# AI Agent Instructions for Trading Bot v4

## Mission & Financial Goals

**Primary Objective:** Build wealth systematically from $106 → $100,000+ through algorithmic trading

**Current Phase:** Phase 1 - Survival & Proof (Nov 2025 - Jan 2026)
- **Current Capital:** $97.55 USDC (zero debt, 100% health)
- **Starting Capital:** $106 (Nov 2025)
- **Target:** $2,500 by end of Phase 1 (Month 2.5)
- **Strategy:** Aggressive compounding, 0 withdrawals
- **Position Sizing:** 100% of free collateral (~$97 at 15x leverage = ~$1,463 notional)
- **Risk Tolerance:** EXTREME - This is recovery/proof-of-concept mode
- **Win Target:** 20-30% monthly returns to reach $2,500
- **Trades Executed:** 161 (as of Nov 12, 2025)

**Why This Matters for AI Agents:**
- Every dollar counts at this stage - optimize for profitability, not just safety
- User needs this system to work for long-term financial goals ($300-500/month withdrawals starting Month 3)
- No changes that reduce win rate unless they improve profit factor
- System must prove itself before scaling (see `TRADING_GOALS.md` for full 8-phase roadmap)

**Key Constraints:**
- Can't afford extended drawdowns (limited capital)
- Must maintain 60%+ win rate to compound effectively
- Quality over quantity - only trade 60+ signal quality scores (lowered from 65 on Nov 12, 2025)
- After 3 consecutive losses, STOP and review system

## 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:** TP2-as-Runner system (CURRENT):
- TP1 at +0.4%: Close configurable % (default 75%, adjustable via `TAKE_PROFIT_1_SIZE_PERCENT`)
- TP2 at +0.7%: **Activates trailing stop** on full remaining % (no position close)
- Runner: Remaining % after TP1 with ATR-based trailing stop (default 25%, configurable)
- **Note:** All UI displays dynamically calculate runner% as `100 - TAKE_PROFIT_1_SIZE_PERCENT`

**Per-Symbol Configuration:** SOL and ETH have independent enable/disable toggles and position sizing:
- `SOLANA_ENABLED`, `SOLANA_POSITION_SIZE`, `SOLANA_LEVERAGE` (defaults: true, 100%, 15x)
- `ETHEREUM_ENABLED`, `ETHEREUM_POSITION_SIZE`, `ETHEREUM_LEVERAGE` (defaults: true, 100%, 1x)
- BTC and other symbols fall back to global settings (`MAX_POSITION_SIZE_USD`, `LEVERAGE`)
- **Priority:** Per-symbol ENV → Market config → Global ENV → Defaults

**Signal Quality System:** Filters trades based on 5 metrics (ATR, ADX, RSI, volumeRatio, pricePosition) scored 0-100. Only trades scoring 60+ are executed (lowered from 65 after data analysis showed 60-64 tier outperformed higher scores). Scores stored in database for future optimization.

**Timeframe-Aware Scoring:** Signal quality thresholds adjust based on timeframe (5min vs daily):
- 5min: ADX 12+ trending (vs 18+ for daily), ATR 0.2-0.7% healthy (vs 0.4%+ for daily)
- Anti-chop filter: -20 points for extreme sideways (ADX <10, ATR <0.25%, Vol <0.9x)
- Pass `timeframe` param to `scoreSignalQuality()` from TradingView alerts (e.g., `timeframe: "5"`)

**MAE/MFE Tracking:** Every trade tracks Maximum Favorable Excursion (best profit %) and Maximum Adverse Excursion (worst loss %) updated every 2s. Used for data-driven optimization of TP/SL levels.

**Manual Trading via Telegram:** Send plain-text messages like `long sol`, `short eth`, `long btc` to open positions instantly (bypasses n8n, calls `/api/trading/execute` directly with preset healthy metrics).

**Re-Entry Analytics System:** Manual trades are validated before execution using fresh TradingView data:
- Market data cached from TradingView signals (5min expiry)
- `/api/analytics/reentry-check` scores re-entry based on fresh metrics + recent performance
- Telegram bot blocks low-quality re-entries unless `--force` flag used
- Uses real TradingView ADX/ATR/RSI when available, falls back to historical data
- Penalty for recent losing trades, bonus for winning streaks

## VERIFICATION MANDATE: Financial Code Requires Proof

**Core Principle:** In trading systems, "working" means "verified with real data", NOT "code looks correct".

**NEVER declare something working without:**
1. Observing actual logs showing expected behavior
2. Verifying database state matches expectations
3. Comparing calculated values to source data
4. Testing with real trades when applicable

### Critical Path Verification Requirements

**Position Manager Changes:**
- [ ] Execute test trade with DRY_RUN=false (small size)
- [ ] Watch docker logs for full TP1 → TP2 → exit cycle
- [ ] SQL query: verify `tp1Hit`, `slMovedToBreakeven`, `currentSize` match Position Manager logs
- [ ] Compare Position Manager tracked size to actual Drift position size
- [ ] Check exit reason matches actual trigger (TP1/TP2/SL/trailing)

**Exit Logic Changes (TP/SL/Trailing):**
- [ ] Log EXPECTED values (TP1 price, SL price after breakeven, trailing stop distance)
- [ ] Log ACTUAL values from Drift position and Position Manager state
- [ ] Verify: Does TP1 hit when price crosses TP1? Does SL move to breakeven?
- [ ] Test: Open position, let it hit TP1, verify 75% closed + SL moved
- [ ] Document: What SHOULD happen vs what ACTUALLY happened

**API Endpoint Changes:**
- [ ] curl test with real payload from TradingView/n8n
- [ ] Check response JSON matches expectations
- [ ] Verify database record created with correct fields
- [ ] Check Telegram notification shows correct values (leverage, size, etc.)
- [ ] SQL query: confirm all fields populated correctly

