Trading System Diagnostics
Purpose
Use this skill when:
- No trading signals are being generated
- Need to verify AI analysis is working
- Validating technical indicator calculations
- Debugging market data issues
Diagnostic Commands
Full Diagnostic (Default)
cd /home/linuxuser/nautilus_AlgVex
source venv/bin/activate
python3 scripts/diagnose.pyQuick Diagnostic (Skip AI calls)
cd /home/linuxuser/nautilus_AlgVex
source venv/bin/activate
python3 scripts/diagnose.py --quickWith Update and Restart
python3 scripts/diagnose.py --update --restartExpected Output
Normal Operation Signs
✅ Configuration loaded successfully
✅ Market data fetched successfully
✅ TechnicalIndicatorManager initialized
✅ Technical data retrieved
✅ Sentiment data retrieved
✅ MultiAgent 层级决策成功
🐂 Bull Agent 分析中...
🐻 Bear Agent 分析中...
⚖️ Judge Agent 判断中...
🛡️ Risk Manager 评估中...
🎯 Judge 最终决策: BUY/SELL/HOLDKey Checkpoints
| Check | Normal Value | Abnormal Handling |
|---|---|---|
| RSI | 0-100 | Out of range = data error |
| MACD | Any value | NaN = insufficient data |
| Signal | LONG/SHORT/HOLD | net_raw 阈值决策 |
| Confidence | HIGH/MEDIUM/LOW | 基于 net_raw 幅度 + zone 条件 |
信号决策流程 (Prism v49.0)
决策流程:
1. 数据聚合: 13 类数据 → 141 typed features
2. 3 维评分: Structure / Divergence / Order Flow → net_raw
3. 阈值决策: |net_raw| >= 0.45→HIGH, >=0.35→MED, >=0.20+zone→LOW
4. DCA 仓位: base_order_pct × equity, 最多 4 层注意: 所有策略参数配置在 configs/base.yaml 中管理。
Common Issues
1. No Trading Signals
Possible Causes:
- net_raw 低于阈值 (|raw| < 0.20)
- Zone 条件不足 (低 raw 需要至少 1 个 zone)
- Direction lock (连续止损锁定方向)
Check Command:
cd /home/linuxuser/nautilus_AlgVex && sudo journalctl -u nautilus-trader --since "1h ago" | grep "Hybrid decision"2. Order Rejected (Min Notional)
Check:
cd /home/linuxuser/nautilus_AlgVex && sudo journalctl -u nautilus-trader --since "1h ago" | grep "notional\|rejected\|-4164"3. Abnormal Technical Indicators
Check:
python3 scripts/diagnose.py 2>&1 | grep -E "(RSI|MACD|SMA)"Key Files
| File | Purpose |
|---|---|
scripts/diagnose.py | Main diagnostic script |
scripts/diagnose_realtime.py | Real-time API diagnostic |
scripts/diagnostics/ | Modular diagnostic system |
scripts/smart_commit_analyzer.py | Regression detection (auto-evolving rules) |
strategy/ai_strategy.py | Main strategy logic |
configs/base.yaml | Base configuration (all parameters) |
configs/production.yaml | Production environment overrides |
Order Flow Simulation (v3.18)
模块化诊断系统包含 7 个订单流场景模拟。
7 Scenarios (模拟场景)
| 场景 | 描述 | 测试目标 |
|---|---|---|
| 1. New Position | 开新仓 (无现有持仓) | Bracket 订单创建 |
| 2. Add to Position | 加仓 (同方向) | SL/TP 数量更新 |
| 3. Reduce Position | 减仓 | SL/TP 数量减少 |
| 4. Reversal | 反转仓位 (多→空/空→多) | 两阶段提交逻辑 |
| 5. Close Position | 平仓信号 | 仓位关闭 + 取消 SL/TP |
| 6. Bracket Failure | SL/TP 订单失败 | CRITICAL 告警 (不回退) |
| 7. SL/TP Modify Failure | SL/TP 修改失败 | WARNING 告警 |
Run Order Flow Simulation
cd /home/linuxuser/nautilus_AlgVex
source venv/bin/activate
python3 scripts/diagnose_realtime.py诊断输出将包含 "Step 9: Order Flow Simulation (v3.18)" 显示所有 7 个场景的模拟结果。
Expected Output
============================================================
Step 9: Order Flow Simulation (v3.18)
============================================================
✅ Scenario 1: New Position - PASSED
✅ Scenario 2: Add to Position - PASSED
✅ Scenario 3: Reduce Position - PASSED
✅ Scenario 4: Reversal - PASSED
✅ Scenario 5: Close Position - PASSED
✅ Scenario 6: Bracket Failure - PASSED
✅ Scenario 7: SL/TP Modify Failure - PASSED
📊 Order Flow Simulation Summary: 7/7 scenarios passed回归检测 (修改代码后必须运行)
# 智能回归检测 (规则自动从 git 历史生成)
python3 scripts/smart_commit_analyzer.py
# 预期结果: ✅ 所有规则验证通过