backtest
Quick backtest a strategy on a symbol. Creates a complete .py script with data fetch, signals, backtest, stats, and plots.
Install
With your agent
Install OMGSkills skill "marketcalls/vectorbt-backtesting-skills:backtest" into this agent's normal skills directory: call the OMGSkills MCP get_install_plan tool for your agent and run the script it returns (it installs only the pinned commit and verifies SKILL.md), and stop if MCP or the pin is unavailable. Do not overwrite or change existing skills without asking me.
Manual command
git clone https://github.com/marketcalls/vectorbt-backtesting-skills /tmp/vectorbt-backtesting-skills && ln -s /tmp/vectorbt-backtesting-skills/.claude/skills/backtest ~/.claude/skills/backtestFrom README
Arguments Parse $ARGUMENTS as: strategy symbol exchange interval $0 = strategy name (e.g., ema-crossover, rsi, donchian, supertrend, macd, sda2, momentum) $1 = symbol (e.g., SBIN, RELIANCE, NIFTY). Default: SBIN $2 = exchange (e.g., NSE, NFO). Default: NSE $3 = interval (e.g., D, 1h, 5m). Default: D If no arguments, ask the user which strategy they want. Instructions Read the vectorbt-expert skill rules for reference patterns Create backtesting/{strategyname}/ directory if it doesn't exist (on-demand) Create a .py file in backtesting/{strategyname}/ named {symbol}{strategy}backtest.py Use the matching template from rules/assets/{strategy}/backtest.py as the starting point The script must: Load .env from the project root using finddotenv() (walks up from script dir automatically) Fetch data via client.history() from OpenAlgo If user provides a DuckDB path, load data directly via duckdb.connect(path, readonly=True) instead of OpenAlgo API.