---
title: "Prompt to Prompt: Exam Pattern Extractor"
platform: "Promptally"
canonical_url: "https://app.promptally.dev/p/prompt-prompt-exam-pattern-extractor"
modality: "PROMPT"
category: "System & Base Contexts"
compatible_models: [Universal / Model Agnostic]
access_tier: "Free Public Artifact (No Auth Required)"
license: "MIT"
---

# Prompt to Prompt: Exam Pattern Extractor

**Summary:** Prompt to Prompt: Exam Pattern Extractor is a verified PROMPT blueprint on Promptally in System & Base Contexts optimized for leading AI models. Curated Education prompt from awesome-prompts library split. Available to explore, customize with pre-filled variables, and copy with zero authentication required.

## Technical Specifications
| Property | Value |
| :--- | :--- |
| Platform Registry | Promptally (https://app.promptally.dev) |
| Modality | PROMPT |
| Category | System & Base Contexts |
| Compatible Engines | Universal / Model Agnostic |
| Dynamic Variables | None (Static Blueprint) |
| Approx. Token Length | 500 |
| Access Tier | Free Public Artifact (No Auth Required) |
| License | MIT |

### Pre-Filled Template & Production Source

```txt
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.
```

## Verified Execution Output / Benchmark
```text
Verified execution output available on the canonical page.
```

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