**Documentation Structure:** - Created docs/ subdirectory organization (analysis/, architecture/, bugs/, cluster/, deployments/, roadmaps/, setup/, archived/) - Moved 68 root markdown files to appropriate categories - Root directory now clean (only README.md remains) - Total: 83 markdown files now organized by purpose **New Content:** - Added comprehensive Environment Variable Reference to copilot-instructions.md - 100+ ENV variables documented with types, defaults, purpose, notes - Organized by category: Required (Drift/RPC/Pyth), Trading Config (quality/ leverage/sizing), ATR System, Runner System, Risk Limits, Notifications, etc. - Includes usage examples (correct vs wrong patterns) **File Distribution:** - docs/analysis/ - Performance analyses, blocked signals, profit projections - docs/architecture/ - Adaptive leverage, ATR trailing, indicator tracking - docs/bugs/ - CRITICAL_*.md, FIXES_*.md bug reports (7 files) - docs/cluster/ - EPYC setup, distributed computing docs (3 files) - docs/deployments/ - *_COMPLETE.md, DEPLOYMENT_*.md status (12 files) - docs/roadmaps/ - All *ROADMAP*.md strategic planning files (7 files) - docs/setup/ - TradingView guides, signal quality, n8n setup (8 files) - docs/archived/2025_pre_nov/ - Obsolete verification checklist (1 file) **Key Improvements:** - ENV variable reference: Single source of truth for all configuration - Common Pitfalls #68-71: Already complete, verified during audit - Better findability: Category-based navigation vs 68 files in root - Preserves history: All files git mv (rename), not copy/delete - Zero broken functionality: Only documentation moved, no code changes **Verification:** - 83 markdown files now in docs/ subdirectories - Root directory cleaned: 68 files → 0 files (except README.md) - Git history preserved for all moved files - Container running: trading-bot-v4 (no restart needed) **Next Steps:** - Create README.md files in each docs subdirectory - Add navigation index - Update main README.md with new structure - Consolidate duplicate deployment docs - Archive truly obsolete files (old SQL backups) See: docs/analysis/CLEANUP_PLAN.md for complete reorganization strategy
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Smart Entry Timing - Deployment Status
Status: ✅ DEPLOYED AND ACTIVE IN PRODUCTION
Deployment Date: November 27, 2025
Current State
Feature Configuration
- SMART_ENTRY_ENABLED:
true(ACTIVE) - MAX_WAIT_MS: 120000 (2 minutes)
- PULLBACK_MIN: 0.15% (minimum favorable move)
- PULLBACK_MAX: 0.50% (maximum before reversal risk)
- ADX_TOLERANCE: 2 points (trend strength validation)
Container Status
- Container:
trading-bot-v4running successfully - Build completed: 74 seconds (all dependencies fresh)
- Configuration loaded: Verified in
/app/.env - Lazy initialization: Will activate on first signal arrival
Expected Behavior
When signal arrives:
- Execute endpoint checks if Smart Entry is enabled (✅ true)
- Gets current price and compares to signal price
- If already at favorable pullback (0.15-0.5%):
- Executes trade immediately
- Logs:
✅ Smart Entry: Already at favorable level
- If not at favorable pullback yet:
- Queues signal for monitoring
- Logs:
⏳ Smart Entry: Queuing signal for optimal entry timing - Returns HTTP 200 to n8n (workflow continues)
- Monitors every 15 seconds for up to 2 minutes
First signal will show initialization:
💡 Smart Entry Timer initialized: {
enabled: true,
maxWait: '120s',
pullback: '0.15-0.5%',
adxTolerance: '2 points'
}
Monitoring Commands
Watch for Smart Entry activation
docker logs -f trading-bot-v4 | grep "Smart Entry"
Check initialization on first signal
docker logs trading-bot-v4 | grep "Smart Entry Timer initialized"
Verify queued signals
# API endpoint to check queue status (future enhancement)
curl http://localhost:3001/api/trading/smart-entry/status
Expected Log Sequence
Scenario 1: Already at favorable price
🎯 Smart Entry: Evaluating entry timing...
Signal Price: $142.50
Current Price: $142.29 (-0.15%)
✅ Smart Entry: Already at favorable level (0.15% pullback)
Executing immediately - no need to wait
Scenario 2: Need to wait for pullback (LONG example)
🎯 Smart Entry: Evaluating entry timing...
Signal Price: $142.50
Current Price: $142.48 (-0.01%)
⏳ Smart Entry: Queuing signal for optimal entry timing
Waiting for dip of 0.15-0.5%
💡 Smart Entry Timer initialized: {enabled: true, maxWait: '120s', pullback: '0.15-0.5%', adxTolerance: '2 points'}
📥 Smart Entry: Queued signal SOL-PERP LONG at $142.50
Target pullback: 0.15-0.5% (watchin for dip to $142.29-$141.79)
Expires in: 120s
🔍 Smart Entry: Checking 1 queued signals... (15s later)
SOL-PERP LONG: Current $142.30 (-0.14%) vs target -0.15% | ADX: 26.0 vs 28.0 (signal)
✅ Smart Entry: Pullback confirmed! SOL-PERP LONG at $142.28 (-0.15%)
Entry improved by: 0.15% ($22 on position)
Wait time: 23 seconds, Checks performed: 2
Scenario 3: Timeout before favorable entry
🔍 Smart Entry: Checking 1 queued signals...
