I know that was a joke, but in situations like this there are two separate measures of error; precision and recall. Precision is how many of the results marked as relevant really were (measure of false positives), recall is how many of the actually relevant results were correctly considered relevant (measure of false negatives).

Any system can trivially have perfect precision by saying all results are not relevant, or perfect recall by saying all results are relevant. Your system would have 100% precision and 0% recall.