Both classical test theory (CTT) and item response theory (IRT) can provide guidance as far as which items are contributing to the latent trait you wish to measure, and which do not. With CTT, consider 1) item difficulty, 2) item correlation to total score, 3) item variance, and 4) impact on internal consistency estimates (e.g., Cronbach's alpha) if the item is removed.
Items that are too easy or too difficult tend not to help separate subject (discriminate between high scorers and low scorers). Unless you are interested in measuring differences between top performers, very difficult questions should be considered for removal. In a similar vein, very easy items are only suitable if you are interested in the performance of low performers.
All items should correlate positively with total score and you can set a lower bound for that correlation of around 0.20 as a guide. Low correlations or negative correlations may indicate that there are wording problems in your questionnaire and that the question should be reversed scored.
Items with low variance (variability of scores) should be considered for removal as they don't separate subjects and don't contribute to the information gathered from the survey. Items with very high variance may be measuring something else than the construct/trait you wish to measure.
If the estimate of internal consistency improves with the item removed, then the item should be considered for removal, or re-worded.
Items that everyone gets correct are sometimes maximum items and those everyone gets wrong are sometimes called minimum items. They don't contribute to the information you are trying to gather.
If you are developing a high stakes questionnaire or plan on marketing the questionnaire you should definitely consider IRT. However, it is a large subject area and unless you are truly interested it is not probably worth the space to get into it here.
Hope this helps.