Gene libraries have been added to Artificial Immune Systems in analogy to biological immune systems, but to date no careful study of their effect has been made. This work investigates the contribution of gene libraries to Artificial Immune Systems by reproducing and extending an earlier system that used gene libraries. Performance on a job-shop scheduling problem is evaluated empirically with and without gene libraries, and with many different library configurations. We propose that gene libraries encourage diversity in a population of solutions and that the number of components in the gene library parameterises this effect. The number of gene libraries used is found to affect solution fitness and indeed using larger numbers of libraries (and therefore libraries of smaller components) enables higher fitness to be attained. We conclude that gene libraries are likely to be of use in applications where there is a need to maintain the diversity of solutions.