# AI Agent Instructions for Trading Bot v4

## Architecture Overview

**Type:** Autonomous cryptocurrency trading bot with Next.js 15 frontend + Solana/Drift Protocol backend

**Data Flow:** TradingView → n8n webhook → Next.js API → Drift Protocol (Solana DEX) → Real-time monitoring → Auto-exit

**Key Design Principle:** Dual-layer redundancy - every trade has both on-chain orders (Drift) AND software monitoring (Position Manager) as backup.

**Exit Strategy:** Three-tier scaling system:
- TP1 at +1.5%: Close 75% (configurable via `TAKE_PROFIT_1_SIZE_PERCENT`)
- TP2 at +3.0%: Close 80% of remaining = 20% total (configurable via `TAKE_PROFIT_2_SIZE_PERCENT`)
- Runner: 5% remaining with 0.3% trailing stop (configurable via `TRAILING_STOP_PERCENT`)

**Signal Quality System:** Filters trades based on 5 metrics (ATR, ADX, RSI, volumeRatio, pricePosition) scored 0-100. Only trades scoring 60+ are executed. Scores stored in database for future optimization.

## Critical Components

### 1. Position Manager (`lib/trading/position-manager.ts`)
**Purpose:** Software-based monitoring loop that checks prices every 2 seconds and closes positions via market orders

**Singleton pattern:** Always use `getInitializedPositionManager()` - never instantiate directly
```typescript
const positionManager = await getInitializedPositionManager()
await positionManager.addTrade(activeTrade)
```

**Key behaviors:**
- Tracks `ActiveTrade` objects in a Map
- Three-tier exits: TP1 (75%), TP2 (80% of remaining), Runner (with trailing stop)
- Dynamic SL adjustments: Moves to breakeven after TP1, locks profit at +1.2%
- Trailing stop: Activates after TP2, tracks `peakPrice` and trails by configured %
- Closes positions via `closePosition()` market orders when targets hit
- Acts as backup if on-chain orders don't fill
- State persistence: Saves to database, restores on restart via `configSnapshot.positionManagerState`
- **Grace period for new trades:** Skips "external closure" detection for positions <30 seconds old (Drift positions take 5-10s to propagate)

### 2. Drift Client (`lib/drift/client.ts`)
**Purpose:** Solana/Drift Protocol SDK wrapper for order execution

**Singleton pattern:** Use `initializeDriftService()` and `getDriftService()` - maintains single connection
```typescript
const driftService = await initializeDriftService()
const health = await driftService.getAccountHealth()
```

**Wallet handling:** Supports both JSON array `[91,24,...]` and base58 string formats from Phantom wallet

### 3. Order Placement (`lib/drift/orders.ts`)
**Critical functions:** 
- `openPosition()` - Opens market position with transaction confirmation
- `closePosition()` - Closes position with transaction confirmation
- `placeExitOrders()` - Places TP/SL orders on-chain

**CRITICAL: Transaction Confirmation Pattern**
Both `openPosition()` and `closePosition()` MUST confirm transactions on-chain:
```typescript
const txSig = await driftClient.placePerpOrder(orderParams)
console.log('⏳ Confirming transaction on-chain...')
const connection = driftService.getConnection()
const confirmation = await connection.confirmTransaction(txSig, 'confirmed')

if (confirmation.value.err) {
  throw new Error(`Transaction failed: ${JSON.stringify(confirmation.value.err)}`)
}
console.log('✅ Transaction confirmed on-chain')
```
Without this, the SDK returns signatures for transactions that never execute, causing phantom trades/closes.