**Calculation Changes (P&L, Position Sizing, Percentages):**
- [ ] Add console.log for EVERY step of calculation
- [ ] Verify units match (tokens vs USD, percent vs decimal, etc.)
- [ ] SQL query with manual calculation: does code result match hand calculation?
- [ ] Test edge cases: 0%, 100%, negative values, very small/large numbers

**SDK/External Data Integration:**
- [ ] Log raw SDK response to verify assumptions about data format
- [ ] NEVER trust documentation - verify with console.log
- [ ] Example: position.size doc said "USD" but logs showed "tokens"
- [ ] Document actual behavior in Common Pitfalls section

### Red Flags Requiring Extra Verification

**High-Risk Changes:**
- Unit conversions (tokens ↔ USD, percent ↔ decimal)
- State transitions (TP1 hit → move SL to breakeven)
- Configuration precedence (per-symbol vs global vs defaults)
- Display values from complex calculations (leverage, size, P&L)
- Timing-dependent logic (grace periods, cooldowns, race conditions)

**Verification Steps for Each:**
1. **Before declaring working**: Show proof (logs, SQL results, test output)
2. **After deployment**: Monitor first real trade closely, verify behavior
3. **Edge cases**: Test boundary conditions (0, 100%, max leverage, min size)
4. **Regression**: Check that fix didn't break other functionality

### SQL Verification Queries

**After Position Manager changes:**
```sql
-- Verify TP1 detection worked correctly
SELECT 
  symbol, entryPrice, currentSize, realizedPnL,
  tp1Hit, slMovedToBreakeven, exitReason,
  TO_CHAR(createdAt, 'MM-DD HH24:MI') as time
FROM "Trade"
WHERE exitReason IS NULL  -- Open positions
  OR createdAt > NOW() - INTERVAL '1 hour'  -- Recent closes
ORDER BY createdAt DESC
LIMIT 5;

-- Compare Position Manager state to expectations
SELECT configSnapshot->'positionManagerState' as pm_state
FROM "Trade" 
WHERE symbol = 'SOL-PERP' AND exitReason IS NULL;
```

**After calculation changes:**
```sql
-- Verify P&L calculations
SELECT 
  symbol, direction, entryPrice, exitPrice,
  positionSize, realizedPnL,
  -- Manual calculation:
  CASE 
    WHEN direction = 'long' THEN 
      positionSize * ((exitPrice - entryPrice) / entryPrice)
    ELSE 
      positionSize * ((entryPrice - exitPrice) / entryPrice)
  END as expected_pnl,
  -- Difference:
  realizedPnL - CASE 
    WHEN direction = 'long' THEN 
      positionSize * ((exitPrice - entryPrice) / entryPrice)
    ELSE 
      positionSize * ((entryPrice - exitPrice) / entryPrice)
  END as pnl_difference
FROM "Trade"
WHERE exitReason IS NOT NULL
  AND createdAt > NOW() - INTERVAL '24 hours'
ORDER BY createdAt DESC
LIMIT 10;
```

### Example: How Position.size Bug Should Have Been Caught

**What went wrong:**
- Read code: "Looks like it's comparing sizes correctly"
- Declared: "Position Manager is working!"
- Didn't verify with actual trade

**What should have been done:**
```typescript
// In Position Manager monitoring loop - ADD THIS LOGGING:
console.log('🔍 VERIFICATION:', {
  positionSizeRaw: position.size,  // What SDK returns
  positionSizeUSD: position.size * currentPrice,  // Converted to USD
  trackedSizeUSD: trade.currentSize,  // What we're tracking
  ratio: (position.size * currentPrice) / trade.currentSize,
  tp1ShouldTrigger: (position.size * currentPrice) < trade.currentSize * 0.95
})
```

Then observe logs on actual trade:
```
🔍 VERIFICATION: {
  positionSizeRaw: 12.28,  // ← AH! This is SOL tokens, not USD!
  positionSizeUSD: 1950.84,  // ← Correct USD value
  trackedSizeUSD: 1950.00,
  ratio: 1.0004,  // ← Should be near 1.0 when position full
  tp1ShouldTrigger: false  // ← Correct
}
```

**Lesson:** One console.log would have exposed the bug immediately.

### Deployment Checklist

Before marking feature complete:
- [ ] Code review completed
- [ ] Unit tests pass (if applicable)
- [ ] Integration test with real API calls
- [ ] Logs show expected behavior
- [ ] Database state verified with SQL
- [ ] Edge cases tested
- [ ] Documentation updated (including Common Pitfalls if applicable)
- [ ] User notified of what to verify during first real trade

### When to Escalate to User

**Don't say "it's working" if:**
- You haven't observed actual logs showing the expected behavior
- SQL query shows unexpected values
- Test trade behaved differently than expected
- You're unsure about unit conversions or SDK behavior
- Change affects money (position sizing, P&L, exits)

**Instead say:**
- "Code is updated. Need to verify with test trade - watch for [specific log message]"
- "Fixed, but requires verification: check database shows [expected value]"
- "Deployed. First real trade should show [behavior]. If not, there's still a bug."

