A halo effect suggests that the overall impression of a rated object (e.g., a person) excessively influences the impression of facets of a person. This leads to correlations between facet ratings higher than would be expected were facets rated accurately.
If someone is a nearly perfect person, then presumably the overall impression they create would be very positive. The halo effect would not influence this overall very positive rating. It will merely increase ratings for facets that should be rated below the overall rating and decrease ratings for facets that should be rated above the overall rating..
Let's simplify it and assume that your person's true rating on all the facets that matter out of 10 are:
- Facet A = 6
- Facet B = 10
- Facet C = 10
- Facet D = 10
If we further simplify to say that overall impression is just the mean of the facets, we have overall impression of (6+10+10+10)/4 = 9.
So, an example of a rater influenced by the halo effect would be one who gave rating such as:
- Facet A = 9
- Facet B = 9
- Facet C = 9
- Facet D = 9
- Facet A = 8
- Facet B = 9.33
- Facet C = 9.33
- Facet D = 9.33
The point is that facets that are worse than the general impression are pulled up, and facets better than the general impression are pulled down. The mean of the facets has not changed. It is just the accuracy of facet ratings has declined. While this is an idealised example, the question relates to a theoretical effect.
A classic examples of a halo effect is where a teacher is marking an assignment and each section of the assignment is graded. If the teacher is influenced by halo effect then the overall mark is not influenced, but the rating for each section will be less differentiated than it should be. So from a quality of student feedback perspective, this is worse, but from a grading perspective, it makes no difference. That said, we might hypothesise that raters that exhibit halo effect may also exhibit other rating problems.
Second guessing your question, perhaps you are interested in some other biases such as first impression bias, central tendency bias, or generally inaccurate ratings. Or perhaps you are, rightly or wrongly, assuming that the overall impression would involve an inaccurate implicit weighting of facets.