playbook Mode 데이터 플로우, DB 스키마 5개 테이블, v2 환경변수
- commands.md: Dashboard 실행, Telegram 명령어 9종 레퍼런스
- CLAUDE.md: Project Structure 확장, 테스트 수 업데이트, --dashboard 플래그
- skills.md: DB 파일명 trades.db로 통일, Dashboard 명령어 추가
- requirements-log.md: 2026-02-16 문서 v2 동기화 요구사항 기록

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

CLAUDE.md

@@ -15,6 +15,9 @@ 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)
@@ -43,6 +46,10 @@ 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)
@@ -109,17 +116,23 @@ 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)
-├── brain/           # Gemini AI decision engine
+├── context/         # L1-L7 hierarchical memory system
 ├── core/            # Risk manager (READ-ONLY)
-├── evolution/       # Self-improvement optimizer
+├── 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)
 ├── markets/         # Market schedules and timezone handling
-├── notifications/   # Telegram real-time alerts
+├── notifications/   # Telegram alerts + bidirectional commands (9 commands)
+├── strategy/        # Pre-market planner, scenario engine, playbook store
 ├── db.py            # SQLite trade logging
 ├── main.py          # Trading loop orchestrator
 └── config.py        # Settings (from .env)
 
-tests/               # 343 tests across 14 files
+tests/               # 551 tests across 25 files
 docs/                # Extended documentation
 ```
 
@@ -131,6 +144,7 @@ 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)

docs/architecture.md

@@ -2,7 +2,9 @@
 
 ## Overview
 
-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).
+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.
 
 ## Trading Modes
 
@@ -46,9 +48,11 @@ 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 (10 requests per second)
+- Leaky-bucket rate limiter (configurable RPS, default 2.0)
 - POST body hash-key signing for order authentication
 - Custom SSL context with disabled hostname verification for VTS (virtual trading) endpoint due to known certificate mismatch
+- `fetch_market_rankings()` — Fetch volume surge rankings from KIS API
+- `get_daily_prices()` — Fetch OHLCV history for technical analysis
 
 **OverseasBroker** (`overseas.py`) — KIS overseas stock API wrapper
 
@@ -63,10 +67,7 @@ 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
-
-**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
+- 10 global markets defined (KR, US_NASDAQ, US_NYSE, US_AMEX, JP, HK, CN_SHA, CN_SZA, VN_HNX, VN_HSX)
 
 ### 2. Analysis (`src/analysis/`)
 
@@ -91,14 +92,9 @@ High-frequency trading with individual stock analysis:
 - **Fallback**: Uses static watchlist if ranking API unavailable
 - **Realtime mode only**: Daily mode uses batch processing for API efficiency
 
-**Benefits:**
-- Reduces Gemini API calls from 20-30 stocks to 1-3 qualified candidates
-- Fast Python-based filtering before expensive AI judgment
-- Logs selection context (RSI, volume_ratio, signal, score) for Evolution system
+### 3. Brain (`src/brain/`)
 
-### 3. Brain (`src/brain/gemini_client.py`)
-
-**GeminiClient** — AI decision engine powered by Google Gemini
+**GeminiClient** (`gemini_client.py`) — AI decision engine powered by Google Gemini
 
 - Constructs structured prompts from market data
 - Parses JSON responses into `TradeDecision` objects (`action`, `confidence`, `rationale`)
@@ -106,11 +102,20 @@ 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
@@ -118,7 +123,79 @@ 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. Notifications (`src/notifications/telegram_client.py`)
+### 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`)
 
 **TelegramClient** — Real-time event notifications via Telegram Bot API
 
@@ -126,7 +203,13 @@ 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
-- Gracefully handles API errors, network timeouts, invalid tokens
+
+**TelegramCommandHandler** — Bidirectional command interface
+
+- Long polling from Telegram API (configurable `TELEGRAM_POLLING_INTERVAL`)
+- 9 interactive commands: `/help`, `/status`, `/positions`, `/report`, `/scenarios`, `/review`, `/dashboard`, `/stop`, `/resume`
+- Authorization filtering by `TELEGRAM_CHAT_ID`
+- Enable/disable via `TELEGRAM_COMMANDS_ENABLED` (default: true)
 
 **Notification Types:**
 - Trade execution (BUY/SELL with confidence)
@@ -134,12 +217,12 @@ 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
 
-**Setup:** See [src/notifications/README.md](../src/notifications/README.md) for bot creation and configuration.
+### 9. Evolution (`src/evolution/`)
 
-### 6. Evolution (`src/evolution/optimizer.py`)
-
-**StrategyOptimizer** — Self-improvement loop
+**StrategyOptimizer** (`optimizer.py`) — Self-improvement loop
 
 - Analyzes high-confidence losing trades from SQLite
 - Asks Gemini to generate new `BaseStrategy` subclasses
@@ -147,99 +230,196 @@ 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             │
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Smart Scanner (Python-first)      │
+        │ Smart Scanner (Python-first)     │
         │ - Fetch volume rankings (KIS)    │
         │ - Get 20d price history per stock│
         │ - Calculate RSI(14) + vol ratio  │
         │ - Filter: vol>2x AND RSI extreme │
         │ - Return top 3 qualified stocks  │
-        └──────────────────┬────────────────┘
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ For Each Qualified Candidate      │
-        └──────────────────┬────────────────┘
+        │ For Each Qualified Candidate     │
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
         │ Broker: Fetch Market Data        │
         │ - Domestic: orderbook + balance  │
         │ - Overseas: price + balance      │
-        └──────────────────┬────────────────┘
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Calculate P&L                     │
-        │ pnl_pct = (eval - cost) / cost   │
-        └──────────────────┬────────────────┘
+        │ Brain: Get Decision (AI)         │
+        │ - Build prompt with market data  │
+        │ - Call Gemini API                │
+        │ - Parse JSON response            │
+        │ - Return TradeDecision           │
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Brain: Get Decision (AI)          │
-        │ - Build prompt with market data   │
-        │ - Call Gemini API                 │
-        │ - Parse JSON response             │
-        │ - Return TradeDecision            │
-        └──────────────────┬────────────────┘
+        │ Risk Manager: Validate Order     │
+        │ - Check circuit breaker          │
+        │ - Check fat-finger limit         │
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ Risk Manager: Validate Order      │
-        │ - Check circuit breaker           │
-        │ - Check fat-finger limit          │
-        │ - Raise if validation fails       │
-        └──────────────────┬────────────────┘
+        │ Broker: Execute Order            │
+        │ - Domestic: send_order()         │
+        │ - Overseas: send_overseas_order()│
+        └──────────────────┬───────────────┘
                            │
                            ▼
         ┌──────────────────────────────────┐
-        │ 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    │
-        └───────────────────────────────────┘
+        │ Decision Logger + Notifications  │
+        │ - Log trade to SQLite            │
+        │ - selection_context (JSON)       │
+        │ - Telegram notification          │
+        └──────────────────────────────────┘
 ```
 
 ## Database Schema
 
-**SQLite** (`src/db.py`)
+**SQLite** (`src/db.py`) — Database: `data/trades.db`
 
+### trades
 ```sql
 CREATE TABLE trades (
     id INTEGER PRIMARY KEY AUTOINCREMENT,
@@ -251,25 +431,73 @@ CREATE TABLE trades (
     quantity INTEGER,
     price REAL,
     pnl REAL DEFAULT 0.0,
-    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}
+    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
 );
 ```
 
-**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
-}
+### 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
 ```
 
-Enables Evolution system to analyze correlation between selection criteria and trade outcomes.
