Imagine a world where crafting the perfect UX evaluation plan for your research is not a daunting task, but an engaging exploration. A world where AI assists you in navigating the complex landscape of metrics, connecting your research to relevant literature, and even anticipating potential risks. That world is now a reality with EvAlignUX, a groundbreaking tool designed to empower HCI scholars in their UX research endeavors. Evaluating user experience, especially in the age of increasingly complex AI systems, presents unique challenges. Traditional methods struggle to capture the nuances of human-AI interaction, and researchers often find themselves lost in a sea of metrics without clear guidance on how to choose the right ones for their project. EvAlignUX steps in as an intelligent guide, leveraging the power of large language models (LLMs) to streamline and enhance the UX evaluation planning process. This innovative system acts like an intelligent research assistant, providing a range of features to support researchers. It starts by analyzing the project description and intelligently suggesting relevant indexes, mapping the project within the existing body of UX literature. Then, it recommends a tailored list of UX metrics, providing explanations, examples from existing studies, and even visualizing their interrelationships in an interactive graph. The system allows researchers to easily add or remove metrics from their plan and dynamically updates related research outcomes and potential risks. Imagine being able to see how 'trust' and 'user satisfaction' intertwine in previous studies or being alerted to potential ethical concerns related to your chosen metrics. EvAlignUX brings these capabilities to your fingertips. But it's not just about having more information; it's about having the right information at the right time. EvAlignUX helps researchers formulate more concrete, complete, and rigorous UX evaluation plans, boosting their confidence in their research design. A study with 19 HCI scholars confirmed the system's effectiveness, showing significant improvements in the perceived clarity, feasibility, and overall quality of their evaluation proposals. One of the most compelling features of EvAlignUX is its ability to promote a 'mindset' shift in UX evaluation. It encourages researchers to move beyond simply applying pre-defined methods and instead critically reflect on the relationships between metrics, outcomes, and potential risks. This dynamic, iterative approach to UX planning is crucial for ensuring that HCI research is not only rigorous but also meaningful and impactful. EvAlignUX represents a significant step forward in how we approach UX research, offering a powerful blend of AI assistance and human expertise. While the current version focuses on human-AI interaction, future iterations could expand into other domains, unlocking even greater potential for UX research across diverse fields. As AI continues to shape the technological landscape, tools like EvAlignUX will be essential for ensuring that the user experience remains at the heart of innovation.