python3 -c " from docx import Document doc = Document('/tmp/workspace/attachments/342d8258-1ff8-4ae6-98ae-a62dfd5c7fd5/MY WORD.docx') for i, p in enumerate(doc.paragraphs): style = p.style.name if p.style else 'None' if p.text.strip(): print(f'[{i}][{style}] {p.text}') "

python3 -c " from docx import Document doc = Document('/tmp/workspace/attachments/342d8258-1ff8-4ae6-98ae-a62dfd5c7fd5/MY WORD.docx') for i, table in enumerate(doc.tables): print(f'--- Table {i} ---') for row in table.rows: for cell in row.cells: txt = cell.text.strip() if txt: print(f' CELL: {txt[:200]}') "

ls -la /tmp/workspace/ && mkdir -p /tmp/workspace/prakriti-migraine/

python3 /tmp/skills/docx/scripts/office/unpack.py "/tmp/workspace/attachments/342d8258-1ff8-4ae6-98ae-a62dfd5c7fd5/MY WORD.docx" /tmp/workspace/prakriti-migraine/unpacked/

python3 << 'EOF' # Read the document.xml and find all relevant strings to replace with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() import re # Find all text nodes that contain "association" (case insensitive) to understand context # We'll search for the surrounding text for match in re.finditer(r'[^<]{0,80}association[^<]{0,80}', content, re.IGNORECASE): print(repr(match.group())) print("---") EOF

python3 << 'PYEOF' import re with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() original = content # ── 1. Title lines (cover page) ────────────────────────────────────────────── # " and its association with" + next run "Migraine - A cross-sectional..." # The title is split across two <w:t> elements: # Run 1: "Assessment of Deha Prakriti and its association with" # Run 2: "Migraine - A cross-sectional observational study" # We want the title to be a single run: "Assessment of Deha Prakriti in Migraine - A cross-sectional observational study" # but it may span two paragraphs. We'll handle each occurrence separately. # Cover page title (paragraphs 0 & 1 in python-docx output) # Run texts seen in XML: # " and its association with" → " in" content = content.replace( '> and its association with</w:t>', '> in</w:t>' ) # ── 2. Quoted title in letter body (paragraph 51) ──────────────────────────── # "Assessment of Deha Prakriti and its association with Migraine - A cross-sectional observational study" content = content.replace( 'Assessment of Deha Prakriti and its association with Migraine - A cross-sectional observational study&#x201D;', 'Assessment of Deha Prakriti in Migraine - A cross-sectional observational study&#x201D;' ) # ── 3. Quoted title in proforma list (paragraph 66) ───────────────────────── # Same string appears again (there are 2 occurrences handled above already by replace-all, # but let's be safe – the replace above will catch both) # ── 4. Table 0 – Purpose cell ──────────────────────────────────────────────── content = content.replace( 'To assess the Deha Prakriti and its association with migraine.', 'To assess the Deha Prakriti in patients diagnosed with Migraine.' ) # ── 5. Table 2 – title cell ────────────────────────────────────────────────── # " and its association with" already replaced in step 1 above (covers table 2 as well) # ── 6. Significance section – Personalized Management sentence ─────────────── # Keep "association" in body text where it refers to OTHER studies or general usage # Only remove it where it refers to THIS study's own framing # "Understanding this association will aid physicians..." → reframe content = content.replace( 'Personalized Management: Understanding this association will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (Ahara) and lifestyle (Vihara) modifications for migraine patients.', 'Personalized Management: Understanding the predominant Deha Prakriti in migraine patients will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (Ahara) and lifestyle (Vihara) modifications.' ) # ── 7. Need of study – "Proving its association with migraines" ────────────── content = content.replace( 'Proving its association with migraines provides a highly accessible screening tool suitable for primary healthcare and resource-limited settings.', 'Identifying the predominant Deha Prakriti in migraine patients provides a highly accessible screening tool suitable for primary healthcare and resource-limited settings.' ) # ── 8. Research Question ───────────────────────────────────────────────────── content = content.replace( 'What is the distribution and association of Deha Prakriti among patients diagnosed with Migraine?', 'What is the distribution of Deha Prakriti among patients diagnosed with Migraine?' ) # ── 9. Null Hypothesis ─────────────────────────────────────────────────────── content = content.replace( 'There is no significant association between Deha Prakriti and Migraine.', 'There is no significant difference in the distribution of Deha Prakriti among patients diagnosed with Migraine.' ) # ── 10. Alternative Hypothesis ─────────────────────────────────────────────── content = content.replace( 'There is a significant association between Deha Prakriti and Migraine.', 'There is a significant difference in the distribution of Deha Prakriti among patients diagnosed with Migraine.' ) # ── 11. Aim ────────────────────────────────────────────────────────────────── content = content.replace( 'To find an association between Deha Prakriti and Migraine.', 'To assess Deha Prakriti in patients diagnosed with Migraine.' ) # ── 12. Expected Outcome – secondary ───────────────────────────────────────── content = content.replace( 'The study is expected to demonstrate a statistically significant association between Deha Prakriti and the prevalence and severity of Migraine. These findings may support the role of Deha Prakriti in individualized and preventive management Migraine.', 'The study is expected to demonstrate the predominant Deha Prakriti type and its relationship with the frequency, severity, duration, and disability burden of Migraine. These findings may support the role of Deha Prakriti in individualized and preventive management of Migraine.' ) # ── 13. Scope point 2 – "To study the association between..." ──────────────── content = content.replace( 'To study the association between Deha Prakriti and the clinical profile of migraine, including frequency, duration, severity (VAS), associated symptoms, and disability (MIDAS score).', 'To study the distribution and predominance of Deha Prakriti types and their relationship with the clinical profile of migraine, including frequency, duration, severity (VAS), associated symptoms, and disability (MIDAS score).' ) # ── 14. Limitations para – "it can identify associations only and cannot establish a causal relationship" ── # This is actually an accurate methodological statement for a cross-sectional study; keep it but rephrase slightly content = content.replace( 'Being a cross-sectional observational study, it can identify associations only and cannot establish a causal relationship between Deha Prakriti and migraine.', 'Being a cross-sectional observational study, it can describe the distribution of Deha Prakriti in migraine patients but cannot establish a causal relationship between Deha Prakriti and migraine.' ) # ── 15. "Therefore, further research is needed to generate evidence regarding the association between" ── content = content.replace( 'Therefore, further research is needed to generate evidence regarding the association between ', 'Therefore, further research is needed to generate evidence regarding the relationship between ' ) # ── 16. Rationale para – last sentence ─────────────────────────────────────── content = content.replace( 'Despite the clinical importance of this correlation, there is a paucity of observational studies specifically assessing Deha Prakriti in diagnosed migraine patients using validated tools.', 'Despite the clinical importance of this subject, there is a paucity of observational studies specifically assessing Deha Prakriti in diagnosed migraine patients using validated tools.' ) # ── 17. Significance – Predictive Screening ────────────────────────────────── # "By establishing a correlation between specific Prakritis...and migraines, the study will help identify..." # Keep this as it's about prakriti distribution / susceptibility, not "association" word # ── Verify changes count ────────────────────────────────────────────────────── changed = sum(1 for a, b in zip(original, content) if a != b) print(f"Characters changed: {changed}") print(f"Original length: {len(original)}, New length: {len(content)}") with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'w', encoding='utf-8') as f: f.write(content) print("document.xml written successfully") PYEOF

