This study explores the integration of Value Sensitive Design (VSD) into Responsible AI (RAI) toolkits, aiming to align VSD values with RAI values and enhance collaboration and learning. The research involves four workshops with 17 early-career AI researchers, focusing on the alignment of VSD and RAI values and the design features of existing RAI toolkits. The findings show that VSD values align closely with RAI values, with a high degree of consensus among participants. The Nokia AI Design toolkit, which offers open-ended cuing and supports collaborative brainstorming, is preferred for team collaboration, while the MIT Blindspots toolkit, with detailed examples and case studies, is better suited for solo work and education. Participants found the Nokia AI Design toolkit more effective for generating a broader range of ideas and considering multiple stakeholder perspectives. The study also highlights the need for more practical support in RAI toolkits, such as code analysis tools and specific recommendations, to improve actionability. Based on these insights, six design guidelines are formulated to enhance value sensitivity in RAI toolkits, emphasizing the importance of open-ended cuing, stakeholder inclusion, and practical support.This study explores the integration of Value Sensitive Design (VSD) into Responsible AI (RAI) toolkits, aiming to align VSD values with RAI values and enhance collaboration and learning. The research involves four workshops with 17 early-career AI researchers, focusing on the alignment of VSD and RAI values and the design features of existing RAI toolkits. The findings show that VSD values align closely with RAI values, with a high degree of consensus among participants. The Nokia AI Design toolkit, which offers open-ended cuing and supports collaborative brainstorming, is preferred for team collaboration, while the MIT Blindspots toolkit, with detailed examples and case studies, is better suited for solo work and education. Participants found the Nokia AI Design toolkit more effective for generating a broader range of ideas and considering multiple stakeholder perspectives. The study also highlights the need for more practical support in RAI toolkits, such as code analysis tools and specific recommendations, to improve actionability. Based on these insights, six design guidelines are formulated to enhance value sensitivity in RAI toolkits, emphasizing the importance of open-ended cuing, stakeholder inclusion, and practical support.