---

## Critical Components

### 1. Signal Quality Scoring (`lib/trading/signal-quality.ts`)
**Purpose:** Unified quality validation system that scores trading signals 0-100 based on 5 market metrics

**Timeframe-aware thresholds:**
```typescript
scoreSignalQuality({ 
  atr, adx, rsi, volumeRatio, pricePosition, 
  timeframe?: string // "5" for 5min, undefined for higher timeframes
})
```

**5min chart adjustments:**
- ADX healthy range: 12-22 (vs 18-30 for daily)
- ATR healthy range: 0.2-0.7% (vs 0.4%+ for daily)
- Anti-chop filter: -20 points for extreme sideways (ADX <10, ATR <0.25%, Vol <0.9x)

**Price position penalties (all timeframes):**
- Long at 90-95%+ range: -15 to -30 points (chasing highs)
- Short at <5-10% range: -15 to -30 points (chasing lows)
- Prevents flip-flop losses from entering range extremes

**Key behaviors:**
- Returns score 0-100 and detailed breakdown object
- Minimum score 60 required to execute trade
- Called by both `/api/trading/check-risk` and `/api/trading/execute`
- Scores saved to database for post-trade analysis

### 2. 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
- **TP2-as-Runner system**: TP1 (configurable %, default 75%) → TP2 trigger (no close, activate trailing) → Runner (remaining %) with ATR-based trailing stop
- Dynamic SL adjustments: Moves to breakeven after TP1, locks profit at +1.2%
- **On-chain order synchronization:** After TP1 hits, calls `cancelAllOrders()` then `placeExitOrders()` with updated SL price at breakeven (uses `retryWithBackoff()` for rate limit handling)
- **ATR-based trailing stop:** Calculates trail distance as `(atrAtEntry / currentPrice × 100) × trailingStopAtrMultiplier`, clamped between min/max %
- Trailing stop: Activates when TP2 price hit, tracks `peakPrice` and trails dynamically
- 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)
- **Exit reason detection:** Uses trade state flags (`tp1Hit`, `tp2Hit`) and realized P&L to determine exit reason, NOT current price (avoids misclassification when price moves after order fills)
- **Real P&L calculation:** Calculates actual profit based on entry vs exit price, not SDK's potentially incorrect values

### 3. Telegram Bot (`telegram_command_bot.py`)
**Purpose:** Python-based Telegram bot for manual trading commands and position status monitoring

**Manual trade commands via plain text:**
```python
# User sends plain text message (not slash commands)
"long sol"          → Validates via analytics, then opens SOL-PERP long
"short eth"         → Validates via analytics, then opens ETH-PERP short
"long btc --force"  → Skips analytics validation, opens BTC-PERP long immediately
```

**Key behaviors:**
- MessageHandler processes all text messages (not just commands)
- Maps user-friendly symbols (sol, eth, btc) to Drift format (SOL-PERP, etc.)
- **Analytics validation:** Calls `/api/analytics/reentry-check` before execution
  - Blocks trades with score <55 unless `--force` flag used
  - Uses fresh TradingView data (<5min old) when available
  - Falls back to historical metrics with penalty
  - Considers recent trade performance (last 3 trades)
- Calls `/api/trading/execute` directly with preset healthy metrics (ATR=0.45, ADX=32, RSI=58/42)
- Bypasses n8n workflow and TradingView requirements
- 60-second timeout for API calls
- Responds with trade confirmation or analytics rejection message

**Status command:**
```python
/status → Returns JSON of open positions from Drift
```

**Implementation details:**
- Uses `python-telegram-bot` library
- Deployed via `docker-compose.telegram-bot.yml`
- Requires `TELEGRAM_BOT_TOKEN` and `TELEGRAM_CHANNEL_ID` in .env
- API calls to `http://trading-bot:3000/api/trading/execute`

**Drift client integration:**
- 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

### 4. Rate Limit Monitoring (`lib/drift/orders.ts` + `app/api/analytics/rate-limits`)
**Purpose:** Track and analyze Solana RPC rate limiting (429 errors) to prevent silent failures

**Retry mechanism with exponential backoff:**
```typescript
await retryWithBackoff(async () => {
  return await driftClient.cancelOrders(...)
}, maxRetries = 3, baseDelay = 2000)
```

**Database logging:** Three event types in SystemEvent table:
- `rate_limit_hit`: Each 429 error (logged with attempt #, delay, error snippet)
- `rate_limit_recovered`: Successful retry (logged with total time, retry count)
- `rate_limit_exhausted`: Failed after max retries (CRITICAL - order operation failed)

**Analytics endpoint:**
```bash
curl http://localhost:3001/api/analytics/rate-limits
```
Returns: Total hits/recoveries/failures, hourly patterns, recovery times, success rate

**Key behaviors:**
- Only RPC calls wrapped: `cancelAllOrders()`, `placeExitOrders()`, `closePosition()`
- Position Manager 2s loop does NOT make RPC calls (only price checks via Pyth WebSocket)
- Exponential backoff: 2s → 4s → 8s delays on retry
- Logs to both console and database for post-trade analysis

**Monitoring queries:** See `docs/RATE_LIMIT_MONITORING.md` for SQL queries

### 5. 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
- `cancelAllOrders()` - Cancels all reduce-only orders for a market

**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.

**CRITICAL: Drift SDK position.size is BASE ASSET TOKENS, not USD**
The Drift SDK returns `position.size` as token quantity (SOL/ETH/BTC), NOT USD notional:
```typescript
// CORRECT: Convert tokens to USD by multiplying by current price
const positionSizeUSD = Math.abs(position.size) * currentPrice

// WRONG: Using position.size directly as USD (off by 150x+ for SOL!)
const positionSizeUSD = Math.abs(position.size)
```
**This affects Position Manager's TP1/TP2 detection** - if position.size is not converted to USD before comparing to tracked USD values, the system will never detect partial closes correctly. See Common Pitfall #22 for the full bug details and fix applied Nov 12, 2025.

**Solana RPC Rate Limiting with Exponential Backoff**
Solana RPC endpoints return 429 errors under load. Always use retry logic for order operations:
```typescript
export async function retryWithBackoff<T>(
  operation: () => Promise<T>,
  maxRetries: number = 3,
  initialDelay: number = 2000
): Promise<T> {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await operation()
    } catch (error: any) {
      if (error?.message?.includes('429') && attempt < maxRetries - 1) {
        const delay = initialDelay * Math.pow(2, attempt)
        console.log(`⏳ Rate limited, retrying in ${delay/1000}s... (attempt ${attempt + 1}/${maxRetries})`)
        await new Promise(resolve => setTimeout(resolve, delay))
        continue
      }
      throw error
    }
  }
  throw new Error('Max retries exceeded')
}

// Usage in cancelAllOrders
await retryWithBackoff(() => driftClient.cancelOrders(...))
```
Without this, order cancellations fail silently during TP1→breakeven order updates, leaving ghost orders that cause incorrect fills.

