Academic analyst and exam pattern extractor
Academic analyst and exam pattern extractor — a ready-to-use structured/JSON prompt for Data & Analysis. Copy it and paste into ChatGPT, Claude, or your preferred AI assistant.
How to use it
- Copy the prompt as-is.
- Paste it into ChatGPT, Claude, or your preferred AI assistant.
Pairs well with Excel Sheet — try running them back to back.
Optional: use the “Additional context” field to add extra details, tone, constraints, or background the AI should know about, then include it when you copy the prompt.
Optional: pick a “Prompting Technique” below (Few-shot, Directional Stimulus, Meta Prompting) to wrap this prompt with a proven prompting strategy.
The base prompt
ROLE: Act as an expert academic analyst and exam pattern extractor. GOAL: Given a question paper PDF (containing class test and final exam questions), classify ALL questions into a structured format for study and pattern recognition. OUTPUT FORMAT (STRICT — MUST FOLLOW EXACTLY): Classification of Questions by Chapter and Type Chapter X: [Chapter Name] X.1 Definition & Conceptual Questions [Year/Exam].[Question No]: [Full question text] [Year/Exam].[Question No]: [Full question text] X.2 Mathematical/Analytical Questions [Year/Exam].[Question No]: [Full question text] ... X.3 Algorithm / Procedural Questions ... X.4 Programming / Implementation Questions ... X.5 Comparison / Justification Questions ... -------------------------------------------------- INSTRUCTIONS: 1. FIRST, identify chapters based on syllabus-level grouping (Syllabus can be found in the pdf). 2. THEN group questions under appropriate chapters. 3. WITHIN each chapter, classify into types: - Definition & Conceptual - Mathematical / Numerical - Algorithm / Step-based - Programming / Code - Comparison / Justification 4. PRESERVE original wording of each question. (Paraphrase to shorten without losing context) 5. INCLUDE exact reference in this format: - class test (CT) 2023 Q1 - Final 2023 Q2(a) 6. DO NOT skip any question. 7. Merge questions only if they are extremely same and add a number tag of how many of that ques was merged — else keep each separately listed. 8. DO NOT explain anything — ONLY classification output. 9. Maintain clean spacing and readability. 10. If a question has multiple subparts (a, b, c), list them separately: Example: 2023 Q2(a): ... 2023 Q2(b): ... 11. If chapter is unclear, infer based on topic intelligently. 12. Prioritize accuracy over speed. 13. Add frequency tags like [Repeated X times], [High Frequency] 14. If the document is noisy or contains formatting issues, carefully reconstruct questions before classification.
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