**Dual Stop System** (USE_DUAL_STOPS=true):
```typescript
// Soft stop: TRIGGER_LIMIT at -1.5% (avoids wicks)
// Hard stop: TRIGGER_MARKET at -2.5% (guarantees exit)
```

**Order types:**
- Entry: MARKET (immediate execution)
- TP1/TP2: LIMIT reduce-only orders
- Soft SL: TRIGGER_LIMIT reduce-only
- Hard SL: TRIGGER_MARKET reduce-only

### 4. Database (`lib/database/trades.ts` + `prisma/schema.prisma`)
**Purpose:** PostgreSQL via Prisma ORM for trade history and analytics

**Models:** Trade, PriceUpdate, SystemEvent, DailyStats

**Singleton pattern:** Use `getPrismaClient()` - never instantiate PrismaClient directly

**Key functions:**
- `createTrade()` - Save trade after execution (includes dual stop TX signatures + signalQualityScore)
- `updateTradeExit()` - Record exit with P&L
- `addPriceUpdate()` - Track price movements (called by Position Manager)
- `getTradeStats()` - Win rate, profit factor, avg win/loss
- `getLastTrade()` - Fetch most recent trade for analytics dashboard

**Important fields:**
- `signalQualityScore` (Int?) - 0-100 score for data-driven optimization
- `maxFavorableExcursion` / `maxAdverseExcursion` - Track best/worst P&L during trade lifetime
- `configSnapshot` (Json) - Stores Position Manager state for crash recovery
- `atr`, `adx`, `rsi`, `volumeRatio`, `pricePosition` - Context metrics from TradingView

## Configuration System

**Three-layer merge:**
1. `DEFAULT_TRADING_CONFIG` (config/trading.ts)
2. Environment variables (.env) via `getConfigFromEnv()`
3. Runtime overrides via `getMergedConfig(overrides)`

**Always use:** `getMergedConfig()` to get final config - never read env vars directly in business logic

**Symbol normalization:** TradingView sends "SOLUSDT" → must convert to "SOL-PERP" for Drift
```typescript
const driftSymbol = normalizeTradingViewSymbol(body.symbol)
```

## API Endpoints Architecture

**Authentication:** All `/api/trading/*` endpoints (except `/test`) require `Authorization: Bearer API_SECRET_KEY`

**Pattern:** Each endpoint follows same flow:
1. Auth check
2. Get config via `getMergedConfig()`
3. Initialize Drift service
4. Check account health
5. Execute operation
6. Save to database
7. Add to Position Manager if applicable

**Key endpoints:**
- `/api/trading/execute` - Main entry point from n8n (production, requires auth)
- `/api/trading/check-risk` - Pre-execution validation (duplicate check, quality score, rate limits)
- `/api/trading/test` - Test trades from settings UI (no auth required)
- `/api/trading/close` - Manual position closing
- `/api/trading/positions` - Query open positions from Drift
- `/api/settings` - Get/update config (writes to .env file)
- `/api/analytics/last-trade` - Fetch most recent trade details for dashboard
- `/api/restart` - Create restart flag for watch-restart.sh script

## Critical Workflows

### Execute Trade (Production)
```
TradingView alert → n8n Parse Signal Enhanced (extracts metrics)
  ↓ /api/trading/check-risk [validates quality score ≥60, checks duplicates]
  ↓ /api/trading/execute
  ↓ normalize symbol (SOLUSDT → SOL-PERP)
  ↓ getMergedConfig()
  ↓ openPosition() [MARKET order]
  ↓ calculate dual stop prices if enabled
  ↓ placeExitOrders() [on-chain TP1/TP2/SL orders]
  ↓ calculateQualityScore() [compute 0-100 score from metrics]
  ↓ createTrade() [save to database with signalQualityScore]
  ↓ positionManager.addTrade() [start monitoring]
```

### Position Monitoring Loop
```
Position Manager every 2s:
  ↓ Verify on-chain position still exists (detect external closures)
  ↓ getPythPriceMonitor().getLatestPrice()
  ↓ Calculate current P&L and update peakPrice
  ↓ Check emergency stop (-2%) → closePosition(100%)
  ↓ Check SL hit → closePosition(100%)
  ↓ Check TP1 hit → closePosition(75%), move SL to breakeven
  ↓ Check profit lock trigger (+1.2%) → move SL to +configured%
  ↓ Check TP2 hit → closePosition(80% of remaining), activate runner
  ↓ Check trailing stop (if runner active) → adjust SL dynamically based on peakPrice
  ↓ addPriceUpdate() [save to database every N checks]
  ↓ saveTradeState() [persist Position Manager state for crash recovery]
```