**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

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

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

**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
- `createBlockedSignal()` - Save blocked signals for data-driven optimization analysis
- `getRecentBlockedSignals()` - Query recent blocked signals
- `getBlockedSignalsForAnalysis()` - Fetch signals needing price analysis (future automation)

**Important fields:**
- `signalQualityScore` (Int?) - 0-100 score for data-driven optimization
- `signalQualityVersion` (String?) - Tracks which scoring logic was used ('v1', 'v2', 'v3', 'v4')
  - v1: Original logic (price position < 5% threshold)
  - v2: Added volume compensation for low ADX (2025-11-07)
  - v3: Stricter breakdown requirements: positions < 15% require (ADX > 18 AND volume > 1.2x) OR (RSI < 35 for shorts / RSI > 60 for longs)
  - v4: CURRENT - Blocked signals tracking enabled for data-driven threshold optimization (2025-11-11)
  - All new trades tagged with current version for comparative analysis
- `maxFavorableExcursion` / `maxAdverseExcursion` - Track best/worst P&L during trade lifetime
- `maxFavorablePrice` / `maxAdversePrice` - Track prices at MFE/MAE points
- `configSnapshot` (Json) - Stores Position Manager state for crash recovery
- `atr`, `adx`, `rsi`, `volumeRatio`, `pricePosition` - Context metrics from TradingView

**BlockedSignal model fields (NEW):**
- Signal metrics: `atr`, `adx`, `rsi`, `volumeRatio`, `pricePosition`, `timeframe`
- Quality scoring: `signalQualityScore`, `signalQualityVersion`, `scoreBreakdown` (JSON), `minScoreRequired`
- Block tracking: `blockReason` (QUALITY_SCORE_TOO_LOW, COOLDOWN_PERIOD, HOURLY_TRADE_LIMIT, etc.), `blockDetails`
- Future analysis: `priceAfter1/5/15/30Min`, `wouldHitTP1/TP2/SL`, `analysisComplete`
- Automatically saved by check-risk endpoint when signals are blocked
- Enables data-driven optimization: collect 10-20 blocked signals → analyze patterns → adjust thresholds

**Per-symbol functions:**
- `getLastTradeTimeForSymbol(symbol)` - Get last trade time for specific coin (enables per-symbol cooldown)
- Each coin (SOL/ETH/BTC) has independent cooldown timer to avoid missed opportunities

## 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

**Per-symbol position sizing:** Use `getPositionSizeForSymbol(symbol, config)` which returns `{ size, leverage, enabled }`
```typescript
const { size, leverage, enabled } = getPositionSizeForSymbol('SOL-PERP', config)
if (!enabled) {
  return NextResponse.json({ success: false, error: 'Symbol trading disabled' }, { status: 400 })
}
```

**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), **auto-caches market data**
- `/api/trading/check-risk` - Pre-execution validation (duplicate check, quality score, **per-symbol cooldown**, rate limits, **symbol enabled check**, **saves blocked signals automatically**)
- `/api/trading/test` - Test trades from settings UI (no auth required, **respects symbol enable/disable**)
- `/api/trading/close` - Manual position closing (requires symbol normalization)
- `/api/trading/cancel-orders` - **Manual order cleanup** (for stuck/ghost orders after rate limit failures)
- `/api/trading/positions` - Query open positions from Drift
- `/api/trading/market-data` - Webhook for TradingView market data updates (GET for debug, POST for data)
- `/api/settings` - Get/update config (writes to .env file, **includes per-symbol settings**)
- `/api/analytics/last-trade` - Fetch most recent trade details for dashboard (includes quality score)
- `/api/analytics/reentry-check` - **Validate manual re-entry** with fresh TradingView data + recent performance
- `/api/analytics/version-comparison` - Compare performance across signal quality logic versions (v1/v2/v3/v4)
- `/api/restart` - Create restart flag for watch-restart.sh script

## Critical Workflows

### Execute Trade (Production)
```
TradingView alert → n8n Parse Signal Enhanced (extracts metrics + timeframe)
  ↓ /api/trading/check-risk [validates quality score ≥60, checks duplicates, per-symbol cooldown]
  ↓ /api/trading/execute
  ↓ normalize symbol (SOLUSDT → SOL-PERP)
  ↓ getMergedConfig()
  ↓ getPositionSizeForSymbol() [check if symbol enabled + get sizing]
  ↓ openPosition() [MARKET order]
  ↓ calculate dual stop prices if enabled
  ↓ placeExitOrders() [on-chain TP1/TP2/SL orders]
  ↓ scoreSignalQuality({ ..., timeframe }) [compute 0-100 score with timeframe-aware thresholds]
  ↓ 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 MAE/MFE metrics
  ↓ Check emergency stop (-2%) → closePosition(100%)
  ↓ Check SL hit → closePosition(100%)
  ↓ Check TP1 hit → closePosition(75%), cancelAllOrders(), placeExitOrders() with SL at 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 + MAE/MFE 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"
```

## SQL Analysis Queries

Essential queries for monitoring signal quality and blocked signals. Run via:
```bash
docker exec trading-bot-postgres psql -U postgres -d trading_bot_v4 -c "YOUR_QUERY"
```