python3 /tmp/skills/docx/scripts/office/unpack.py --repack /tmp/workspace/prakriti-migraine/unpacked/ "/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx" 2>&1 # Also try the standard zip approach if that script doesn't exist ls /tmp/skills/docx/scripts/office/

python3 /tmp/skills/docx/scripts/office/pack.py /tmp/workspace/prakriti-migraine/unpacked/ "/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx"

python3 -c " from docx import Document doc = Document('/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx') # Print key paragraphs to verify all changes check_indices = [0, 1, 51, 66, 83, 157, 161, 165, 170, 172, 180, 182, 183] for i, p in enumerate(doc.paragraphs): if i in check_indices or ('association' in p.text.lower() and 'other' not in p.text.lower()[:5]): print(f'[{i}] {p.text[:200]}') print() # Check tables print('--- Tables ---') for i, table in enumerate(doc.tables): for row in table.rows: for cell in row.cells: txt = cell.text.strip() if txt and i in [0, 2]: print(f'Table {i}: {txt[:200]}') "

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() # These strings didn't match because of XML encoding / different whitespace - let's find exact strings import re # Find paragraph 51 - the quoted title with smart quotes snippets = [ 'Assessment of Deha Prakriti and its association with Migraine', 'its association with migraine', 'association with Migraine', 'association with migraine', 'distribution and association of', 'Understanding this association will aid', ] for s in snippets: count = content.count(s) print(f"Found {count} occurrences of: {s!r}") PYEOF

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() # Fix remaining instances content = content.replace( 'association with Migraine - A cross-sectional observational study', 'in Migraine - A cross-sectional observational study' ) content = content.replace( 'its association with migraine.', 'Deha Prakriti in patients diagnosed with Migraine.' ) content = content.replace( 'distribution and association of Deha Prakriti among patients diagnosed with Migraine?', 'distribution of Deha Prakriti among patients diagnosed with Migraine?' ) content = content.replace( 'Understanding this association will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (Ahara) and lifestyle (Vihara) modifications for migraine patients.', 'Understanding the predominant Deha Prakriti in migraine patients will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (Ahara) and lifestyle (Vihara) modifications.' ) with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'w', encoding='utf-8') as f: f.write(content) print("Fixed. Checking remaining 'association' references related to THIS study...") import re for match in re.finditer(r'[^<]{0,100}association[^<]{0,100}', content, re.IGNORECASE): txt = match.group() # Skip references to other studies if any(x in txt for x in ['Dr.', 'Chowdhury', 'Previous studies', 'nausea', 'cross-section']): continue print(repr(txt)) print("---") PYEOF

