The VAKRA framework evaluates how AI agents handle complex tool-use tasks and reasoning chains. Researchers identified specific failure modes where agents loop indefinitely or misinterpret tool outputs. This analysis provides a blueprint for debugging agentic workflows. Developers can now pinpoint exactly where logic breaks during multi-step execution to improve reliability in autonomous systems.