### Settings Update
```
Web UI → /api/settings POST
  ↓ Validate new settings
  ↓ Write to .env file using string replacement
  ↓ Return success
  ↓ User clicks "Restart Bot" → /api/restart
  ↓ Creates /tmp/trading-bot-restart.flag
  ↓ watch-restart.sh detects flag
  ↓ Executes: docker restart trading-bot-v4
```

## Docker Context

**Multi-stage build:** deps → builder → runner (Node 20 Alpine)

**Critical Dockerfile steps:**
1. Install deps with `npm install --production`
2. Copy source and `npx prisma generate` (MUST happen before build)
3. `npm run build` (Next.js standalone output)
4. Runner stage copies standalone + static + node_modules + Prisma client

**Container networking:**
- External: `trading-bot-v4` on port 3001
- Internal: Next.js on port 3000
- Database: `trading-bot-postgres` on 172.28.0.0/16 network

**DATABASE_URL caveat:** Use `trading-bot-postgres` (container name) in .env for runtime, but `localhost:5432` for Prisma CLI migrations from host

## Project-Specific Patterns

### 1. Singleton Services
Never create multiple instances - always use getter functions:
```typescript
const driftService = await initializeDriftService() // NOT: new DriftService()
const positionManager = getPositionManager()        // NOT: new PositionManager()
const prisma = getPrismaClient()                     // NOT: new PrismaClient()
```

### 2. Price Calculations
Direction matters for long vs short:
```typescript
function calculatePrice(entry: number, percent: number, direction: 'long' | 'short') {
  if (direction === 'long') {
    return entry * (1 + percent / 100)  // Long: +1% = higher price
  } else {
    return entry * (1 - percent / 100)  // Short: +1% = lower price
  }
}
```

### 3. Error Handling
Database failures should not fail trades - always wrap in try/catch:
```typescript
try {
  await createTrade(params)
  console.log('💾 Trade saved to database')
} catch (dbError) {
  console.error('❌ Failed to save trade:', dbError)
  // Don't fail the trade if database save fails
}
```

### 4. Reduce-Only Orders
All exit orders MUST be reduce-only (can only close, not open positions):
```typescript
const orderParams = {
  reduceOnly: true,  // CRITICAL for TP/SL orders
  // ... other params
}
```

## Testing Commands

```bash
# Local development
npm run dev

# Build production
npm run build && npm start

# Docker build and restart
docker compose build trading-bot
docker compose up -d --force-recreate trading-bot
docker logs -f trading-bot-v4

# Database operations
npx prisma generate                                    # Generate client
DATABASE_URL="postgresql://...@localhost:5432/..." npx prisma migrate dev
docker exec trading-bot-postgres psql -U postgres -d trading_bot_v4 -c "\dt"

# Test trade from UI
# Go to http://localhost:3001/settings
# Click "Test LONG" or "Test SHORT"
```

## Common Pitfalls

1. **Prisma not generated in Docker:** Must run `npx prisma generate` in Dockerfile BEFORE `npm run build`

2. **Wrong DATABASE_URL:** Container runtime needs `trading-bot-postgres`, Prisma CLI from host needs `localhost:5432`

3. **Symbol format mismatch:** Always normalize with `normalizeTradingViewSymbol()` before calling Drift (applies to ALL endpoints including `/api/trading/close`)

4. **Missing reduce-only flag:** Exit orders without `reduceOnly: true` can accidentally open new positions

5. **Singleton violations:** Creating multiple DriftClient or Position Manager instances causes connection/state issues

6. **Type errors with Prisma:** The Trade type from Prisma is only available AFTER `npx prisma generate` - use explicit types or `// @ts-ignore` carefully

7. **Quality score duplication:** Signal quality calculation exists in BOTH `check-risk` and `execute` endpoints - keep logic synchronized

8. **Runner configuration confusion:** 
   - `TAKE_PROFIT_1_SIZE_PERCENT=75` means "close 75% at TP1" (not "keep 75%")
   - `TAKE_PROFIT_2_SIZE_PERCENT=80` means "close 80% of REMAINING" (not of original)
   - Actual runner size = (100 - TP1%) × (100 - TP2%) / 100 = 5% with defaults

9. **Transaction confirmation CRITICAL:** Both `openPosition()` AND `closePosition()` MUST call `connection.confirmTransaction()` after `placePerpOrder()`. Without this, the SDK returns transaction signatures that aren't confirmed on-chain, causing "phantom trades" or "phantom closes". Always check `confirmation.value.err` before proceeding.