### Phase 1: Monitor Data Collection Progress
```sql
-- Check blocked signals count (target: 10-20 for Phase 2)
SELECT COUNT(*) as total_blocked FROM "BlockedSignal";

-- Score distribution of blocked signals
SELECT 
  CASE 
    WHEN signalQualityScore >= 60 THEN '60-64 (Close Call)'
    WHEN signalQualityScore >= 55 THEN '55-59 (Marginal)'
    WHEN signalQualityScore >= 50 THEN '50-54 (Weak)'
    ELSE '0-49 (Very Weak)'
  END as tier,
  COUNT(*) as count,
  ROUND(AVG(signalQualityScore)::numeric, 1) as avg_score
FROM "BlockedSignal"
WHERE blockReason = 'QUALITY_SCORE_TOO_LOW'
GROUP BY tier
ORDER BY MIN(signalQualityScore) DESC;

-- Recent blocked signals with full details
SELECT 
  symbol,
  direction,
  signalQualityScore as score,
  ROUND(adx::numeric, 1) as adx,
  ROUND(atr::numeric, 2) as atr,
  ROUND(pricePosition::numeric, 1) as pos,
  ROUND(volumeRatio::numeric, 2) as vol,
  blockReason,
  TO_CHAR(createdAt, 'MM-DD HH24:MI') as time
FROM "BlockedSignal"
ORDER BY createdAt DESC
LIMIT 10;
```

### Phase 2: Compare Blocked vs Executed Trades
```sql
-- Compare executed trades in 60-69 score range
SELECT 
  signalQualityScore as score,
  COUNT(*) as trades,
  ROUND(AVG(realizedPnL)::numeric, 2) as avg_pnl,
  ROUND(SUM(realizedPnL)::numeric, 2) as total_pnl,
  ROUND(100.0 * SUM(CASE WHEN realizedPnL > 0 THEN 1 ELSE 0 END) / COUNT(*)::numeric, 1) as win_rate
FROM "Trade"
WHERE exitReason IS NOT NULL
  AND signalQualityScore BETWEEN 60 AND 69
GROUP BY signalQualityScore
ORDER BY signalQualityScore;

-- Block reason breakdown
SELECT 
  blockReason,
  COUNT(*) as count,
  ROUND(AVG(signalQualityScore)::numeric, 1) as avg_score
FROM "BlockedSignal"
GROUP BY blockReason
ORDER BY count DESC;
```

### Analyze Specific Patterns
```sql
-- Blocked signals at range extremes (price position)
SELECT 
  direction,
  signalQualityScore as score,
  ROUND(pricePosition::numeric, 1) as pos,
  ROUND(adx::numeric, 1) as adx,
  ROUND(volumeRatio::numeric, 2) as vol,
  symbol,
  TO_CHAR(createdAt, 'MM-DD HH24:MI') as time
FROM "BlockedSignal"
WHERE blockReason = 'QUALITY_SCORE_TOO_LOW'
  AND (pricePosition < 10 OR pricePosition > 90)
ORDER BY signalQualityScore DESC;

-- ADX distribution in blocked signals
SELECT 
  CASE 
    WHEN adx >= 25 THEN 'Strong (25+)'
    WHEN adx >= 20 THEN 'Moderate (20-25)'
    WHEN adx >= 15 THEN 'Weak (15-20)'
    ELSE 'Very Weak (<15)'
  END as adx_tier,
  COUNT(*) as count,
  ROUND(AVG(signalQualityScore)::numeric, 1) as avg_score
FROM "BlockedSignal"
WHERE blockReason = 'QUALITY_SCORE_TOO_LOW'
  AND adx IS NOT NULL
GROUP BY adx_tier
ORDER BY MIN(adx) DESC;
```

**Usage Pattern:**
1. Run "Monitor Data Collection" queries weekly during Phase 1
2. Once 10+ blocked signals collected, run "Compare Blocked vs Executed" queries
3. Use "Analyze Specific Patterns" to identify optimization opportunities
4. Full query reference: `BLOCKED_SIGNALS_TRACKING.md`

## 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. **TP2-as-Runner configuration:** 
   - `takeProfit2SizePercent: 0` means "TP2 activates trailing stop, no position close"
   - This creates runner of remaining % after TP1 (default 25%, configurable via TAKE_PROFIT_1_SIZE_PERCENT)
   - `TAKE_PROFIT_2_PERCENT=0.7` sets TP2 trigger price, `TAKE_PROFIT_2_SIZE_PERCENT` should be 0
   - Settings UI correctly shows "TP2 activates trailing stop" with dynamic runner % calculation

9. **P&L calculation CRITICAL:** Use actual entry vs exit price calculation, not SDK values:
```typescript
const profitPercent = this.calculateProfitPercent(trade.entryPrice, exitPrice, trade.direction)
const actualRealizedPnL = (closedSizeUSD * profitPercent) / 100
trade.realizedPnL += actualRealizedPnL  // NOT: result.realizedPnL from SDK
```

10. **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.

11. **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.

12. **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.

13. **Drift minimum position sizes:** Actual minimums differ from documentation:
    - SOL-PERP: 0.1 SOL (~$5-15 depending on price)
    - ETH-PERP: 0.01 ETH (~$38-40 at $4000/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.

14. **Exit reason detection bug:** Position Manager was using current price to determine exit reason, but on-chain orders filled at a DIFFERENT price in the past. Now uses `trade.tp1Hit` / `trade.tp2Hit` flags and realized P&L to correctly identify whether TP1, TP2, or SL triggered. Prevents profitable trades being mislabeled as "SL" exits.

15. **Per-symbol cooldown:** Cooldown period is per-symbol, NOT global. ETH trade at 10:00 does NOT block SOL trade at 10:01. Each coin (SOL/ETH/BTC) has independent cooldown timer to avoid missing opportunities on different assets.

