ThinkWithPrompt by SynotticThinkWithPrompt

Find the patterns in my practice exam mistakes

Your missed questions sorted by cause, with the top fixes, the topics to restudy, and a readiness verdict.

Learning & TeachingFew-ShotStandardEducationAnalyzeFill-in TemplateStep-by-step

The prompt

Analyze my practice exam mistakes and find the patterns behind them. Exam: [CERTIFICATION NAME] Practice score and passing target: [e.g. "64%, aiming for 75%+"] Results by domain (if available): [PASTE] Missed questions: [FOR EACH: topic, my answer, correct answer, and why I chose mine - a few words is fine] Time used vs. time allowed: [DETAILS] Readiness checklist (optional): [PASTE FROM STEP 1] Steps: 1. Classify each miss by cause: knowledge gap, misread the question, fell for a distractor, overthought or changed a correct answer, applied workplace habit instead of the exam's framework, time pressure, or careless error. 2. Count the causes and find the top 3 patterns. 3. Separate content problems (need to study) from test-taking problems (need a technique). 4. Rank topics to restudy by how many points they cost me and their exam weight. Return: - A table: Question/topic | Cause | Content or technique | Fix. - Top 3 patterns, each with a specific fix (e.g. "underline the qualifier: FIRST, BEST, LEAST before reading options"). - Ranked restudy list. - Updated confidence ratings for my step 1 checklist, if I pasted it. - A retest plan: what to review and when to take the next practice exam. - An honest readiness verdict: on track, borderline, or not yet, based only on the data I've given. This is step 4 of the "Pass a professional certification exam" pack. It works on its own, and can use the practice questions from step 3 or any practice exam.

Highlighted [brackets] are blanks to replace with your own details.

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What to fill in

  • CERTIFICATION NAME
  • e.g. "64%, aiming for 75%+"
  • PASTE
  • DETAILS
  • PASTE FROM STEP 1

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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