This study explores how Value Sensitive Design (VSD) can be integrated into Responsible AI (RAI) toolkits. VSD is a framework that integrates human values into the design process, while RAI focuses on ethical AI development. The study hypothesizes that VSD is compatible and beneficial for RAI toolkits. To test this, four workshops were conducted with 17 early-career AI researchers. The workshops aimed to identify links between VSD and RAI values and examine how existing toolkits incorporate VSD principles. The findings show that collaborative and educational design features in these toolkits, such as illustrative examples and open-ended cues, help researchers understand human and ethical values and incorporate them into AI systems. Based on these insights, six design guidelines for integrating VSD into RAI toolkits were formulated. These guidelines focus on concrete design features such as supporting actionability and shared knowledge. The study also highlights the importance of considering VSD values in the design of RAI toolkits, as well as the need for practical tools and frameworks that support collaboration and learning. The findings suggest that VSD values align closely with RAI values, and that existing RAI toolkits can be improved by incorporating VSD principles. The study also identifies key design features that support collaboration and learning in RAI toolkits, such as open-ended cues, examples, and case studies. The study concludes that VSD can effectively guide the creation of RAI toolkits, and that integrating VSD into RAI toolkits can enhance their ability to support ethical AI development.This study explores how Value Sensitive Design (VSD) can be integrated into Responsible AI (RAI) toolkits. VSD is a framework that integrates human values into the design process, while RAI focuses on ethical AI development. The study hypothesizes that VSD is compatible and beneficial for RAI toolkits. To test this, four workshops were conducted with 17 early-career AI researchers. The workshops aimed to identify links between VSD and RAI values and examine how existing toolkits incorporate VSD principles. The findings show that collaborative and educational design features in these toolkits, such as illustrative examples and open-ended cues, help researchers understand human and ethical values and incorporate them into AI systems. Based on these insights, six design guidelines for integrating VSD into RAI toolkits were formulated. These guidelines focus on concrete design features such as supporting actionability and shared knowledge. The study also highlights the importance of considering VSD values in the design of RAI toolkits, as well as the need for practical tools and frameworks that support collaboration and learning. The findings suggest that VSD values align closely with RAI values, and that existing RAI toolkits can be improved by incorporating VSD principles. The study also identifies key design features that support collaboration and learning in RAI toolkits, such as open-ended cues, examples, and case studies. The study concludes that VSD can effectively guide the creation of RAI toolkits, and that integrating VSD into RAI toolkits can enhance their ability to support ethical AI development.