After 20 years of testing a framework for affective user responses to artificial agents and robots, we compiled a full formalization of our findings so to make the agent respond affectively to its user. Silicon Coppélia as we dubbed our system works from the features of the observed other, appraises these in various domains (e.g., ethics and affordances), then compares them to goals and concerns of the agent, to finally reach a response that includes intentions to work with the user as well as a level of being engaged with the user. This ultimately results in an action that adds to or changes the situation both agencies are in. Unlike many other systems, Silicon Coppélia can deal with ambiguous emotions of its user and has ambiguous 'feelings' of its own, which makes its decisions quite human-like. In the current paper, we advance a fuzzy-sets approach and show the inner workings of our system through an elaborate example. We present a number of simulation experiments, one of which showed decision behaviors based on biases when agent goals had low priorities. Silicon Coppélia is open to scrutiny and experimentation by way of an open-source implementation in Ptolemy.