+### 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
+```
 
-Auto-migration: Adds `market`, `exchange_code`, and `selection_context` columns if missing for backward compatibility.
+### playbooks
+```sql
+CREATE TABLE playbooks (
+    id INTEGER PRIMARY KEY AUTOINCREMENT,
+    date TEXT NOT NULL,
+    market TEXT NOT NULL,
+    status TEXT DEFAULT 'generated',
+    playbook_json TEXT NOT NULL,   -- Full playbook with scenarios
+    generated_at TEXT NOT NULL,
+    token_count INTEGER,
+    scenario_count INTEGER,
+    match_count INTEGER DEFAULT 0
+);
+-- Indices: idx_playbooks_date, idx_playbooks_market
+```
+
+### context_metadata
+```sql
+CREATE TABLE context_metadata (
+    layer TEXT PRIMARY KEY,
+    description TEXT,
+    retention_days INTEGER,
+    aggregation_source TEXT
+);
+```
 
 ## Configuration
 
@@ -284,29 +512,62 @@ KIS_APP_SECRET=your_app_secret
 KIS_ACCOUNT_NO=XXXXXXXX-XX
 GEMINI_API_KEY=your_gemini_key
 
-# Optional
+# Optional — Trading Mode
 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)
 
-# Telegram Notifications (optional)
+# Optional — Database
+DB_PATH=data/trades.db
+
+# Optional — Risk
+CONFIDENCE_THRESHOLD=80
+MAX_LOSS_PCT=3.0
+MAX_ORDER_PCT=30.0
+
+# Optional — Markets
+ENABLED_MARKETS=KR,US         # Comma-separated market codes
+RATE_LIMIT_RPS=2.0            # KIS API requests per second
+
+# Optional — Pre-Market Planner (v2)
+PRE_MARKET_MINUTES=30         # Minutes before market open to generate playbook
+MAX_SCENARIOS_PER_STOCK=5     # Max scenarios per stock in playbook
+PLANNER_TIMEOUT_SECONDS=60    # Timeout for playbook generation
+DEFENSIVE_PLAYBOOK_ON_FAILURE=true  # Fallback on AI failure
+RESCAN_INTERVAL_SECONDS=300   # Scenario rescan interval during trading
+
+# Optional — Smart Scanner (realtime mode only)
+RSI_OVERSOLD_THRESHOLD=30     # 0-50, oversold threshold
+RSI_MOMENTUM_THRESHOLD=70     # 50-100, momentum threshold
+VOL_MULTIPLIER=2.0            # Minimum volume ratio (2.0 = 200%)
+SCANNER_TOP_N=3               # Max qualified candidates per scan
+
+# Optional — Dashboard
+DASHBOARD_ENABLED=false       # Enable FastAPI dashboard
+DASHBOARD_HOST=127.0.0.1      # Dashboard bind address
+DASHBOARD_PORT=8080           # Dashboard port (1-65535)
+
+# Optional — Telegram
 TELEGRAM_BOT_TOKEN=1234567890:ABCdefGHIjklMNOpqrsTUVwxyz
 TELEGRAM_CHAT_ID=123456789
 TELEGRAM_ENABLED=true
+TELEGRAM_COMMANDS_ENABLED=true   # Enable bidirectional commands
+TELEGRAM_POLLING_INTERVAL=1.0    # Command polling interval (seconds)
 
-# Smart Scanner (optional, 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 — 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=...
 ```
 
 Tests use in-memory SQLite (`DB_PATH=":memory:"`) and dummy credentials via `tests/conftest.py`.
@@ -340,4 +601,9 @@ 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
 
-**Guarantee**: Notification failures never interrupt trading operations.
+### 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.

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
+# Run full test suite with coverage (551 tests across 25 files)
 pytest -v --cov=src --cov-report=term-missing
 
 # Run a single test file
@@ -137,11 +137,61 @@ 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`.
+
 ## Environment Setup
 
 ```bash

docs/requirements-log.md

@@ -86,3 +86,28 @@
   - Plan Consistency (필수), Safety & Constraints, Quality, Workflow 4개 카테고리
 
 **이슈/PR:** #114
+
+---
+
+## 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

docs/skills.md

@@ -34,6 +34,12 @@ 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
@@ -59,7 +65,7 @@ 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 `trade_logs.db` for failing patterns
+1. Analyze `trades.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
@@ -91,12 +97,12 @@ curl http://localhost:8080/health
 
 ### View Trade Logs
 ```bash
-sqlite3 data/trade_logs.db "SELECT * FROM trades ORDER BY timestamp DESC LIMIT 20;"
+sqlite3 data/trades.db "SELECT * FROM trades ORDER BY timestamp DESC LIMIT 20;"
 ```
 
 ### Export Trade History
 ```bash
-sqlite3 -header -csv data/trade_logs.db "SELECT * FROM trades;" > trades_export.csv
+sqlite3 -header -csv data/trades.db "SELECT * FROM trades;" > trades_export.csv
 ```
 
 ## Safety Checklist (Pre-Deploy)

docs/testing.md

@@ -2,51 +2,29 @@
 
 ## Test Structure
 
-**54 tests** across four files. `asyncio_mode = "auto"` in pyproject.toml — async tests need no special decorator.
+**551 tests** across **25 files**. `asyncio_mode = "auto"` in pyproject.toml — async tests need no special decorator.
 
 The `settings` fixture in `conftest.py` provides safe defaults with test credentials and in-memory DB.