10. **Execution order matters:** When creating trades via API endpoints, the order MUST be:
    1. Open position + place exit orders
    2. Save to database (`createTrade()`)
    3. Add to Position Manager (`positionManager.addTrade()`)
    
    If Position Manager is added before database save, race conditions occur where monitoring checks before the trade exists in DB.

11. **New trade grace period:** Position Manager skips "external closure" detection for trades <30 seconds old because Drift positions take 5-10 seconds to propagate after opening. Without this grace period, new positions are immediately detected as "closed externally" and cancelled.

12. **Drift minimum position sizes:** Actual minimums differ from documentation:
    - SOL-PERP: 0.1 SOL (~$5-15 depending on price)
    - ETH-PERP: 0.002 ETH (~$7-8 at $4000/ETH) - NOT 0.01 ETH
    - BTC-PERP: 0.0001 BTC (~$10-12 at $100k/BTC)
    
    Always calculate: `minOrderSize × currentPrice` must exceed Drift's $4 minimum. Add buffer for price movement.

## File Conventions

- **API routes:** `app/api/[feature]/[action]/route.ts` (Next.js 15 App Router)
- **Services:** `lib/[service]/[module].ts` (drift, pyth, trading, database)
- **Config:** Single source in `config/trading.ts` with env merging
- **Types:** Define interfaces in same file as implementation (not separate types directory)
- **Console logs:** Use emojis for visual scanning: 🎯 🚀 ✅ ❌ 💰 📊 🛡️

## When Making Changes

1. **Adding new config:** Update DEFAULT_TRADING_CONFIG + getConfigFromEnv() + .env file
2. **Adding database fields:** Update prisma/schema.prisma → `npx prisma migrate dev` → `npx prisma generate` → rebuild Docker
3. **Changing order logic:** Test with DRY_RUN=true first, use small position sizes ($10)
4. **API endpoint changes:** Update both endpoint + corresponding n8n workflow JSON (Check Risk and Execute Trade nodes)
5. **Docker changes:** Rebuild with `docker compose build trading-bot` then restart container
6. **Modifying quality score logic:** Update BOTH `/api/trading/check-risk` and `/api/trading/execute` endpoints
7. **Exit strategy changes:** Modify Position Manager logic + update on-chain order placement in `placeExitOrders()`

## Development Roadmap

See `POSITION_SCALING_ROADMAP.md` for planned optimizations:
- **Phase 1 (CURRENT):** Collect data with quality scores (20-50 trades needed)
- **Phase 2:** ATR-based dynamic targets (adapt to volatility)
- **Phase 3:** Signal quality-based scaling (high quality = larger runners)
- **Phase 4:** Direction-based optimization (shorts vs longs have different performance)
- **Phase 5:** Optimize runner size (5% → 10-25%) and trailing stop (0.3% fixed → ATR-based)
- **Phase 6:** ML-based exit prediction (future)

**Data-driven approach:** Each phase requires validation through SQL analysis before implementation. No premature optimization.

## Integration Points

- **n8n:** Expects exact response format from `/api/trading/execute` (see n8n-complete-workflow.json)
- **Drift Protocol:** Uses SDK v2.75.0 - check docs at docs.drift.trade for API changes
- **Pyth Network:** WebSocket + HTTP fallback for price feeds (handles reconnection)
- **PostgreSQL:** Version 16-alpine, must be running before bot starts

---

**Key Mental Model:** Think of this as two parallel systems (on-chain orders + software monitoring) working together. The Position Manager is the "backup brain" that constantly watches and acts if on-chain orders fail. Both write to the same database for complete trade history.