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() # These two didn't match because of whitespace differences in the XML - find exact surrounding context import re # Find "Understanding this association" in full XML context for m in re.finditer(r'.{0,30}Understanding this association.{0,80}', content): print(repr(m.group())) print() for m in re.finditer(r'.{0,30}distribution and association of.{0,80}', content): print(repr(m.group())) print() PYEOF

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() # The text runs are split at different positions in XML - replace the exact strings found content = content.replace( '<w:t>Personalized Management: Understanding this association will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (Ahara) and lifestyle (Vihara) modifications for migraine patients.</w:t>', '<w:t>Personalized Management: Understanding the predominant Deha Prakriti in migraine patients will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (Ahara) and lifestyle (Vihara) modifications.</w:t>' ) content = content.replace( 'What is the distribution and association of </w:t>', 'What is the distribution of </w:t>' ) with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'w', encoding='utf-8') as f: f.write(content) # Verify no study-specific "association" remains import re remaining = [] for m in re.finditer(r'[^<]{0,80}association[^<]{0,80}', content, re.IGNORECASE): txt = m.group() if not any(x in txt for x in ['Dr.', 'Chowdhury', 'Previous studies', 'nausea', 'cross-section', 'associations in', 'associations between']): remaining.append(txt) if remaining: print("Still remaining:") for r in remaining: print(repr(r)) print() else: print("All study-specific 'association' references cleaned up!") PYEOF

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() import re # Get the full XML element for this problematic run m = re.search(r'<w:t>[^<]*Personalized Management: Understanding this association[^<]*</w:t>', content) if m: print("FOUND:", repr(m.group())) # Also show what's around it start = max(0, m.start()-200) end = min(len(content), m.end()+200) print("CONTEXT:", repr(content[start:end])) else: print("Not found with simple pattern, searching broader...") m2 = re.search(r'Personalized Management.{0,200}', content) if m2: print(repr(m2.group())) PYEOF

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() # The run is split mid-sentence. Replace just the first run's text content = content.replace( '<w:t>Personalized Management: Understanding this association will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (</w:t>', '<w:t>Personalized Management: Understanding the predominant Deha Prakriti in migraine patients will aid physicians in designing tailored preventive and therapeutic strategies, including specific dietary (</w:t>' ) with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'w', encoding='utf-8') as f: f.write(content) import re remaining = [] for m in re.finditer(r'[^<]{0,80}association[^<]{0,80}', content, re.IGNORECASE): txt = m.group() if not any(x in txt for x in ['Dr.', 'Chowdhury', 'Previous studies', 'nausea', 'cross-section', 'associations in', 'associations between']): remaining.append(txt) if remaining: print("Still remaining:") for r in remaining: print(repr(r)) else: print("All cleaned! Now repacking...") # Repack import subprocess result = subprocess.run( ['python3', '/tmp/skills/docx/scripts/office/pack.py', '/tmp/workspace/prakriti-migraine/unpacked/', '/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx'], capture_output=True, text=True ) print(result.stdout) print(result.stderr) PYEOF

python3 -c " from docx import Document doc = Document('/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx') # Final verification of all key paragraphs key = {0, 1, 51, 66, 90, 157, 161, 165, 170, 180, 183} for i, p in enumerate(doc.paragraphs): if i in key: print(f'[{i}] {p.text[:220]}') print() # Table 0 Purpose cell print('--- Table 0 Purpose ---') t0 = doc.tables[0] for row in t0.rows: if 'Purpose' in row.cells[0].text: print(row.cells[1].text) # Table 2 title print('--- Table 2 Title ---') print(doc.tables[2].rows[0].cells[0].text) "

python3 << 'PYEOF' with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'r', encoding='utf-8') as f: content = f.read() import re # Fix "and its in Migraine" → "in Migraine" (paragraphs 51 & 66 quoted titles) content = content.replace('and its in Migraine', 'in Migraine') # Fix Table 0 Purpose - "To assess the Deha Prakriti and Deha Prakriti in patients diagnosed with Migraine." content = content.replace( 'To assess the Deha Prakriti and Deha Prakriti in patients diagnosed with Migraine.', 'To assess the Deha Prakriti in patients diagnosed with Migraine.' ) with open('/tmp/workspace/prakriti-migraine/unpacked/word/document.xml', 'w', encoding='utf-8') as f: f.write(content) # Repack import subprocess result = subprocess.run( ['python3', '/tmp/skills/docx/scripts/office/pack.py', '/tmp/workspace/prakriti-migraine/unpacked/', '/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx'], capture_output=True, text=True ) print(result.stdout) # Final verification from docx import Document doc = Document('/tmp/workspace/prakriti-migraine/Assessment_of_Deha_Prakriti_in_Migraine.docx') key = {0, 1, 51, 66} for i, p in enumerate(doc.paragraphs): if i in key: print(f'[{i}] {p.text[:220]}') print() t0 = doc.tables[0] for row in t0.rows: if 'Purpose' in row.cells[0].text: print("Table 0 Purpose:", row.cells[1].text) print("Table 2 Title:", doc.tables[2].rows[0].cells[0].text) PYEOF