The 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
...
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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.
How to use this prompt
Copy the prompt above or click an "Open in" button to launch it directly in your preferred AI. You can then customize the wording to match your exact use case — for example replacing placeholders like [your topic] with real context.
Which AI model works best
ChatGPT, Claude, and Gemini all produce useful results for this type of prompt. Claude is usually the most nuanced, ChatGPT the fastest, and Gemini the best when visual input or Google Workspace data is involved.
How to customize this prompt
Adapt the prompt to your specific use case. Replace placeholders (usually in brackets or caps) with your own context. The more detail you provide, the more precise the response.
Common use cases
- Use directly in ChatGPT, Claude, or Gemini
- Adapt to your specific project or industry
- Use as a starting point for your own custom prompt
- Compare across models to find the best fit for your case
- Share with your team as a standard workflow
Variations
Adapt the tone (more casual, more technical), change the output format (bullet points vs. paragraphs), or add constraints (word limits, target audience).
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