backtest-runner

Execute historical backtests for algorithmic trading strategies and analyze performance metrics.

Updated Aug 27, 2026

Search Tags:#risk management #performance analysis #backtesting #trading strategy #crypto trading #historical data

Ready to run

npx skills add https://github.com/anjieyang/GetAll --skill backtest-runner

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: backtest-runner
Source: https://github.com/anjieyang/GetAll/tree/main/getall/skills/backtest-runner
Command: npx skills add https://github.com/anjieyang/GetAll --skill backtest-runner

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the process of backtesting trading strategies, providing detailed performance metrics and visualizations to assess their historical viability.

Core Features & Use Cases

Strategy Validation: Run backtests on custom trading strategies against historical market data.
Performance Analysis: Interpret key metrics like total return, drawdown, Sharpe ratio, and win rate.
Visual Reporting: Automatically generate professional dashboard charts for easy understanding of strategy performance.
Use Case: After developing a new trading strategy, use this Skill to test its performance over the last six months on BTC/USDT using a 4-hour timeframe.

Quick Start

Use the backtest runner to validate the attached strategy configuration.

Frequently Asked Questions about backtest-runner

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I backtest a crypto trading strategy using historical data?▼

Backtest a crypto trading strategy by providing structured strategy configurations, timeframes, and exchange parameters for deterministic execution against historical data. The runner executes the backtest and automatically generates visual dashboard charts and performance metrics.

What performance analysis metrics are included in historical backtesting results?▼

Historical backtesting results include total return, drawdown, Sharpe ratio, and win rate. These performance analysis metrics are interpreted against benchmarks across specified periods and symbols to assess the strategy's historical viability.

Can I validate a custom trading strategy on BTC/USDT with a 4-hour timeframe?▼

Yes, you can validate custom trading strategies on BTC/USDT using a 4-hour timeframe. The Skill requires structured strategy configurations, specified periods, and exchange parameters to execute deterministic historical backtests and report performance.

What is the best way to analyze algorithmic trading strategy performance against benchmarks?▼

The best way to analyze algorithmic trading strategy performance is running historical backtests across specified periods and symbols. This approach interprets key metrics like drawdown and Sharpe ratio against benchmarks to validate historical viability.

Do I need structured strategy configurations to run a backtest on historical market data?▼

Yes, structured strategy configurations are required to run a backtest on historical market data. You must also provide specified timeframes and exchange parameters to ensure deterministic execution and accurate performance reporting.