The difficulty of the whole test naturally depends on the difficulty of each item that constitutes the test. According to the distribution of the total score of the exam, we can know the difficulty of the whole exam. If the test difficulty is appropriate, the test scores of standardized samples should be roughly normal distribution.
If the test difficulty is improper, there may be two typical skewed distributions in the test scores. One is normal and skewed distribution, and the scores are concentrated at the low end. This shows that the exam is too difficult and lacks a sufficient number of easy questions. Subjects who should have a large distribution range at the left end of the normal curve get zero or close to zero in this item. Therefore, the test can't distinguish the subjects with lower ability level.
The other is negative skew distribution, and the scores are concentrated at the high end. This shows that the exam is too easy and there are not enough difficult items. Subjects who should have a large distribution range at the right end of the normal curve get full marks or close to full marks in this project. Therefore, the test cannot distinguish the subjects with high ability level.