 
 ### Test Files
 
-#### `tests/test_risk.py` (11 tests)
-- Circuit breaker boundaries
-- Fat-finger edge cases
+#### Core Components
+
+##### `tests/test_risk.py` (14 tests)
+- Circuit breaker boundaries and exact threshold triggers
+- Fat-finger edge cases and percentage validation
 - P&L calculation edge cases
 - Order validation logic
 
-**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)
+##### `tests/test_broker.py` (11 tests)
 - OAuth token lifecycle
 - Rate limiting enforcement
 - Hash key generation
 - Network error handling
 - SSL context configuration
 
-**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
+##### `tests/test_brain.py` (24 tests)
+- Valid JSON parsing and markdown-wrapped JSON handling
 - Malformed JSON fallback
 - Missing fields handling
 - Invalid action validation
@@ -54,33 +32,143 @@ async def test_rate_limiter(broker):
 - Empty response handling
 - Prompt construction for different markets
 
-**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)
+##### `tests/test_market_schedule.py` (24 tests)
 - Market open/close logic
 - Timezone handling (UTC, Asia/Seoul, America/New_York, etc.)
 - DST (Daylight Saving Time) transitions
-- Weekend handling
-- Lunch break logic
+- Weekend handling and lunch break logic
 - Multiple market filtering
 - Next market open calculation
 
-**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
-```
+##### `tests/test_db.py` (3 tests)
+- Database initialization and table creation
+- Trade logging with all fields (market, exchange_code, decision_id)
+- Query and retrieval operations
+
+##### `tests/test_main.py` (37 tests)
+- Trading loop orchestration
+- Market iteration and stock processing
+- Dashboard integration (`--dashboard` flag)
+- Telegram command handler wiring
+- Error handling and graceful shutdown
+
+#### Strategy & Playbook (v2)
+
+##### `tests/test_pre_market_planner.py` (37 tests)
+- Pre-market playbook generation
+- Gemini API integration for scenario creation
+- Timeout handling and defensive playbook fallback
+- Multi-market playbook generation
+
+##### `tests/test_scenario_engine.py` (44 tests)
+- Scenario matching against live market data
+- Confidence scoring and threshold filtering
+- Multiple scenario type handling
+- Edge cases (no match, partial match, expired scenarios)
+
+##### `tests/test_playbook_store.py` (23 tests)
+- Playbook persistence to SQLite
+- Date-based retrieval and market filtering
+- Playbook status management (generated, active, expired)
+- JSON serialization/deserialization
+
+##### `tests/test_strategy_models.py` (33 tests)
+- Pydantic model validation for scenarios, playbooks, decisions
+- Field constraints and default values
+- Serialization round-trips
+
+#### Analysis & Scanning
+
+##### `tests/test_volatility.py` (24 tests)
+- ATR and RSI calculation accuracy
+- Volume surge ratio computation
+- Momentum scoring
+- Breakout/breakdown pattern detection
+- Market scanner watchlist management
+
+##### `tests/test_smart_scanner.py` (13 tests)
+- Python-first filtering pipeline
+- RSI and volume ratio filter logic
+- Candidate scoring and ranking
+- Fallback to static watchlist
+
+#### Context & Memory
+
+##### `tests/test_context.py` (18 tests)
+- L1-L7 layer storage and retrieval
+- Context key-value CRUD operations
+- Timeframe-based queries
+- Layer metadata management
+
+##### `tests/test_context_scheduler.py` (5 tests)
+- Periodic context aggregation scheduling
+- Layer summarization triggers
+
+#### Evolution & Review
+
+##### `tests/test_evolution.py` (24 tests)
+- Strategy optimization loop
+- High-confidence losing trade analysis
+- Generated strategy validation
+
+##### `tests/test_daily_review.py` (10 tests)
+- End-of-day review generation
+- Trade performance summarization
+- Context layer (L6_DAILY) integration
+
+##### `tests/test_scorecard.py` (3 tests)
+- Daily scorecard metrics calculation
+- Win rate, P&L, confidence tracking
+
+#### Notifications & Commands
+
+##### `tests/test_telegram.py` (25 tests)
+- Message sending and formatting
+- Rate limiting (leaky bucket)
+- Error handling (network timeout, invalid token)
+- Auto-disable on missing credentials
+- Notification types (trade, circuit breaker, fat-finger, market events)
+
+##### `tests/test_telegram_commands.py` (31 tests)
+- 9 command handlers (/help, /status, /positions, /report, /scenarios, /review, /dashboard, /stop, /resume)
+- Long polling and command dispatch
+- Authorization filtering by chat_id
+- Command response formatting
+
+#### Dashboard
+
+##### `tests/test_dashboard.py` (14 tests)
+- FastAPI endpoint responses (8 API routes)
+- Status, playbook, scorecard, performance, context, decisions, scenarios
+- Query parameter handling (market, date, limit)
+
+#### Performance & Quality
+
+##### `tests/test_token_efficiency.py` (34 tests)
+- Gemini token usage optimization
+- Prompt size reduction verification
+- Cache effectiveness
+
+##### `tests/test_latency_control.py` (30 tests)
+- API call latency measurement
+- Rate limiter timing accuracy
+- Async operation overhead
+
+##### `tests/test_decision_logger.py` (9 tests)
+- Decision audit trail completeness
+- Context snapshot capture
+- Outcome tracking (P&L, accuracy)
+
+##### `tests/test_data_integration.py` (38 tests)
+- External data source integration
+- News API, market data, economic calendar
+- Error handling for API failures
+
+##### `tests/test_backup.py` (23 tests)
+- Backup scheduler and execution
+- Cloud storage (S3) upload
+- Health monitoring
+- Data export functionality
 
 ## Coverage Requirements
 
@@ -91,20 +179,6 @@ 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

src/config.py

@@ -101,4 +101,7 @@ class Settings(BaseSettings):
     @property
     def enabled_market_list(self) -> list[str]:
         """Parse ENABLED_MARKETS into list of market codes."""
-        return [m.strip() for m in self.ENABLED_MARKETS.split(",") if m.strip()]
+        from src.markets.schedule import expand_market_codes
+
+        raw = [m.strip() for m in self.ENABLED_MARKETS.split(",") if m.strip()]
+        return expand_market_codes(raw)

src/dashboard/app.py

@@ -26,7 +26,19 @@ def create_dashboard_app(db_path: str) -> FastAPI:
     def get_status() -> dict[str, Any]:
         today = datetime.now(UTC).date().isoformat()
         with _connect(db_path) as conn:
-            markets = ["KR", "US"]
+            market_rows = conn.execute(
+                """
+                SELECT DISTINCT market FROM (
+                    SELECT market FROM trades WHERE DATE(timestamp) = ?
+                    UNION
+                    SELECT market FROM decision_logs WHERE DATE(timestamp) = ?
+                    UNION
+                    SELECT market FROM playbooks WHERE date = ?
