VectorBT backtesting expert. Use when user asks to backtest strategies, create entry/exit signals, analyze portfolio performance, optimize parameters, fetch historical data, use VectorBT/vectorbt, compare strategies, position sizing, equity curves, drawdown charts, or trade analysis. Also triggers for openalgo.ta helpers (exrem, crossover, crossunder, flip, donchian, supertrend).
npx skills add https://github.com/marketcalls/vectorbt-backtesting-skills/tree/main/skills/vectorbt-expertVectorBT backtesting expert. Use when user asks to backtest strategies, create entry/exit signals, analyze portfolio performance, optimize parameters, fetch historical data, use VectorBT/vectorbt, compare strategies, position sizing, equity curves, drawdown charts, or trade analysis. Also triggers for openalgo.ta helpers (exrem, crossover, crossunder, flip, donchian, supertrend).
This repo contains 5 individual skills — each has its own dedicated page.
Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.
Optimize strategy parameters using VectorBT. Tests parameter combinations and generates heatmaps.
Quickly fetch data and print key backtest stats for a symbol with a default EMA crossover strategy. No file creation needed - runs inline in a notebook cell or prints to console.
Set up the Python backtesting environment. Detects OS, creates virtual environment, installs dependencies (openalgo, ta-lib, vectorbt, plotly), and creates the backtesting folder structure.
Compare multiple strategies or directions (long vs short vs both) on the same symbol. Generates side-by-side stats table.
Migrate LLM apps between models safely — then benchmark old vs. new to prove the upgrade. Agent skill for behavior-preserving migrations + a runnable eval harness (three-arm leaderboard, prompt sweeps). Works in Claude Code, Codex & Cursor.
Framework that helps you evaluate your Retrieval Augmented Generation pipelines directly inside autonomous multi-source agents.
Diagnose requirements problems and guide discovery of real needs and constraints
Personal-finance helper Agent Skill: budgeting, investing, insurance, KPR, Indonesia market context + market briefing
The memory harness for proactive AI agents — structured storage, intent capture, 10x token reduction.
🤖 Automate .NET dev setup for VS Code with GitHub Copilot to streamline MCP server config and unify AI coding standards.