{"enrichment":{"faq":[{"a":"Regime Detection combines ADX trend strength with statistical methods like Hurst exponent to classify market behavior. ADX measures directional momentum, while Hurst exponent detects mean-reversion versus trending persistence. The skill also monitors Bollinger Band squeeze and CUSUM change-point detection to spot transitions between choppy ranges and clean trends, tuned for crypto's faster regime shifts.","q":"How does regime-detection identify trending vs ranging markets?"},{"a":"Regime Detection applies multiple approaches: ATR volatility percentiles and Bollinger Band squeeze for volatility classification, ADX for trend strength, Hurst exponent for mean-reversion detection, and CUSUM for change-point identification. These combine into a regime quadrant (volatility \u00d7 trend axes) without requiring machine learning, making it transparent and fast for adaptive strategy selection.","q":"What market regime detection methods does this skill use?"},{"a":"Regime Detection measures volatility and classifies the current regime quadrant, enabling you to scale position size accordingly. High-volatility regimes warrant smaller positions; low-volatility trending conditions allow larger exposure. The skill also adapts stop losses and risk limits based on detected regime, helping you align risk parameters with current market conditions.","q":"How can I use regime detection for position sizing and risk management?"},{"a":"Regime Detection applies statistical methods including Hurst exponent to classify trending versus mean-reversion behavior. In trending regimes (high ADX, high Hurst), follow the trend. In ranging regimes (low ADX, low Hurst), use mean-reversion. The skill detects these transitions automatically, helping you select the appropriate strategy for current market conditions without manual regime assessment.","q":"When should I use trend following versus mean reversion strategies?"},{"a":"Regime Detection is tuned for crypto's faster and more volatile regime shifts compared to traditional markets. It uses rapid change-point detection via CUSUM and volatility clustering analysis to catch transitions quickly. ATR percentiles and volatility regime classification adjust dynamically, enabling crypto traders to adapt position sizing and strategy selection as market conditions evolve.","q":"How does regime-detection adapt to crypto market regime changes?"},{"a":"Regime Detection is released under the MIT license, allowing free use, modification, and distribution for both commercial and personal projects with minimal restrictions.","q":"What is the license for regime-detection?"}],"shadow_tags":["market-classification","volatility-measurement","trend-confirmation","adaptive-strategy","statistical-analysis","mean-reversion-detection","breakout-identification","risk-adjustment","regime-transition","signal-routing"],"summary_rewrite":"Regime Detection classifies market conditions across volatility and trend axes to help you choose the right strategy for current conditions. It combines simple approaches like ATR percentiles and ADX with statistical methods including Hurst exponent and change-point detection, with tuning for crypto's faster regime shifts."},"files":[{"bytes":10654,"path":"skills/regime-detection/SKILL.md","sha256":"6c654c23f490a3f09e78c6d47cbed6d6b09fd5ac3e9ba4a57875b710d02f535d","url":"https://skillfed.io/files/agiprolabs/claude-trading-skills/regime-detection/31cdfb0f/SKILL.md"}],"id":"agiprolabs/claude-trading-skills/regime-detection","links":{"html":"https://skillfed.io/agiprolabs/claude-trading-skills/regime-detection","md":"https://skillfed.io/agiprolabs/claude-trading-skills/regime-detection.md","repo":"https://github.com/agiprolabs/claude-trading-skills"},"meta":{"agents_supported":[],"first_seen":"2026-07-28","forks":52,"language":"Python","last_updated":"2026-06-24","license":"MIT","name":"regime-detection","publisher":"agiprolabs","stars":248},"relations":{"similar":[{"id":"agiprolabs/claude-trading-skills/mean-reversion"},{"id":"agiprolabs/claude-trading-skills/volatility-modeling"},{"id":"agiprolabs/claude-trading-skills/feature-engineering"},{"id":"agiprolabs/claude-trading-skills/cointegration-analysis"},{"id":"robonet-tech/skills/design-trading-strategies"},{"id":"terrylica/cc-skills/garch-vol-recipes"},{"id":"agiprolabs/claude-trading-skills/strategy-framework"},{"id":"ScientiaCapital/skills/trading-signals-skill"},{"id":"HKUDS/Vibe-Trading/correlation-analysis"},{"id":"HKUDS/Vibe-Trading/options-advanced"}]},"slug":{"owner":"agiprolabs","repo":"claude-trading-skills","skill":"regime-detection"},"version":"31cdfb0f"}