+                ) ORDER BY market
+                """,
+                (today, today, today),
+            ).fetchall()
+            markets = [row[0] for row in market_rows] if market_rows else []
             market_status: dict[str, Any] = {}
             total_trades = 0
             total_pnl = 0.0

src/db.py

@@ -214,3 +214,24 @@ def get_latest_buy_trade(
     if not row:
         return None
     return {"decision_id": row[0], "price": row[1], "quantity": row[2]}
+
+
+def get_open_position(
+    conn: sqlite3.Connection, stock_code: str, market: str
+) -> dict[str, Any] | None:
+    """Return open position if latest trade is BUY, else None."""
+    cursor = conn.execute(
+        """
+        SELECT action, decision_id, price, quantity
+        FROM trades
+        WHERE stock_code = ?
+          AND market = ?
+        ORDER BY timestamp DESC
+        LIMIT 1
+        """,
+        (stock_code, market),
+    )
+    row = cursor.fetchone()
+    if not row or row[0] != "BUY":
+        return None
+    return {"decision_id": row[1], "price": row[2], "quantity": row[3]}

src/main.py

@@ -8,6 +8,7 @@ from __future__ import annotations
 
 import argparse
 import asyncio
+import json
 import logging
 import signal
 import threading
@@ -28,7 +29,7 @@ from src.context.store import ContextStore
 from src.core.criticality import CriticalityAssessor
 from src.core.priority_queue import PriorityTaskQueue
 from src.core.risk_manager import CircuitBreakerTripped, FatFingerRejected, RiskManager
-from src.db import get_latest_buy_trade, init_db, log_trade
+from src.db import get_latest_buy_trade, get_open_position, init_db, log_trade
 from src.evolution.daily_review import DailyReviewer
 from src.evolution.optimizer import EvolutionOptimizer
 from src.logging.decision_logger import DecisionLogger
@@ -114,6 +115,7 @@ async def trading_cycle(
 
         current_price = safe_float(orderbook.get("output1", {}).get("stck_prpr", "0"))
         foreigner_net = safe_float(orderbook.get("output1", {}).get("frgn_ntby_qty", "0"))
+        price_change_pct = safe_float(orderbook.get("output1", {}).get("prdy_ctrt", "0"))
     else:
         # Overseas market
         price_data = await overseas_broker.get_overseas_price(
@@ -136,6 +138,7 @@ async def trading_cycle(
 
         current_price = safe_float(price_data.get("output", {}).get("last", "0"))
         foreigner_net = 0.0  # Not available for overseas
+        price_change_pct = safe_float(price_data.get("output", {}).get("rate", "0"))
 
     # Calculate daily P&L %
     pnl_pct = (
@@ -149,6 +152,7 @@ async def trading_cycle(
         "market_name": market.name,
         "current_price": current_price,
         "foreigner_net": foreigner_net,
+        "price_change_pct": price_change_pct,
     }
 
     # Enrich market_data with scanner metrics for scenario engine
@@ -240,6 +244,34 @@ async def trading_cycle(
         confidence=match.confidence,
         rationale=match.rationale,
     )
+    stock_playbook = playbook.get_stock_playbook(stock_code)
+
+    if decision.action == "HOLD":
+        open_position = get_open_position(db_conn, stock_code, market.code)
+        if open_position:
+            entry_price = safe_float(open_position.get("price"), 0.0)
+            if entry_price > 0:
+                loss_pct = (current_price - entry_price) / entry_price * 100
+                stop_loss_threshold = -2.0
+                if stock_playbook and stock_playbook.scenarios:
+                    stop_loss_threshold = stock_playbook.scenarios[0].stop_loss_pct
+
+                if loss_pct <= stop_loss_threshold:
+                    decision = TradeDecision(
+                        action="SELL",
+                        confidence=95,
+                        rationale=(
+                            f"Stop-loss triggered ({loss_pct:.2f}% <= "
+                            f"{stop_loss_threshold:.2f}%)"
+                        ),
+                    )
+                    logger.info(
+                        "Stop-loss override for %s (%s): %.2f%% <= %.2f%%",
+                        stock_code,
+                        market.name,
+                        loss_pct,
+                        stop_loss_threshold,
+                    )
     logger.info(
         "Decision for %s (%s): %s (confidence=%d)",
         stock_code,
@@ -278,6 +310,7 @@ async def trading_cycle(
     input_data = {
         "current_price": current_price,
         "foreigner_net": foreigner_net,
+        "price_change_pct": price_change_pct,
         "total_eval": total_eval,
         "total_cash": total_cash,
         "pnl_pct": pnl_pct,
@@ -507,6 +540,9 @@ async def run_daily_session(
                     foreigner_net = safe_float(
                         orderbook.get("output1", {}).get("frgn_ntby_qty", "0")
                     )
+                    price_change_pct = safe_float(
+                        orderbook.get("output1", {}).get("prdy_ctrt", "0")
+                    )
                 else:
                     price_data = await overseas_broker.get_overseas_price(
                         market.exchange_code, stock_code
@@ -515,12 +551,16 @@ async def run_daily_session(
                         price_data.get("output", {}).get("last", "0")
                     )
                     foreigner_net = 0.0
+                    price_change_pct = safe_float(
+                        price_data.get("output", {}).get("rate", "0")
+                    )
 
                 stock_data: dict[str, Any] = {
                     "stock_code": stock_code,
                     "market_name": market.name,
                     "current_price": current_price,
                     "foreigner_net": foreigner_net,
+                    "price_change_pct": price_change_pct,
                 }
                 # Enrich with scanner metrics
                 cand = candidate_map.get(stock_code)
@@ -820,7 +860,7 @@ async def _run_evolution_loop(
     market_date: str,
 ) -> None:
     """Run evolution loop once at US close (end of trading day)."""
-    if market_code != "US":
+    if not market_code.startswith("US"):
         return
 
     try:
@@ -936,6 +976,10 @@ async def run(settings: Settings) -> None:
             "/help - Show available commands\n"
             "/status - Trading status (mode, markets, P&L)\n"
             "/positions - Current holdings\n"
+            "/report - Daily summary report\n"
+            "/scenarios - Today's playbook scenarios\n"
+            "/review - Recent scorecards\n"
+            "/dashboard - Dashboard URL/status\n"
             "/stop - Pause trading\n"
             "/resume - Resume trading"
         )
@@ -1055,11 +1099,164 @@ async def run(settings: Settings) -> None:
                 "<b>⚠️ Error</b>\n\nFailed to retrieve positions."
             )
 
+    async def handle_report() -> None:
+        """Handle /report command - show daily summary metrics."""
