Trader Regime
- 635 installs
- 67k repo stars
- Updated August 4, 2026
- ruvnet/ruflo
trader-regime is a Claude Code skill that detects bull, bear, ranging, and volatile market regimes using neural-trader and recommends regime-appropriate trading strategies before backtests or signals.
About
trader-regime is a ruflo skill that runs neural-trader regime detection to classify current market conditions as bull, bear, ranging, or volatile, then suggests strategies suited to that regime. It accepts symbols such as SPY or comma-separated tickers like AAPL and MSFT, installs neural-trader via npm when missing, and integrates claude-flow MCP memory and neural_predict tools. Developers reach for trader-regime when evaluating market conditions, selecting a strategy for current volatility, or making backtests and signal runs regime-aware.
- trader-regime
Trader Regime by the numbers
- 635 all-time installs (skills.sh)
- +10 installs in the week ending Jul 26, 2026 (Skillselion tracking)
- Ranked #586 of 4,347 Backend & APIs skills by installs in the Skillselion catalog
- Data as of Aug 5, 2026 (Skillselion catalog sync)
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| Installs | 635 |
|---|---|
| repo stars | ★ 67k |
| Last updated | August 4, 2026 |
| Repository | ruvnet/ruflo ↗ |
How do you detect current market regime for trading?
Use trader-regime for development tasks
Who is it for?
Quant developers using neural-trader who need regime-aware strategy selection before backtests or live signals.
Skip if: Developers building unrelated web apps or teams without npm neural-trader and market data access for regime classification.
When should I use this skill?
User asks about market conditions, wants a strategy for current conditions, or before regime-aware backtests or signal generation.
What you get
Regime classification label, recommended strategy mapping, and symbol-specific regime report stored via claude-flow memory.
- regime classification
- strategy recommendation
- memory-stored regime report
By the numbers
- Detects 4 market regimes: bull, bear, ranging, volatile
Files
Detect the current market regime using neural-trader's regime detection engine.
Steps: 1. Ensure neural-trader is available: npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-trader 2. Run regime detection:
npx neural-trader --regime-detect --symbol TICKERFor multiple symbols:
npx neural-trader --regime-detect --symbols "AAPL,MSFT,GOOGL,AMZN"3. Get technical indicators for context:
npx neural-trader --symbol TICKER --indicators rsi,macd,bollinger,adx,atr4. Use SONA for regime prediction: mcp__claude-flow__neural_predict({ input: "indicators: RSI=X, ADX=Y, VIX=Z" }) 5. Search for similar historical regimes: mcp__claude-flow__memory_search({ query: "regime similar to CURRENT", namespace: "trading-analysis" }) 6. Present: regime classification, confidence, recommended strategy type, historical precedents 7. Store analysis: mcp__claude-flow__memory_store({ key: "regime-DATE", value: "REGIME_ANALYSIS", namespace: "trading-analysis" })
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Pick trader-regime for live regime classification before strategy runs; use general analytics skills when the task is product metrics rather than market regimes.
FAQ
What regimes does trader-regime detect?
trader-regime uses neural-trader to classify markets as bull, bear, ranging, or volatile, then recommends strategies appropriate to the detected regime before backtests or signal runs.
Which symbols can trader-regime analyze?
trader-regime accepts a --symbol argument such as SPY or a --symbols comma list like AAPL,MSFT, installing neural-trader via npm if the package is not already available.