⏰ Smart Entry: Timeout reached for SOL-PERP LONG (waited 120s)
Executing at current price: $142.55 (+0.04%)
Entry timing: Not optimal but within acceptable range
Scenario 4: ADX cancellation
🔍 Smart Entry: Checking 1 queued signals...
❌ Smart Entry: ADX dropped too much for SOL-PERP LONG
Signal ADX: 28.0, Current ADX: 25.5 (dropped 2.5 points > 2.0 tolerance)
Cancelling signal - trend weakening
Database Tracking
All trades will include Smart Entry metadata in configSnapshot:
{
"smartEntry": {
"used": true,
"improvement": 0.15,
"waitTime": 23,
"reason": "pullback_confirmed",
"checksPerformed": 2
}
}
Performance Analysis Query:
SELECT
COUNT(*) as total_trades,
COUNT(CASE WHEN (configSnapshot::jsonb->'smartEntry'->>'used')::boolean THEN 1 END) as smart_entry_used,
AVG((configSnapshot::jsonb->'smartEntry'->>'improvement')::float) as avg_improvement,
AVG((configSnapshot::jsonb->'smartEntry'->>'waitTime')::float) as avg_wait_time
FROM "Trade"
WHERE "createdAt" > NOW() - INTERVAL '7 days'
AND configSnapshot::jsonb ? 'smartEntry';
Financial Impact Projection
Expected Entry Improvement: 0.2-0.5% per trade
On $8,000 average position:
- 0.2% improvement = $16 per trade
- 0.5% improvement = $40 per trade
- Conservative estimate: $20-30 per trade average
Over 100 trades:
- Conservative: $2,000 improvement
- Expected: $3,000 improvement
- Best case: $4,000 improvement
Current capital ($540) → Goal ($100,000):
- Every $1,000 improvement = 1.85× capital gain
- $3,000 improvement = 5.55× capital gain (from entry timing alone)
- Compounds with existing 57.1% win rate and TP2-as-runner system
Validation Checklist
After First Signal
- Initialization log appears:
💡 Smart Entry Timer initialized - Config shows enabled: true
- Either immediate execution OR queued with monitoring
After First Queued Signal
- Monitoring logs every 15 seconds:
🔍 Smart Entry: Checking N queued signals... - Pullback detection working (shows current price vs target)
- ADX validation running (shows current vs signal ADX)
- Execution occurs on favorable pullback OR timeout
After 5-10 Trades
- Database
configSnapshotincludessmartEntrymetadata - Improvement percentages recorded correctly
- Wait times reasonable (mostly <60 seconds or timeouts)
- No errors or crashes from Smart Entry logic
After 50-100 Trades
- Run performance analysis SQL query
- Compare smart entry vs immediate entry (control group)
- Validate 0.2-0.5% improvement hypothesis
- Measure impact on win rate and profit factor
Troubleshooting
If no initialization log on first signal
- Check if signal passed quality score threshold (90+ for LONG, 95+ for SHORT)
- Verify signal included
signalPricefield - Check execute endpoint logs for Smart Entry evaluation
- Confirm
SMART_ENTRY_ENABLED=truein/app/.envinside container
If signals not queuing when expected
- Verify current price is NOT already at favorable pullback
- Check log:
✅ Smart Entry: Already at favorable level= immediate execution (correct) - Ensure pullback direction matches trade direction (LONG=dip, SHORT=bounce)
If queued signals never execute
- Check monitoring interval is running:
🔍 Smart Entry: Checking N queued signals... - Verify ADX not dropping too much (>2 points = cancellation)
- Ensure timeout (120s) eventually triggers execution
- Check Position Manager not interfering with queued signals
Next Steps
- Monitor first signal arrival (watch logs for initialization)
- Validate queuing behavior on first unfavorable entry price
- Collect 5-10 test trades to verify system stability
- Analyze entry improvements after 20-30 trades
- Full performance review after 50-100 trades
- Configuration tuning if needed (pullback range, wait time, ADX tolerance)
Git Commits
a8c1b2c- Implementation (smart-entry-timer.ts + integration)a98ddad- Documentation (SMART_ENTRY_TIMING_STATUS.md)cf6bdac- Deployment (SMART_ENTRY_ENABLED=true + rebuild)
Status: Ready for production trading. Feature will activate on next signal arrival.
Expected value: $2,000-4,000 improvement over 100 trades from better entry timing alone.