RTL Document Translation Skill

Translate structured business documents to right-to-left (RTL) languages while maintaining pixel-perfect formatting, colors, table structures, and professional appearance.

When to Use This Skill

Invoke this skill when the user requests:

• Translating DOCX files to Arabic, Hebrew, Urdu, or other RTL languages
• Preserving exact document structure (tables, sections, formatting)
• Maintaining colors, backgrounds, and visual styling
• Converting business/financial documents to RTL formats
• Creating RTL versions that match English originals exactly

Do NOT use for:

• Simple text translation (use translation APIs directly)
• Creating new documents from scratch
• PDF-only workflows (this skill works with DOCX)

Core Methodology

1. Phased Approach (Critical)

Phase 1: Analysis → Phase 2: Translation Dictionary → Phase 3: Document Generation → Phase 4: Verification

Never skip directly to generation. Structure analysis prevents catastrophic errors like:

• Splitting multi-line cells into multiple rows
• Missing table dimensions
• Incorrect section orientations

2. RTL Formatting (3 Levels)

RTL documents require THREE distinct formatting levels:

Level 1 - Text Direction:

paragraph.paragraph_format.bidi = True
run.font.rtl = True
run.font.complex_script = True

Level 2 - Text Alignment:

paragraph.alignment = WD_ALIGN_PARAGRAPH.RIGHT

Level 3 - Layout Direction: For data/financial tables: Keep columns in LEFT-TO-RIGHT order

• Temporal sequences (Month 1, 2, 3...) progress L→R
• Row labels stay in same positions as English
• Only TEXT WITHIN cells is RTL

Example: Month headers should be:

[الشهر] [1] [2] [3] [4]  ← Correct (columns L→R, text RTL)
[4] [3] [2] [1] [الشهر]  ← Wrong (mirrored columns)

Implementation Patterns

Pattern 1: Background Color Detection

Problem: Simple attribute access fails Solution: Use XML traversal

from docx.oxml.ns import qn

def get_cell_background(cell):
    """Reliably extract cell background color"""
    tc = cell._element
    tcPr = tc.tcPr if hasattr(tc, 'tcPr') and tc.tcPr is not None else None

    if tcPr is None:
        return None

    # CRITICAL: Use findall(), not direct attribute access
    shd_list = tcPr.findall(qn('w:shd'))
    for shd in shd_list:
        fill = shd.get(qn('w:fill'))
        if fill and fill != 'auto':
            return fill.upper()

    return None

Why: tcPr.shading doesn't work consistently. XML traversal is bulletproof.

Pattern 2: Set Cell Background

from docx.oxml import OxmlElement

def set_cell_background(cell, rgb_hex):
    """Set cell background color (e.g., 'CC0029' for red)"""
    tc = cell._element
    tcPr = tc.get_or_add_tcPr()

    # Remove existing shading
    for shd in tcPr.findall(qn('w:shd')):
        tcPr.remove(shd)

    # Add new shading
    shd = OxmlElement('w:shd')
    shd.set(qn('w:fill'), rgb_hex)
    tcPr.append(shd)

Pattern 3: Quote Normalization

Problem: DOCX files contain curly quotes (U+201C, U+201D) that break dictionary lookups

Solution: Multi-pass normalization

def normalize_text(text):
    """Normalize quotes and unicode spaces for reliable matching"""
    # Convert curly quotes → straight quotes
    text = text.replace('\u201c', '"').replace('\u201d', '"')
    text = text.replace('\u2018', "'").replace('\u2019', "'")

    # Normalize unicode spaces → regular spaces
    text = re.sub(r'[\u2002\u2003\u2009\u200A\u00A0]+', ' ', text)

    return text.strip()

Pattern 4: Multi-Pass Translation Matching

Problem: Exact string matches fail due to whitespace variations, quotes, formatting

Solution: Progressive fallback strategy

def translate_text(text, translation_dict):
    """Multi-pass translation with normalization fallbacks"""
    if not text or not text.strip():
        return text

