Indeed. coala is more of a framework that allows you to plug in any analysis routine. However, it also provides means to
create new code analysis very easily and combine arbitrary routines.
So yes, there are some very simple generic algorithms (line length checking, spacing corrections, we have things like variable name checking in the works which only need a few lines "language definition") and you can combine them with - possibly wrapped or not - language dependent algorithms easily.
This is useful for the user because he doesn't have to learn and configure tons of tools and he has some basic functionality for every language - even the ones he writes tomorrow.
It's also useful for people writing static code analysis because they can just write their algorithm and be done with it - why should everybody rewrite a CLI interface, editor plugins and so on?
I wrote a thesis about code clone detection (another algorithm that is basically generic and would need only a relatively small parsing part per language, coala allows me to modularize meanfully into parsing and language independent AST processing) and it just took me a few functions that actually performed the analysis. People can now use it easily which usually isn't true for research programs and I had even less work than I would have if I had written it without coala.