signal-classification
๐ฏSkillfrom agiprolabs/claude-trading-skills
|A machine learning trading skill that trains XGBoost/LightGBM classifiers with walk-forward validation for predicting trading signals, part of a 62-skill collection of ready-to-use trading, DeFi, and quant finance skills.
Same repository
agiprolabs/claude-trading-skills(64 items)
Installation
npx vibeindex add agiprolabs/claude-trading-skills --skill signal-classificationnpx skills add agiprolabs/claude-trading-skills --skill signal-classification~/.claude/skills/signal-classification/SKILL.mdSKILL.md
More from this repository10
Part of a collection of 62 trading, DeFi, and quantitative finance agent skills. Provides pandas-ta technical analysis capabilities for market data analysis, enabling AI agents to compute indicators and execute quantitative trading workflows.
A comprehensive collection of 62 ready-to-use trading, DeFi, and quantitative finance agent skills for AI tools like Claude Code and Cursor, covering market data analysis, on-chain research, backtesting, risk management, and tax compliance.
A skill covering walk-forward validation frameworks for trading strategies and ML models, addressing why standard k-fold cross-validation fails on financial time series and providing correct techniques including rolling/expanding windows, purged cross-validation, and overfit detection.
A trading agent skill implementing the Kelly criterion for optimal bet sizing in crypto trading, covering full and fractional Kelly variants, edge estimation from historical data, and practical application for managing position sizes and ruin risk.
Creates professional trading visualizations including candlestick charts, equity curves, drawdown plots, correlation heatmaps, and return distributions using mplfinance, matplotlib, and plotly with dark theme defaults.
A comprehensive collection of 62 ready-to-use trading, DeFi, and quantitative finance agent skills for AI tools like Claude Code and Cursor, covering market data analysis, on-chain research, backtesting, risk management, and tax compliance.
Identifies current market regimes using volatility clustering, trend detection, and statistical methods such as ATR percentile, ADX, and Hurst exponent analysis. Classifies markets into four quadrants (trending/ranging vs low/high volatility) to guide strategy selection, position sizing, and risk management.
A skill for DEX orderflow analysis on Solana, covering trade classification (buy vs sell), volume profiles, buyer/seller pressure metrics, whale detection, flow momentum signals, and wash trading detection for AMM-based trading.
Covers trade position sizing methods including fixed fractional, volatility-adjusted, Kelly criterion, liquidity-constrained, and anti-martingale approaches with formulas, risk tiers, and practical examples for portfolio risk management.
A trading agent skill for extracting and quantifying market sentiment from social media, news feeds, and on-chain data, identifying crowd positioning, euphoria/panic extremes, and influencer tracking for contrarian trading opportunities.