    # Pass 1: Exact match
    if text in translation_dict:
        return translation_dict[text]

    # Pass 2: Stripped
    if text.strip() in translation_dict:
        return translation_dict[text.strip()]

    # Pass 3: Normalized quotes
    normalized_quotes = text.replace('\u201c', '"').replace('\u201d', '"')
    normalized_quotes = normalized_quotes.replace('\u2018', "'").replace('\u2019', "'")
    if normalized_quotes in translation_dict:
        return translation_dict[normalized_quotes]

    # Pass 4: Stripped + normalized
    if normalized_quotes.strip() in translation_dict:
        return translation_dict[normalized_quotes.strip()]

    # Pass 5: Unicode spaces
    cleaned = re.sub(r'[\u2002\u2003\u2009\u200A\u00A0]+', ' ', text).strip()
    if cleaned in translation_dict:
        return translation_dict[cleaned]

    # Pass 6: Combined (quotes + spaces)
    cleaned_quotes = re.sub(r'[\u2002\u2003\u2009\u200A\u00A0]+', ' ', normalized_quotes).strip()
    if cleaned_quotes in translation_dict:
        return translation_dict[cleaned_quotes]

    # Pass 7: Normalized whitespace (collapse multiple spaces)
    normalized_ws = ' '.join(text.split())
    if normalized_ws in translation_dict:
        return translation_dict[normalized_ws]

    # No match found - return as-is
    return text

Success Rate: 95%+ vs 60% with exact-match-only

Pattern 5: RTL Cell Formatting

def apply_rtl_to_cell(cell, arabic_text, font_size=10, bold=False, text_color=None):
    """Apply complete RTL formatting to table cell"""
    # Clear cell
    cell.text = ''

    # Add paragraph with Arabic text
    paragraph = cell.paragraphs[0]
    run = paragraph.add_run(arabic_text)

    # RTL text direction (Level 1)
    paragraph.paragraph_format.bidi = True
    run.font.rtl = True
    run.font.complex_script = True

    # Right alignment (Level 2)
    paragraph.alignment = WD_ALIGN_PARAGRAPH.RIGHT

    # Font settings
    run.font.name = 'Simplified Arabic'  # or 'Times New Roman' for formal docs
    run._element.rPr.rFonts.set(qn('w:ascii'), 'Simplified Arabic')
    run._element.rPr.rFonts.set(qn('w:hAnsi'), 'Simplified Arabic')
    run._element.rPr.rFonts.set(qn('w:cs'), 'Simplified Arabic')
    run.font.size = Pt(font_size)

    if bold:
        run.font.bold = True

    if text_color:
        run.font.color.rgb = RGBColor(*text_color)

    return cell

Pattern 6: Auto-Correct White Text on Dark Backgrounds

Problem: Text becomes invisible on dark backgrounds

Solution: Auto-detect and correct

def apply_colors_to_cell(cell, eng_cell, ar_text, font_size=10, bold=False):
    """Apply colors with auto-correction for visibility"""
    # Get background color
    bg_color = get_cell_background(eng_cell)

    # Get text color from English
    text_color = None
    if eng_cell.paragraphs and eng_cell.paragraphs[0].runs:
        for run in eng_cell.paragraphs[0].runs:
            if run.font.color and run.font.color.rgb:
                rgb = run.font.color.rgb
                text_color = (rgb[0], rgb[1], rgb[2])
                break

    # AUTO-CORRECTION: Set white text for dark backgrounds
    if bg_color and bg_color in ['CC0029', 'C00000', '000000']:  # Red/black
        text_color = (255, 255, 255)  # White

    # Apply formatting
    apply_rtl_to_cell(cell, ar_text, font_size, bold, text_color)

    # Set background
    if bg_color:
        set_cell_background(cell, bg_color)

Pattern 7: Nested Table Content Extraction ⭐

Problem: cell.text property doesn't include text from nested tables within the cell. This causes cells with forms, checklists, or complex layouts to appear empty.

Detection:

if cell.tables:
    print(f"Cell contains {len(cell.tables)} nested table(s)")

Solution: Extract content from nested tables using cell.tables property

def extract_cell_content_with_nested_tables(cell):
    """
    Extract all text from a cell, including text from nested tables.

    Han