Agent skill · Data & Analytics

diagnose

Run diagnostics for the AItrader trading system. 运行 AItrader 交易系统诊断。 Use this skill when: - No trading signals are being generated (没有交易信号) - Need to check if AI analysis is working (检查 AI 分析是否正常) - Verifying technical indicator calculations (验证技术指标计算) - Debugging market data fetching issues (调试市场数据获取) - Troubleshooting why no trades are happening (排查为什么没有交易) - Running system health checks (运行系统健康检查)

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill diagnose --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 3 KB
Bundled scripts: none
Path: skills/analysis/diagnose/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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) ```bash cd /home/linuxuser/nautilus_AItrader source venv/bin/activate python3 scripts/diagnose.py ``` ### Quick Diagnostic (Skip AI calls) ```bash cd /home/linuxuser/nautilus_AItrader source venv/bin/activate python3 scripts/diagnose.py --quick ``` ### With Update and Restart ```bash python3 scripts/diagnose.py --update --restart ``` ## Expected 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/HOLD ``` ### Key Checkpoints | Check | Normal Value | Abnormal Handling | |-------|--------------|-------------------| | RSI | 0-100 | Out of range = data error | | MACD | Any value | NaN = insufficient data | | Judge Signal | BUY/SELL/HOLD | ER

What's inside
Steps it walks through
  1. Purpose
  2. Diagnostic Commands
  3. Full Diagnostic (Default)
  4. Quick Diagnostic (Skip AI calls)
  5. With Update and Restart
  6. Expected Output
  7. Normal Operation Signs
  8. Key Checkpoints
  9. 信号决策流程 (层级决策架构)
  10. Common Issues
  11. 1. No Trading Signals
  12. 2. DeepSeek API Failure
  13. 3. Abnormal Technical Indicators
  14. Key Files
Ships with 1 file
  • metadata.json
Commands it runs
cd /home/linuxuser/nautilus_AItrader
source venv/bin/activate
python3 scripts/diagnose.py
python3 scripts/diagnose.py --quick
python3 scripts/diagnose.py --update --restart
python3 scripts/diagnose_realtime.py 2>&1 | grep -E "(Judge|Final Signal|Confidence|Winning Side)"
grep "DEEPSEEK_API_KEY" ~/.env.aitrader
python3 scripts/diagnose.py 2>&1 | grep -E "(RSI|MACD|SMA)"
python3 scripts/smart_commit_analyzer.py
More from claude-skill-registry
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About this skill
What does the diagnose skill do?

Run diagnostics for the AItrader trading system. 运行 AItrader 交易系统诊断。 Use this skill when: - No trading signals are being generated (没有交易信号) - Need to check if AI analysis is working (检查 AI 分析是否正常) - Verifying technical indicator calculations (验证技术指标计算) - Debugging market data fetching issues (调试市场数据获取) - Troubleshooting why no trades are happening (排查为什么没有交易) - Running system health checks (运行系统健康检查)

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill diagnose --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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