16. **Timeframe-aware scoring crucial:** Signal quality thresholds MUST adjust for 5min vs higher timeframes:
    - 5min charts naturally have lower ADX (12-22 healthy) and ATR (0.2-0.7% healthy) than daily charts
    - Without timeframe awareness, valid 5min breakouts get blocked as "low quality"
    - Anti-chop filter applies -20 points for extreme sideways regardless of timeframe
    - Always pass `timeframe` parameter from TradingView alerts to `scoreSignalQuality()`

17. **Price position chasing causes flip-flops:** Opening longs at 90%+ range or shorts at <10% range reliably loses money:
    - Database analysis showed overnight flip-flop losses all had price position 9-94% (chasing extremes)
    - These trades had valid ADX (16-18) but entered at worst possible time
    - Quality scoring now penalizes -15 to -30 points for range extremes
    - Prevents rapid reversals when price is already overextended

18. **TradingView ADX minimum for 5min:** Set ADX filter to 15 (not 20+) in TradingView alerts for 5min charts:
    - Higher timeframes can use ADX 20+ for strong trends
    - 5min charts need lower threshold to catch valid breakouts
    - Bot's quality scoring provides second-layer filtering with context-aware metrics
    - Two-stage filtering (TradingView + bot) prevents both overtrading and missing valid signals

19. **Prisma Decimal type handling:** Raw SQL queries return Prisma `Decimal` objects, not plain numbers:
    - Use `any` type for numeric fields in `$queryRaw` results: `total_pnl: any`
    - Convert with `Number()` before returning to frontend: `totalPnL: Number(stat.total_pnl) || 0`
    - Frontend uses `.toFixed()` which doesn't exist on Decimal objects
    - Applies to all aggregations: SUM(), AVG(), ROUND() - all return Decimal types
    - Example: `/api/analytics/version-comparison` converts all numeric fields

20. **ATR-based trailing stop implementation (Nov 11, 2025):** Runner system was using FIXED 0.3% trailing, causing immediate stops:
    - **Problem:** At $168 SOL, 0.3% = $0.50 wiggle room. Trades with +7-9% MFE exited for losses.
    - **Fix:** `trailingDistancePercent = (atrAtEntry / currentPrice * 100) × trailingStopAtrMultiplier`
    - **Config:** `TRAILING_STOP_ATR_MULTIPLIER=1.5`, `MIN=0.25%`, `MAX=0.9%`, `ACTIVATION=0.5%`
    - **Typical improvement:** 0.45% ATR × 1.5 = 0.675% trail ($1.13 vs $0.50 = 2.26x more room)
    - **Fallback:** If `atrAtEntry` unavailable, uses clamped legacy `trailingStopPercent`
    - **Log verification:** Look for "📊 ATR-based trailing: 0.0045 (0.52%) × 1.5x = 0.78%" messages
    - **ActiveTrade interface:** Must include `atrAtEntry?: number` field for calculation
    - See `ATR_TRAILING_STOP_FIX.md` for full details and database analysis

21. **CreateTradeParams interface sync:** When adding new database fields to Trade model, MUST update `CreateTradeParams` interface in `lib/database/trades.ts`:
    - Interface defines what parameters `createTrade()` accepts
    - Must add new field to interface (e.g., `indicatorVersion?: string`)
    - Must add field to Prisma create data object in `createTrade()` function
    - TypeScript build will fail if endpoint passes field not in interface
    - Example: indicatorVersion tracking required 3-file update (execute route.ts, CreateTradeParams interface, createTrade function)

22. **Position.size tokens vs USD bug (CRITICAL - Fixed Nov 12, 2025):**
    - **Symptom:** Position Manager detects false TP1 hits, moves SL to breakeven prematurely
    - **Root Cause:** `lib/drift/client.ts` returns `position.size` as BASE ASSET TOKENS (12.28 SOL), not USD ($1,950)
    - **Bug:** Comparing tokens (12.28) directly to USD ($1,950) → 12.28 < 1,950 × 0.95 = "99.4% reduction" → FALSE TP1!
    - **Fix:** Always convert to USD before comparisons:
    ```typescript
    // In Position Manager (lines 322, 519, 558, 591)
    const positionSizeUSD = Math.abs(position.size) * currentPrice
    
    // Now compare USD to USD
    if (positionSizeUSD < trade.currentSize * 0.95) {
      // Actual 5%+ reduction detected
    }
    ```
    - **Impact:** Without this fix, TP1 never triggers correctly, SL moves at wrong times, runner system fails
    - **Where it matters:** Position Manager, any code querying Drift positions
    - **Database evidence:** Trade showed `tp1Hit: true` when 100% still open, `slMovedToBreakeven: true` prematurely

23. **Leverage display showing global config instead of symbol-specific (Fixed Nov 12, 2025):**
    - **Symptom:** Telegram notifications showing "⚡ Leverage: 10x" when actual position uses 15x or 20x
    - **Root Cause:** API response returning `config.leverage` (global default) instead of symbol-specific value
    - **Fix:** Use actual leverage from `getPositionSizeForSymbol()`:
    ```typescript
    // app/api/trading/execute/route.ts (lines 345, 448, 522, 557)
    const { size, leverage, enabled } = getPositionSizeForSymbol(driftSymbol, config)
    
    // Return symbol-specific leverage
    leverage: leverage,  // NOT: config.leverage
    ```
    - **Impact:** Misleading notifications, user confusion about actual position risk
    - **Hierarchy:** Per-symbol ENV (SOLANA_LEVERAGE) → Market config → Global ENV (LEVERAGE) → Defaults

24. **Indicator version tracking (Nov 12, 2025+):**
    - Database field `indicatorVersion` tracks which TradingView strategy generated the signal
    - **v5:** Buy/Sell Signal strategy (pre-Nov 12)
    - **v6:** HalfTrend + BarColor strategy (Nov 12+)
    - Used for performance comparison between strategies

