bendex-resilience is a Python library that performs resilience testing on AI agents and stateful systems. It uses twin-trajectory divergence analysis to determine whether a system recovers or cascades after a perturbation. The tool works with minimal historical data and requires no internal model of the system.
In the LLM eval & observability space, bendex-resilience takes a focused approach. It focuses on evaluating whether an AI agent or stateful system recovers from perturbations without internal models or large datasets. It is built as an open-source project for AI developers. The project is open source (MIT). It ships for the command line.
It is developed by 9hannahnine-jpg, and it first shipped in 2026. The project is developed in the open on GitHub with 1 commit in the last 90 days. Among its 4 catalogued features are twin-trajectory analysis, resilience testing, and minimal data requirement.
Summary written by a language model from the project’s public pages.
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