Multi-agent systems are societies with autonomous and heterogeneous agents that can work together to achieve similar or different goals. Agents executing in such systems may not be able to achieve their goals due to failures during system execution. When an agent tries to achieve its desired goals, but faces failures during execution, it becomes important to understand why such failures occurred and what can be done to remedy the problem. The distributed, dynamic and nature of multi-agent systems calls for a new form of failure handling approach to address its unique requirements, which involves both diagnosing specific failures and recommending alternative plans for successful agent execution and goal attainment. We discuss solutions to the main challenges of creating a system that can perform diagnoses and provide recommendations about agent executions to support goal attainment, and propose a hybrid diagnostic-recommendation framework that provides support for methods to address such challenges. From the framework, instances of different domains can be created, such as, applications based on ubiquitous computing and different diagnoses and recommendations can be provided.