+        try:
+            today = datetime.now(UTC).date().isoformat()
+            trade_row = db_conn.execute(
+                """
+                SELECT COUNT(*) AS trade_count,
+                       COALESCE(SUM(pnl), 0.0) AS total_pnl,
+                       SUM(CASE WHEN pnl > 0 THEN 1 ELSE 0 END) AS wins
+                FROM trades
+                WHERE DATE(timestamp) = ?
+                """,
+                (today,),
+            ).fetchone()
+            decision_row = db_conn.execute(
+                """
+                SELECT COUNT(*) AS decision_count,
+                       COALESCE(AVG(confidence), 0.0) AS avg_confidence
+                FROM decision_logs
+                WHERE DATE(timestamp) = ?
+                """,
+                (today,),
+            ).fetchone()
+
+            trade_count = int(trade_row[0] if trade_row else 0)
+            total_pnl = float(trade_row[1] if trade_row else 0.0)
+            wins = int(trade_row[2] if trade_row and trade_row[2] is not None else 0)
+            decision_count = int(decision_row[0] if decision_row else 0)
+            avg_confidence = float(decision_row[1] if decision_row else 0.0)
+            win_rate = (wins / trade_count * 100.0) if trade_count > 0 else 0.0
+
+            await telegram.send_message(
+                "<b>📈 Daily Report</b>\n\n"
+                f"<b>Date:</b> {today}\n"
+                f"<b>Trades:</b> {trade_count}\n"
+                f"<b>Total P&L:</b> {total_pnl:+.2f}\n"
+                f"<b>Win Rate:</b> {win_rate:.2f}%\n"
+                f"<b>Decisions:</b> {decision_count}\n"
+                f"<b>Avg Confidence:</b> {avg_confidence:.2f}"
+            )
+        except Exception as exc:
+            logger.error("Error in /report handler: %s", exc)
+            await telegram.send_message(
+                "<b>⚠️ Error</b>\n\nFailed to generate daily report."
+            )
+
+    async def handle_scenarios() -> None:
+        """Handle /scenarios command - show today's playbook scenarios."""
+        try:
+            today = datetime.now(UTC).date().isoformat()
+            rows = db_conn.execute(
+                """
+                SELECT market, playbook_json
+                FROM playbooks
+                WHERE date = ?
+                ORDER BY market
+                """,
+                (today,),
+            ).fetchall()
+
+            if not rows:
+                await telegram.send_message(
+                    "<b>🧠 Today's Scenarios</b>\n\nNo playbooks found for today."
+                )
+                return
+
+            lines = ["<b>🧠 Today's Scenarios</b>", ""]
+            for market, playbook_json in rows:
+                lines.append(f"<b>{market}</b>")
+                playbook_data = {}
+                try:
+                    playbook_data = json.loads(playbook_json)
+                except Exception:
+                    playbook_data = {}
+
+                stock_playbooks = playbook_data.get("stock_playbooks", [])
+                if not stock_playbooks:
+                    lines.append("- No scenarios")
+                    lines.append("")
+                    continue
+
+                for stock_pb in stock_playbooks:
+                    stock_code = stock_pb.get("stock_code", "N/A")
+                    scenarios = stock_pb.get("scenarios", [])
+                    for sc in scenarios:
+                        action = sc.get("action", "HOLD")
+                        confidence = sc.get("confidence", 0)
+                        lines.append(f"- {stock_code}: {action} ({confidence})")
+                lines.append("")
+
+            await telegram.send_message("\n".join(lines).strip())
+        except Exception as exc:
+            logger.error("Error in /scenarios handler: %s", exc)
+            await telegram.send_message(
+                "<b>⚠️ Error</b>\n\nFailed to retrieve scenarios."
+            )
+
+    async def handle_review() -> None:
+        """Handle /review command - show recent scorecards."""
+        try:
+            rows = db_conn.execute(
+                """
+                SELECT timeframe, key, value
+                FROM contexts
+                WHERE layer = 'L6_DAILY' AND key LIKE 'scorecard_%'
+                ORDER BY updated_at DESC
+                LIMIT 5
+                """
+            ).fetchall()
+
+            if not rows:
+                await telegram.send_message(
+                    "<b>📝 Recent Reviews</b>\n\nNo scorecards available."
+                )
+                return
+
+            lines = ["<b>📝 Recent Reviews</b>", ""]
+            for timeframe, key, value in rows:
+                scorecard = json.loads(value)
+                market = key.replace("scorecard_", "")
+                total_pnl = float(scorecard.get("total_pnl", 0.0))
+                win_rate = float(scorecard.get("win_rate", 0.0))
+                decisions = int(scorecard.get("total_decisions", 0))
+                lines.append(
+                    f"- {timeframe} {market}: P&L {total_pnl:+.2f}, "
+                    f"Win {win_rate:.2f}%, Decisions {decisions}"
+                )
+
+            await telegram.send_message("\n".join(lines))
+        except Exception as exc:
+            logger.error("Error in /review handler: %s", exc)
+            await telegram.send_message(
+                "<b>⚠️ Error</b>\n\nFailed to retrieve reviews."
+            )
+
+    async def handle_dashboard() -> None:
+        """Handle /dashboard command - show dashboard URL if enabled."""
+        if not settings.DASHBOARD_ENABLED:
+            await telegram.send_message(
+                "<b>🖥️ Dashboard</b>\n\nDashboard is not enabled."
+            )
+            return
+
+        url = f"http://{settings.DASHBOARD_HOST}:{settings.DASHBOARD_PORT}"
+        await telegram.send_message(
+            "<b>🖥️ Dashboard</b>\n\n"
+            f"<b>URL:</b> {url}"
+        )
+
     command_handler.register_command("help", handle_help)
     command_handler.register_command("stop", handle_stop)
     command_handler.register_command("resume", handle_resume)
     command_handler.register_command("status", handle_status)
     command_handler.register_command("positions", handle_positions)
+    command_handler.register_command("report", handle_report)
+    command_handler.register_command("scenarios", handle_scenarios)
+    command_handler.register_command("review", handle_review)
+    command_handler.register_command("dashboard", handle_dashboard)
 
     # Initialize volatility hunter
     volatility_analyzer = VolatilityAnalyzer(min_volume_surge=2.0, min_price_change=1.0)

src/markets/schedule.py

@@ -123,6 +123,23 @@ MARKETS: dict[str, MarketInfo] = {
     ),
 }
 
+MARKET_SHORTHAND: dict[str, list[str]] = {
+    "US": ["US_NASDAQ", "US_NYSE", "US_AMEX"],
+    "CN": ["CN_SHA", "CN_SZA"],
+    "VN": ["VN_HAN", "VN_HCM"],
+}
+
+
+def expand_market_codes(codes: list[str]) -> list[str]:
+    """Expand shorthand market codes into concrete exchange market codes."""
