These are all the Class 10 cbse pyq of different years and different sets. List out the important and most frequemt asked question according to index of the chapter provided. Provide frequency chart too. Analyze all the question from all the pdf and pyq.

I'll analyze all the CBSE Science question papers to identify the most frequent and important questions by chapter. Let me start by reading through the PDFs.
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I need to extract and analyze all these PDFs. Since they're large, I'll use the PDF skill to process them efficiently.
Reading File
I'll extract and analyze all the PDFs to identify the most frequent questions by chapter. Let me process them systematically.I understand this is a large-scope analysis task. Let me first extract and analyze all the PDFs to provide you with a comprehensive breakdown, then I'll ask which specific areas you'd like to explore in detail.
Running Command

cd /tmp/workspace && python3 << 'EOF' import pdfplumber import os from collections import defaultdict import json # List of all PDF files pdf_files = [ "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience2025_set1_Questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience2025_set2_Questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience2023_set3_Questionpaper .pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience_2022_set2_questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience_2022_set3_questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience_2020_Set3_Questionpaper .pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/31-2-3_Science.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/5b299d09-bfc2-47e5-a526-3e0fefa97830.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/74f0c34a-f1d2-4038-999c-c8246feeaec0.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/29a16b10-de8a-44d2-8aff-376781d7a5af.pdf", ] all_text = {} # Extract text from all PDFs for pdf_file in pdf_files: if os.path.exists(pdf_file): try: with pdfplumber.open(pdf_file) as pdf: text = "" for page in pdf.pages: text += page.extract_text() or "" all_text[os.path.basename(pdf_file)] = text print(f"✓ Extracted: {os.path.basename(pdf_file)}") except Exception as e: print(f"✗ Error extracting {os.path.basename(pdf_file)}: {e}") else: print(f"✗ File not found: {pdf_file}") # Save all extracted text for analysis with open("/tmp/workspace/extracted_questions.json", "w") as f: json.dump(all_text, f) print(f"\n✓ Total PDFs processed: {len(all_text)}") EOF

I'll analyze all the CBSE Science question papers to identify the most frequent and important questions by chapter. Let me start by reading through the PDFs.I need to extract and analyze all these PDFs. Since they're large, I'll use the PDF skill to process them efficiently.I'll extract and analyze all the PDFs to identify the most frequent questions by chapter. Let me process them systematically.I understand this is a large-scope analysis task. Let me first extract and analyze all the PDFs to provide you with a comprehensive breakdown, then I'll ask which specific areas you'd like to explore in detail.
!

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These are all the Class 10 cbse pyq of different years and different sets. List out the important and most frequemt asked question according to index of the chapter provided. Provide frequency chart too. Analyze all the question from all the pdf and pyq.

Let me process all the PDFs systematically to extract and analyze the questions.
Running Command

cd /tmp/workspace && python3 << 'EOF' import pdfplumber import os from collections import defaultdict # List of all PDF files pdf_files = [ "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience2025_set1_Questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience2025_set2_Questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience2023_set3_Questionpaper .pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience_2022_set2_questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience_2022_set3_questionpaper.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/CBSEScience_2020_Set3_Questionpaper .pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/31-2-3_Science.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/5b299d09-bfc2-47e5-a526-3e0fefa97830.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/74f0c34a-f1d2-4038-999c-c8246feeaec0.pdf", "/tmp/workspace/attachments/ef3e71e8-3f36-4496-8f60-bb6bda08c980/29a16b10-de8a-44d2-8aff-376781d7a5af.pdf", ] all_content = "" # Extract text from all PDFs for pdf_file in pdf_files: if os.path.exists(pdf_file): try: with pdfplumber.open(pdf_file) as pdf: for page in pdf.pages: text = page.extract_text() if text: all_content += text + "\n\n" print(f"✓ {os.path.basename(pdf_file)}") except Exception as e: print(f"✗ {os.path.basename(pdf_file)}: {e}") # Save to file for analysis with open("/tmp/workspace/all_questions.txt", "w", encoding="utf-8") as f: f.write(all_content) print(f"\n✓ Total text extracted: {len(all_content)} characters") print(f"Saved to: /tmp/workspace/all_questions.txt") EOF

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