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This article contributes results of a longitudinal field study of Skill-sIdentifier, an employment tool originally designed and assessed in the United States (U.S.), to support "underrepresented" job seekers in identifying and articulating their employment skills. To understand whether the tool could support the needs of job seekers outside the U.S., we assessed it among 16 job seekers with limited education and language resources in Switzerland. While many of our results mirrored those of the U.S., we found that the tool was especially beneficial for non-French speaking immigrants who needed support describing their skills outside of their native language. We also found that listing skills like "active listening" without important context was insufficient and risked hiding key skills and meaning behind those skills to employers. Taking these factors into account, we illustrate the design implications of our findings and directions for practitioners who wish to design employment tools in support of job seekers, especially those who have traditionally been excluded from the labor market. We then provide insight into the potential for unintended consequences as a result of focusing solely on skills in a post-COVID labor market and contribute ways to mitigate them. CCS CONCEPTS• Human-centered computing → Empirical studies in HCI; User studies; • Social and professional topics → Employment issues.

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In this letter, we seek to build connections between control Lyapunov functions (CLFs) and Hamilton-Jacobi (HJ) reachability analysis. CLFs have been used extensively in the control community for synthesizing stabilizing feedback controllers. However, there is no systematic way to construct CLFs for general nonlinear systems and the problem can become more complex with input constraints. HJ reachability is a formal method that can be used to guarantee safety or reachability for general nonlinear systems with input constraints. The main drawback is the well-known "curse of dimensionality." In this letter we modify HJ reachability to construct what we call a control Lyapunov-Value Function (CLVF) which can be used to find and stabilize to the smallest control invariant set (I ∞ m ) around a point of interest. We prove that the CLVF is the viscosity solution to a modified HJ variational inequality (VI), and can be computed numerically, during which the input constraints and exponential decay rate γ are incorporated. This process identifies the region of exponential stability to I ∞ m given the desired input bounds and γ . Finally, a feasibilityguaranteed quadratic program (QP) is proposed for online implementation.