agent-walkforward is an open-source CLI tool for performing walk-forward and out-of-sample validation in agent evaluation workflows. It helps AI researchers and ML engineers detect and prevent eval-set overfitting, similar to techniques used in quantitative finance for backtest validation. The tool is designed for robust agent benchmarking and MLops workflows.
agent-walkforward is a LLM eval & observability product. It focuses on detecting and preventing overfitting in agent evaluation by enabling walk-forward and out-of-sample validation. agent-walkforward is an open-source project aimed at AI researchers and ML engineers evaluating agent performance. The project is open source (MIT). It runs on the command line.
Behind agent-walkforward is Starlight143, and the product first shipped in 2026. The project is developed in the open on GitHub with 4 commits in the last 90 days. Among its 6 catalogued features are walk-forward validation, out-of-sample testing, and agent evaluation.
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