+    expanded: list[str] = []
+    for code in codes:
+        if code in MARKET_SHORTHAND:
+            expanded.extend(MARKET_SHORTHAND[code])
+        else:
+            expanded.append(code)
+    return expanded
+
 
 def is_market_open(market: MarketInfo, now: datetime | None = None) -> bool:
     """

tests/test_dashboard.py

@@ -1,21 +1,25 @@
-"""Tests for FastAPI dashboard endpoints."""
+"""Tests for dashboard endpoint handlers."""
 
 from __future__ import annotations
 
 import json
 import sqlite3
+from collections.abc import Callable
+from datetime import UTC, datetime
 from pathlib import Path
+from typing import Any
 
 import pytest
-
-pytest.importorskip("fastapi")
-from fastapi.testclient import TestClient
+from fastapi import HTTPException
+from fastapi.responses import FileResponse
 
 from src.dashboard.app import create_dashboard_app
 from src.db import init_db
 
 
 def _seed_db(conn: sqlite3.Connection) -> None:
+    today = datetime.now(UTC).date().isoformat()
+
     conn.execute(
         """
         INSERT INTO playbooks (
@@ -34,6 +38,24 @@ def _seed_db(conn: sqlite3.Connection) -> None:
             1,
         ),
     )
+    conn.execute(
+        """
+        INSERT INTO playbooks (
+            date, market, status, playbook_json, generated_at,
+            token_count, scenario_count, match_count
+        ) VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        (
+            today,
+            "US_NASDAQ",
+            "ready",
+            json.dumps({"market": "US_NASDAQ", "stock_playbooks": []}),
+            f"{today}T08:30:00+00:00",
+            100,
+            1,
+            0,
+        ),
+    )
     conn.execute(
         """
         INSERT INTO contexts (layer, timeframe, key, value, created_at, updated_at)
@@ -71,7 +93,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
         """,
         (
             "d-kr-1",
-            "2026-02-14T09:10:00+00:00",
+            f"{today}T09:10:00+00:00",
             "005930",
             "KR",
             "KRX",
@@ -91,9 +113,9 @@ def _seed_db(conn: sqlite3.Connection) -> None:
         """,
         (
             "d-us-1",
-            "2026-02-14T21:10:00+00:00",
+            f"{today}T21:10:00+00:00",
             "AAPL",
-            "US",
+            "US_NASDAQ",
             "NASDAQ",
             "SELL",
             80,
@@ -110,7 +132,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
         ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
         """,
         (
-            "2026-02-14T09:11:00+00:00",
+            f"{today}T09:11:00+00:00",
             "005930",
             "BUY",
             85,
@@ -132,7 +154,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
         ) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
         """,
         (
-            "2026-02-14T21:11:00+00:00",
+            f"{today}T21:11:00+00:00",
             "AAPL",
             "SELL",
             80,
@@ -140,7 +162,7 @@ def _seed_db(conn: sqlite3.Connection) -> None:
             1,
             200,
             -1.0,
-            "US",
+            "US_NASDAQ",
             "NASDAQ",
             None,
             "d-us-1",
@@ -149,122 +171,128 @@ def _seed_db(conn: sqlite3.Connection) -> None:
     conn.commit()
 
 
-def _client(tmp_path: Path) -> TestClient:
+def _app(tmp_path: Path) -> Any:
     db_path = tmp_path / "dashboard_test.db"
     conn = init_db(str(db_path))
     _seed_db(conn)
     conn.close()
-    app = create_dashboard_app(str(db_path))
-    return TestClient(app)
+    return create_dashboard_app(str(db_path))
+
+
+def _endpoint(app: Any, path: str) -> Callable[..., Any]:
+    for route in app.routes:
+        if getattr(route, "path", None) == path:
+            return route.endpoint
+    raise AssertionError(f"route not found: {path}")
 
 
 def test_index_serves_html(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/")
-    assert resp.status_code == 200
-    assert "The Ouroboros Dashboard API" in resp.text
+    app = _app(tmp_path)
+    index = _endpoint(app, "/")
+    resp = index()
+    assert isinstance(resp, FileResponse)
+    assert "index.html" in str(resp.path)
 
 
 def test_status_endpoint(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/status")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_status = _endpoint(app, "/api/status")
+    body = get_status()
     assert "KR" in body["markets"]
-    assert "US" in body["markets"]
+    assert "US_NASDAQ" in body["markets"]
     assert "totals" in body
 
 
 def test_playbook_found(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/playbook/2026-02-14?market=KR")
-    assert resp.status_code == 200
-    assert resp.json()["market"] == "KR"
+    app = _app(tmp_path)
+    get_playbook = _endpoint(app, "/api/playbook/{date_str}")
+    body = get_playbook("2026-02-14", market="KR")
+    assert body["market"] == "KR"
 
 
 def test_playbook_not_found(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/playbook/2026-02-15?market=KR")
-    assert resp.status_code == 404
+    app = _app(tmp_path)
+    get_playbook = _endpoint(app, "/api/playbook/{date_str}")
+    with pytest.raises(HTTPException, match="playbook not found"):
+        get_playbook("2026-02-15", market="KR")
 
 
 def test_scorecard_found(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/scorecard/2026-02-14?market=KR")
-    assert resp.status_code == 200
-    assert resp.json()["scorecard"]["total_pnl"] == 1.5
+    app = _app(tmp_path)
+    get_scorecard = _endpoint(app, "/api/scorecard/{date_str}")
+    body = get_scorecard("2026-02-14", market="KR")
+    assert body["scorecard"]["total_pnl"] == 1.5
 
 
 def test_scorecard_not_found(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/scorecard/2026-02-15?market=KR")
-    assert resp.status_code == 404
+    app = _app(tmp_path)
+    get_scorecard = _endpoint(app, "/api/scorecard/{date_str}")
+    with pytest.raises(HTTPException, match="scorecard not found"):
+        get_scorecard("2026-02-15", market="KR")
 
 
 def test_performance_all(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/performance?market=all")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_performance = _endpoint(app, "/api/performance")
+    body = get_performance(market="all")
     assert body["market"] == "all"
     assert body["combined"]["total_trades"] == 2
     assert len(body["by_market"]) == 2
 
 
 def test_performance_market_filter(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/performance?market=KR")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_performance = _endpoint(app, "/api/performance")
+    body = get_performance(market="KR")
     assert body["market"] == "KR"
     assert body["metrics"]["total_trades"] == 1
 
 
 def test_performance_empty_market(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/performance?market=JP")
-    assert resp.status_code == 200
-    assert resp.json()["metrics"]["total_trades"] == 0
+    app = _app(tmp_path)
+    get_performance = _endpoint(app, "/api/performance")
+    body = get_performance(market="JP")
+    assert body["metrics"]["total_trades"] == 0
 
 
 def test_context_layer_all(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/context/L7_REALTIME")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_context_layer = _endpoint(app, "/api/context/{layer}")
+    body = get_context_layer("L7_REALTIME", timeframe=None, limit=100)
     assert body["layer"] == "L7_REALTIME"
     assert body["count"] == 1
 
 