26. **External closure duplicate updates bug (CRITICAL - Fixed Nov 12, 2025):**
    - **Symptom:** Trades showing 7-8x larger losses than actual ($58 loss when Drift shows $7 loss)
    - **Root Cause:** Position Manager monitoring loop re-processes external closures multiple times before trade removed from activeTrades Map
    - **Bug sequence:**
      1. Trade closed externally (on-chain SL order fills at -$7.98)
      2. Position Manager detects closure: `position === null`
      3. Calculates P&L and calls `updateTradeExit()` → -$7.50 in DB
      4. **BUT:** Trade still in `activeTrades` Map (removal happens after DB update)
      5. Next monitoring loop (2s later) detects closure AGAIN
      6. Accumulates P&L: `previouslyRealized (-$7.50) + runnerRealized (-$7.50) = -$15.00`
      7. Updates database AGAIN → -$15.00 in DB
      8. Repeats 8 times → final -$58.43 (8× the actual loss)
    - **Fix:** Remove trade from `activeTrades` Map BEFORE database update:
    ```typescript
    // BEFORE (BROKEN):
    await updateTradeExit({ ... })
    await this.removeTrade(trade.id)  // Too late! Loop already ran again
    
    // AFTER (FIXED):
    this.activeTrades.delete(trade.id)  // Remove FIRST
    await updateTradeExit({ ... })      // Then update DB
    if (this.activeTrades.size === 0) {
      this.stopMonitoring()
    }
    ```
    - **Impact:** Without this fix, every external closure is recorded 5-8 times with compounding P&L
    - **Root cause:** Async timing issue - `removeTrade()` is async but monitoring loop continues synchronously
    - **Evidence:** Logs showed 8 consecutive "External closure recorded" messages with increasing P&L
    - **Line:** `lib/trading/position-manager.ts` line 493 (external closure detection block)
    - Must update `CreateTradeParams` interface when adding new database fields (see pitfall #21)
    - Analytics endpoint `/api/analytics/version-comparison` compares v5 vs v6 performance

25. **Signal quality threshold adjustment (Nov 12, 2025):**
    - **Lowered from 65 → 60** based on data analysis of 161 trades
    - **Reason:** Score 60-64 tier outperformed higher scores:
      - 60-64: 2 trades, +$45.78 total, 100% WR, +$22.89 avg
      - 65-69: 13 trades, +$28.28 total, 53.8% WR, +$2.18 avg
      - 70-79: 67 trades, +$8.28 total, 44.8% WR (worst performance!)
    - **Paradox:** Higher quality scores don't correlate with better performance in current data
    - **Expected impact:** 2-3 additional trades/week, +$46-69 weekly profit potential
    - **Data collection:** Enables blocked signals at 55-59 range for Phase 2 optimization
    - **Risk:** Small sample size (2 trades) could be outliers, but downside limited
    - SQL analysis showed clear pattern: stricter filtering was blocking profitable setups

## 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: 🎯 🚀 ✅ ❌ 💰 📊 🛡️

## Re-Entry Analytics System (Phase 1)

**Purpose:** Validate manual Telegram trades using fresh TradingView data + recent performance analysis

**Components:**
1. **Market Data Cache** (`lib/trading/market-data-cache.ts`)
   - Singleton service storing TradingView metrics
   - 5-minute expiry on cached data
   - Tracks: ATR, ADX, RSI, volume ratio, price position, timeframe

2. **Market Data Webhook** (`app/api/trading/market-data/route.ts`)
   - Receives TradingView alerts every 1-5 minutes
   - POST: Updates cache with fresh metrics
   - GET: View cached data (debugging)

3. **Re-Entry Check Endpoint** (`app/api/analytics/reentry-check/route.ts`)
   - Validates manual trade requests
   - Uses fresh TradingView data if available (<5min old)
   - Falls back to historical metrics from last trade
   - Scores signal quality + applies performance modifiers:
     - **-20 points** if last 3 trades lost money (avgPnL < -5%)
     - **+10 points** if last 3 trades won (avgPnL > +5%, WR >= 66%)
     - **-5 points** for stale data, **-10 points** for no data
   - Minimum score: 55 (vs 60 for new signals)

4. **Auto-Caching** (`app/api/trading/execute/route.ts`)
   - Every trade signal from TradingView auto-caches metrics
   - Ensures fresh data available for manual re-entries

5. **Telegram Integration** (`telegram_command_bot.py`)
   - Calls `/api/analytics/reentry-check` before executing manual trades
   - Shows data freshness ("✅ FRESH 23s old" vs "⚠️ Historical")
   - Blocks low-quality re-entries unless `--force` flag used
   - Fail-open: Proceeds if analytics check fails

**User Flow:**
```
User: "long sol"
  ↓ Check cache for SOL-PERP
  ↓ Fresh data? → Use real TradingView metrics
  ↓ Stale/missing? → Use historical + penalty
  ↓ Score quality + recent performance
  ↓ Score >= 55? → Execute
  ↓ Score < 55? → Block (unless --force)
```

**TradingView Setup:**
Create alerts that fire every 1-5 minutes with this webhook message:
```json
{
  "action": "market_data",
  "symbol": "{{ticker}}",
  "timeframe": "{{interval}}",
  "atr": {{ta.atr(14)}},
  "adx": {{ta.dmi(14, 14)}},
  "rsi": {{ta.rsi(14)}},
  "volumeRatio": {{volume / ta.sma(volume, 20)}},
  "pricePosition": {{(close - ta.lowest(low, 100)) / (ta.highest(high, 100) - ta.lowest(low, 100)) * 100}},
  "currentPrice": {{close}}
}
```

Webhook URL: `https://your-domain.com/api/trading/market-data`

## Per-Symbol Trading Controls

**Purpose:** Independent enable/disable toggles and position sizing for SOL and ETH to support different trading strategies (e.g., ETH for data collection at minimal size, SOL for profit generation).

