We present a rule--based shallow--parser compiler, which allows to generate a robust shallow-parser for any language, even in the absence of training data, by resorting to a very limited number of rules which aim at identifying constituent boundaries. We contrast our approach to other approaches used for shallow--parsing (i.e. finite-state and probabilistic methods). We present an evaluation of our tool for English (Penn Treebank) and for French (newspaper corpus "LeMonde") for several tasks (NP-chunking & "deeper" parsing).