 def test_context_layer_timeframe_filter(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/context/L6_DAILY?timeframe=2026-02-14")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_context_layer = _endpoint(app, "/api/context/{layer}")
+    body = get_context_layer("L6_DAILY", timeframe="2026-02-14", limit=100)
     assert body["count"] == 1
     assert body["entries"][0]["key"] == "scorecard_KR"
 
 
 def test_decisions_endpoint(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/decisions?market=KR")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_decisions = _endpoint(app, "/api/decisions")
+    body = get_decisions(market="KR", limit=50)
     assert body["count"] == 1
     assert body["decisions"][0]["decision_id"] == "d-kr-1"
 
 
 def test_scenarios_active_filters_non_matched(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/scenarios/active?market=KR&date_str=2026-02-14")
-    assert resp.status_code == 200
-    body = resp.json()
+    app = _app(tmp_path)
+    get_active_scenarios = _endpoint(app, "/api/scenarios/active")
+    body = get_active_scenarios(
+        market="KR",
+        date_str=datetime.now(UTC).date().isoformat(),
+        limit=50,
+    )
     assert body["count"] == 1
     assert body["matches"][0]["stock_code"] == "005930"
 
 
 def test_scenarios_active_empty_when_no_matches(tmp_path: Path) -> None:
-    client = _client(tmp_path)
-    resp = client.get("/api/scenarios/active?market=US&date_str=2026-02-14")
-    assert resp.status_code == 200
-    assert resp.json()["count"] == 0
+    app = _app(tmp_path)
+    get_active_scenarios = _endpoint(app, "/api/scenarios/active")
+    body = get_active_scenarios(market="US", date_str="2026-02-14", limit=50)
+    assert body["count"] == 0

tests/test_db.py

@@ -0,0 +1,60 @@
+"""Tests for database helper functions."""
+
+from src.db import get_open_position, init_db, log_trade
+
+
+def test_get_open_position_returns_latest_buy() -> None:
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=2,
+        price=70000.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id="d-buy-1",
+    )
+
+    position = get_open_position(conn, "005930", "KR")
+    assert position is not None
+    assert position["decision_id"] == "d-buy-1"
+    assert position["price"] == 70000.0
+    assert position["quantity"] == 2
+
+
+def test_get_open_position_returns_none_when_latest_is_sell() -> None:
+    conn = init_db(":memory:")
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=70000.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id="d-buy-1",
+    )
+    log_trade(
+        conn=conn,
+        stock_code="005930",
+        action="SELL",
+        confidence=95,
+        rationale="exit",
+        quantity=1,
+        price=71000.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id="d-sell-1",
+    )
+
+    assert get_open_position(conn, "005930", "KR") is None
+
+
+def test_get_open_position_returns_none_when_no_trades() -> None:
+    conn = init_db(":memory:")
+    assert get_open_position(conn, "AAPL", "US_NASDAQ") is None

tests/test_main.py

@@ -116,6 +116,7 @@ class TestTradingCycleTelegramIntegration:
                 "output1": {
                     "stck_prpr": "50000",
                     "frgn_ntby_qty": "100",
+                    "prdy_ctrt": "1.23",
                 }
             }
         )
@@ -747,7 +748,7 @@ class TestScenarioEngineIntegration:
         broker = MagicMock()
         broker.get_orderbook = AsyncMock(
             return_value={
-                "output1": {"stck_prpr": "50000", "frgn_ntby_qty": "100"}
+                "output1": {"stck_prpr": "50000", "frgn_ntby_qty": "100", "prdy_ctrt": "2.50"}
             }
         )
         broker.get_balance = AsyncMock(
@@ -830,6 +831,7 @@ class TestScenarioEngineIntegration:
         assert market_data["rsi"] == 25.0
         assert market_data["volume_ratio"] == 3.5
         assert market_data["current_price"] == 50000.0
+        assert market_data["price_change_pct"] == 2.5
 
         # Portfolio data should include pnl
         assert "portfolio_pnl_pct" in portfolio_data
@@ -1232,6 +1234,107 @@ async def test_sell_updates_original_buy_decision_outcome() -> None:
     assert updated_buy.outcome_accuracy == 1
 
 
+@pytest.mark.asyncio
+async def test_hold_overridden_to_sell_when_stop_loss_triggered() -> None:
+    """HOLD decision should be overridden to SELL when stop-loss threshold is breached."""
+    db_conn = init_db(":memory:")
+    decision_logger = DecisionLogger(db_conn)
+
+    buy_decision_id = decision_logger.log_decision(
+        stock_code="005930",
+        market="KR",
+        exchange_code="KRX",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        context_snapshot={},
+        input_data={},
+    )
+    log_trade(
+        conn=db_conn,
+        stock_code="005930",
+        action="BUY",
+        confidence=90,
+        rationale="entry",
+        quantity=1,
+        price=100.0,
+        market="KR",
+        exchange_code="KRX",
+        decision_id=buy_decision_id,
+    )
+
+    broker = MagicMock()
+    broker.get_orderbook = AsyncMock(
+        return_value={"output1": {"stck_prpr": "95", "frgn_ntby_qty": "0", "prdy_ctrt": "-5.0"}}
+    )
+    broker.get_balance = AsyncMock(
+        return_value={
+            "output2": [
+                {
+                    "tot_evlu_amt": "100000",
+                    "dnca_tot_amt": "10000",
+                    "pchs_amt_smtl_amt": "90000",
+                }
+            ]
+        }
+    )
+    broker.send_order = AsyncMock(return_value={"msg1": "OK"})
+
+    scenario = StockScenario(
+        condition=StockCondition(rsi_below=30),
+        action=ScenarioAction.BUY,
+        confidence=88,
+        stop_loss_pct=-2.0,
+        rationale="stop loss policy",
+    )
+    playbook = DayPlaybook(
+        date=date(2026, 2, 8),
+        market="KR",
+        stock_playbooks=[
+            {"stock_code": "005930", "stock_name": "Samsung", "scenarios": [scenario]}
+        ],
+    )
+    engine = MagicMock(spec=ScenarioEngine)
+    engine.evaluate = MagicMock(return_value=_make_hold_match())
+
+    market = MagicMock()
+    market.name = "Korea"
+    market.code = "KR"
+    market.exchange_code = "KRX"
+    market.is_domestic = True
+
+    telegram = MagicMock()
+    telegram.notify_trade_execution = AsyncMock()
+    telegram.notify_fat_finger = AsyncMock()
+    telegram.notify_circuit_breaker = AsyncMock()
+    telegram.notify_scenario_matched = AsyncMock()
+
+    await trading_cycle(
+        broker=broker,
+        overseas_broker=MagicMock(),
+        scenario_engine=engine,
+        playbook=playbook,
+        risk=MagicMock(),
+        db_conn=db_conn,
+        decision_logger=decision_logger,
+        context_store=MagicMock(
+            get_latest_timeframe=MagicMock(return_value=None),
+            set_context=MagicMock(),
+        ),
+        criticality_assessor=MagicMock(
+            assess_market_conditions=MagicMock(return_value=MagicMock(value="NORMAL")),
+            get_timeout=MagicMock(return_value=5.0),
+        ),
+        telegram=telegram,
+        market=market,
+        stock_code="005930",
+        scan_candidates={},
+    )
+
+    broker.send_order.assert_called_once()
+    assert broker.send_order.call_args.kwargs["order_type"] == "SELL"
+
+
 @pytest.mark.asyncio
 async def test_handle_market_close_runs_daily_review_flow() -> None:
     """Market close should aggregate, create scorecard, lessons, and notify."""