**Configuration Priority:**
1. **Per-symbol ENV vars** (highest priority)
   - `SOLANA_ENABLED`, `SOLANA_POSITION_SIZE`, `SOLANA_LEVERAGE`
   - `ETHEREUM_ENABLED`, `ETHEREUM_POSITION_SIZE`, `ETHEREUM_LEVERAGE`
2. **Market-specific config** (from `MARKET_CONFIGS` in config/trading.ts)
3. **Global ENV vars** (fallback for BTC and other symbols)
   - `MAX_POSITION_SIZE_USD`, `LEVERAGE`
4. **Default config** (lowest priority)

**Settings UI:** `app/settings/page.tsx` has dedicated sections:
- 💎 Solana section: Toggle + position size + leverage + risk calculator
- ⚡ Ethereum section: Toggle + position size + leverage + risk calculator
- 💰 Global fallback: For BTC-PERP and future symbols

**Example usage:**
```typescript
// In execute/test endpoints
const { size, leverage, enabled } = getPositionSizeForSymbol(driftSymbol, config)
if (!enabled) {
  return NextResponse.json({
    success: false,
    error: 'Symbol trading disabled'
  }, { status: 400 })
}
```

**Test buttons:** Settings UI has symbol-specific test buttons:
- 💎 Test SOL LONG/SHORT (disabled when `SOLANA_ENABLED=false`)
- ⚡ Test ETH LONG/SHORT (disabled when `ETHEREUM_ENABLED=false`)

## 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, ensure timeframe-aware thresholds are synchronized
7. **Exit strategy changes:** Modify Position Manager logic + update on-chain order placement in `placeExitOrders()`
8. **TradingView alert changes:** Ensure alerts pass `timeframe` field (e.g., `"timeframe": "5"`) to enable proper signal quality scoring
9. **Position Manager changes:** ALWAYS execute test trade after deployment
   - Use `/api/trading/test` endpoint or Telegram `long sol --force`
   - Monitor `docker logs -f trading-bot-v4` for full cycle
   - Verify TP1 hit → 75% close → SL moved to breakeven
   - SQL: Check `tp1Hit`, `slMovedToBreakeven`, `currentSize` in Trade table
   - Compare: Position Manager logs vs actual Drift position size
10. **Calculation changes:** Add verbose logging and verify with SQL
    - Log every intermediate step, especially unit conversions
    - Never assume SDK data format - log raw values to verify
    - SQL query with manual calculation to compare results
    - Test boundary cases: 0%, 100%, min/max values

## Development Roadmap

**Current Status (Nov 12, 2025):**
- **161 trades executed** with quality scores and MAE/MFE tracking
- **Capital:** $97.55 USDC at 100% health (zero debt, all USDC collateral)
- **Leverage:** 15x SOL (reduced from 20x for safer liquidation cushion)
- **Three active optimization initiatives** in data collection phase:
  1. **Signal Quality:** 0/20 blocked signals collected → need 10-20 for analysis
  2. **Position Scaling:** 161 v5 trades, collecting v6 data → need 50+ v6 trades
  3. **ATR-based TP:** 1/50 trades with ATR data → need 50 for validation
- **Expected combined impact:** 35-40% P&L improvement when all three optimizations complete
- **Master roadmap:** See `OPTIMIZATION_MASTER_ROADMAP.md` for consolidated view

See `SIGNAL_QUALITY_OPTIMIZATION_ROADMAP.md` for systematic signal quality improvements:
- **Phase 1 (🔄 IN PROGRESS):** Collect 10-20 blocked signals with quality scores (1-2 weeks)
- **Phase 2 (🔜 NEXT):** Analyze patterns and make data-driven threshold decisions
- **Phase 3 (🎯 FUTURE):** Implement dual-threshold system or other optimizations based on data
- **Phase 4 (🤖 FUTURE):** Automated price analysis for blocked signals
- **Phase 5 (🧠 DISTANT):** ML-based scoring weight optimization

See `POSITION_SCALING_ROADMAP.md` for planned position management optimizations:
- **Phase 1 (✅ COMPLETE):** 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 (✅ COMPLETE):** TP2-as-runner system implemented - configurable runner (default 25%, adjustable via TAKE_PROFIT_1_SIZE_PERCENT) with ATR-based trailing stop
- **Phase 6:** ML-based exit prediction (future)

**Recent Implementation:** TP2-as-runner system provides 5x larger runner (default 25% vs old 5%) for better profit capture on extended moves. When TP2 price is hit, trailing stop activates on full remaining position instead of closing partial amount. Runner size is configurable (100% - TP1 close %).

**Blocked Signals Tracking (Nov 11, 2025):** System now automatically saves all blocked signals to database for data-driven optimization. See `BLOCKED_SIGNALS_TRACKING.md` for SQL queries and analysis workflows.

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

**Signal Quality Version Tracking:** Database tracks `signalQualityVersion` field to compare algorithm performance:
- Analytics dashboard shows version comparison: trades, win rate, P&L, extreme position stats
- v4 (current) includes blocked signals tracking for data-driven optimization
- Focus on extreme positions (< 15% range) - v3 aimed to reduce losses from weak ADX entries
- SQL queries in `docs/analysis/SIGNAL_QUALITY_VERSION_ANALYSIS.sql` for deep-dive analysis
- Need 20+ trades per version before meaningful comparison

**Financial Roadmap Integration:**
All technical improvements must align with current phase objectives (see top of document):
- **Phase 1 (CURRENT):** Prove system works, compound aggressively, 60%+ win rate mandatory
- **Phase 2-3:** Transition to sustainable growth while funding withdrawals
- **Phase 4+:** Scale capital while reducing risk progressively
- See `TRADING_GOALS.md` for complete 8-phase plan ($106 → $1M+)
- SQL queries in `docs/analysis/SIGNAL_QUALITY_VERSION_ANALYSIS.sql` for deep-dive analysis
- Need 20+ trades per version before meaningful comparison

**Blocked Signals Analysis:** See `BLOCKED_SIGNALS_TRACKING.md` for:
- SQL queries to analyze blocked signal patterns
- Score distribution and metric analysis
- Comparison with executed trades at similar quality levels
- Future automation of price tracking (would TP1/TP2/SL have hit?)

## 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.