Diagnose my admissions test practice results by question type
Accuracy and timing by question type, your biggest point opportunities ranked, and a focus plan for the next two weeks.
The prompt
Diagnose my GRE, GMAT, LSAT, or similar practice test results by question type.
Test: [NAME]
Practice test source: [e.g. "official practice test 1" - official tests give the most reliable estimate]
Section scores and total: [SCORES]
Target score: [PASTE FROM STEP 1, or state it]
Question-level results: [FOR EACH QUESTION OR GROUP: question type, right/wrong, time spent - paste the score report export if you have it]
How it felt: [e.g. "ran out of time in quant", "guessed a lot on reading"]
Steps:
1. Group results by question type and calculate accuracy and average time for each.
2. Classify wrong answers where possible: didn't know the content, misread, fell for a trap answer, ran out of time, or guessed.
3. Rank point opportunities: how often a question type appears x how far my accuracy is from what my target score requires.
4. Separate quick wins (careless errors, timing) from longer builds (content gaps).
5. Check for timing problems: types where I spend far longer than average for low accuracy.
Return:
- A table: Question type | Questions | Accuracy | Avg time | Main error type | Priority.
- The top 3 point opportunities with why.
- Quick wins I can apply on the next test.
- A two-week focus plan: which question types to drill on which days, and when to take the next practice test.
Work only from the data I give; if the data is too thin for a conclusion, say so. This is step 2 of the "Prepare for a graduate admissions test" pack. It works on its own, and can use the target from step 1.
Highlighted [brackets] are blanks to replace with your own details.
Fill in the blanks and use this promptMore Learning & Teaching prompts
What to fill in
- NAME
- SCORES
- PASTE FROM STEP 1, or state it
- e.g. "ran out of time in quant", "guessed a lot on reading"
How this prompt is built
This prompt follows the Few-Shot structure (Few-shot prompting). A few-shot prompt includes one or more worked examples of the input and the output you want, so the model can copy the pattern instead of guessing it.
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