@@ -1427,7 +1530,7 @@ async def test_run_evolution_loop_notifies_when_pr_generated() -> None:
     await _run_evolution_loop(
         evolution_optimizer=optimizer,
         telegram=telegram,
-        market_code="US",
+        market_code="US_NASDAQ",
         market_date="2026-02-14",
     )
 
@@ -1451,7 +1554,7 @@ async def test_run_evolution_loop_notification_error_is_ignored() -> None:
     await _run_evolution_loop(
         evolution_optimizer=optimizer,
         telegram=telegram,
-        market_code="US",
+        market_code="US_NYSE",
         market_date="2026-02-14",
     )
 

tests/test_market_schedule.py

@@ -7,6 +7,7 @@ import pytest
 
 from src.markets.schedule import (
     MARKETS,
+    expand_market_codes,
     get_next_market_open,
     get_open_markets,
     is_market_open,
@@ -199,3 +200,28 @@ class TestGetNextMarketOpen:
             enabled_markets=["INVALID", "KR"], now=test_time
         )
         assert market.code == "KR"
+
+
+class TestExpandMarketCodes:
+    """Test shorthand market expansion."""
+
+    def test_expand_us_shorthand(self) -> None:
+        assert expand_market_codes(["US"]) == ["US_NASDAQ", "US_NYSE", "US_AMEX"]
+
+    def test_expand_cn_shorthand(self) -> None:
+        assert expand_market_codes(["CN"]) == ["CN_SHA", "CN_SZA"]
+
+    def test_expand_vn_shorthand(self) -> None:
+        assert expand_market_codes(["VN"]) == ["VN_HAN", "VN_HCM"]
+
+    def test_expand_mixed_codes(self) -> None:
+        assert expand_market_codes(["KR", "US", "JP"]) == [
+            "KR",
+            "US_NASDAQ",
+            "US_NYSE",
+            "US_AMEX",
+            "JP",
+        ]
+
+    def test_expand_preserves_unknown_code(self) -> None:
+        assert expand_market_codes(["KR", "UNKNOWN"]) == ["KR", "UNKNOWN"]

tests/test_telegram_commands.py

@@ -682,6 +682,10 @@ class TestBasicCommands:
                 "/help - Show available commands\n"
                 "/status - Trading status (mode, markets, P&L)\n"
                 "/positions - Current holdings\n"
+                "/report - Daily summary report\n"
+                "/scenarios - Today's playbook scenarios\n"
+                "/review - Recent scorecards\n"
+                "/dashboard - Dashboard URL/status\n"
                 "/stop - Pause trading\n"
                 "/resume - Resume trading"
             )
@@ -707,10 +711,106 @@ class TestBasicCommands:
             assert "/help" in payload["text"]
             assert "/status" in payload["text"]
             assert "/positions" in payload["text"]
+            assert "/report" in payload["text"]
+            assert "/scenarios" in payload["text"]
+            assert "/review" in payload["text"]
+            assert "/dashboard" in payload["text"]
             assert "/stop" in payload["text"]
             assert "/resume" in payload["text"]
 
 
+class TestExtendedCommands:
+    """Test additional bot commands."""
+
+    @pytest.mark.asyncio
+    async def test_report_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_report() -> None:
+            await client.send_message("<b>📈 Daily Report</b>\n\nTrades: 1")
+
+        handler.register_command("report", mock_report)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/report"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Daily Report" in payload["text"]
+
+    @pytest.mark.asyncio
+    async def test_scenarios_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_scenarios() -> None:
+            await client.send_message("<b>🧠 Today's Scenarios</b>\n\n- AAPL: BUY (85)")
+
+        handler.register_command("scenarios", mock_scenarios)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/scenarios"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Today's Scenarios" in payload["text"]
+
+    @pytest.mark.asyncio
+    async def test_review_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_review() -> None:
+            await client.send_message("<b>📝 Recent Reviews</b>\n\n- 2026-02-14 KR")
+
+        handler.register_command("review", mock_review)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/review"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Recent Reviews" in payload["text"]
+
+    @pytest.mark.asyncio
+    async def test_dashboard_command(self) -> None:
+        client = TelegramClient(bot_token="123:abc", chat_id="456", enabled=True)
+        handler = TelegramCommandHandler(client)
+
+        mock_resp = AsyncMock()
+        mock_resp.status = 200
+        mock_resp.__aenter__ = AsyncMock(return_value=mock_resp)
+        mock_resp.__aexit__ = AsyncMock(return_value=False)
+
+        async def mock_dashboard() -> None:
+            await client.send_message("<b>🖥️ Dashboard</b>\n\nURL: http://127.0.0.1:8080")
+
+        handler.register_command("dashboard", mock_dashboard)
+
+        with patch("aiohttp.ClientSession.post", return_value=mock_resp) as mock_post:
+            await handler._handle_update(
+                {"update_id": 1, "message": {"chat": {"id": 456}, "text": "/dashboard"}}
+            )
+            payload = mock_post.call_args.kwargs["json"]
+            assert "Dashboard" in payload["text"]
+
+
 class TestGetUpdates:
     """Test getUpdates API interaction."""