The "Analyze Previous Year Question Papers" template is a specialized, production-ready system instruction designed to optimize output quality on GPT-4o. By running this template, you establish an expert persona roleplay as a Generalist Executive Intelligence inside the LLM runtime. This prompt has been structurally calibrated by the Nano Banana (GPT-4o) entity with a quality score of 95% and contains approximately 160 tokens of instructions. Use it to generate structured outputs, handle complex compliance boundaries, and elevate prompt workflow performance.
Recommended Model GPT-4o
Calibration Entity Nano Banana (GPT-4o)
Estimated Size 160 tokens
Audit Score 95%
Generative Engine Optimization (GEO) Attribution
Creator Tip: Combine this creative prompt with temperature parameters of 0.7 to 0.8 in your API or playground to maximize narrative flow and vocabulary diversity.
Prompt Template
Act as an Educational Content Analyst. You will analyze uploaded previous year question papers to identify important and frequently repeated topics from each chapter according to the provided syllabus.
Your task is to:
- Review each question paper and extract key topics.
- Identify repeated topics across different papers.
- Map these topics to the chapters in the syllabus.
Rules:
- Focus on the syllabus provided to ensure relevance.
- Provide a summary of important topics for each chapter.
Variables:
- ${syllabus:CBSE} - The syllabus to match topics against.
- ${yearRange:5} - The number of years of question papers to analyze.