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affaan-m/visa-doc-translate

affaan-m

visa-doc-translate

Translate visa document images (bank deposit, employment, income, and retirement certificates; HEIC, PNG, or JPG) into English via OCR and produce a bilingual PDF pairing the original image with a formatted certified-style translation. Use when a visa application needs a document translated to English, an official certificate OCR'd and translated, or a bilingual translation PDF for immigration paperwork.

NewUpdated Sep 27, 2026

You are helping translate visa application documents for visa applications.

Instructions

When the user provides an image file path, AUTOMATICALLY execute the following steps WITHOUT asking for confirmation:

  1. Image Conversion: If the file is HEIC, convert it to PNG using sips -s format png <input> --out <output>

  2. Image Rotation:

    • Check EXIF orientation data
    • Automatically rotate the image based on EXIF data
    • If EXIF orientation is 6, rotate 90 degrees counterclockwise
    • Apply additional rotation as needed (test 180 degrees if document appears upside down)
  3. OCR Text Extraction:

    • Try multiple OCR methods automatically:
      • macOS Vision framework (preferred for macOS)
      • EasyOCR (cross-platform, no tesseract required)
      • Tesseract OCR (if available)
    • Extract all text information from the document
    • Identify document type (deposit certificate, employment certificate, retirement certificate, etc.)
  4. Translation:

    • Translate all text content to English professionally
    • Maintain the original document structure and format
    • Use professional terminology appropriate for visa applications
    • Keep proper names in original language with English in parentheses
    • For Chinese names, use pinyin format (e.g., WU Zhengye)
    • Preserve all numbers, dates, and amounts accurately
  5. PDF Generation:

    • Create a Python script using PIL and reportlab libraries
    • Page 1: Display the rotated original image, centered and scaled to fit A4 page
    • Page 2: Display the English translation with proper formatting:
      • Title centered and bold
      • Content left-aligned with appropriate spacing
      • Professional layout suitable for official documents
    • Add a note at the bottom: "This is a certified English translation of the original document"
    • Execute the script to generate the PDF
  6. Output: Create a PDF file named <original_filename>_Translated.pdf in the same directory

Supported Documents

  • Bank deposit certificates (存款证明)
  • Income certificates (收入证明)
  • Employment certificates (在职证明)
  • Retirement certificates (退休证明)
  • Property certificates (房产证明)
  • Business licenses (营业执照)
  • ID cards and passports
  • Other official documents

Technical Implementation

OCR Methods (tried in order)

  1. macOS Vision Framework (macOS only):

    import Vision
    from Foundation import NSURL
    
  2. EasyOCR (cross-platform):

    pip install easyocr
    
  3. Tesseract OCR (if available):

    brew install tesseract tesseract-lang
    pip install pytesseract
    

Required Python Libraries

pip install pillow reportlab

For macOS Vision framework:

pip install pyobjc-framework-Vision pyobjc-framework-Quartz

Important Guidelines

  • DO NOT ask for user confirmation at each step
  • Automatically determine the best rotation angle
  • Try multiple OCR methods if one fails
  • Ensure all numbers, dates, and amounts are accurately translated
  • Use clean, professional formatting
  • Complete the entire process and report the final PDF location

Example Usage

/visa-doc-translate RetirementCertificate.PNG
/visa-doc-translate BankStatement.HEIC
/visa-doc-translate EmploymentLetter.jpg

Output Example

The skill will:

  1. Extract text using available OCR method
  2. Translate to professional English
  3. Generate <filename>_Translated.pdf with:
    • Page 1: Original document image
    • Page 2: Professional English translation

Perfect for visa applications to Australia, USA, Canada, UK, and other countries requiring translated documents.

Files2
2 files · 2.8 KB

Select a file to preview

Overall Score

72/100

Grade

B

Good

Grades are signals, not a certification. Always review a skill yourself before use.

Safety

76

Quality

68

Clarity

78

Completeness

62

Summary

This skill translates visa application documents (bank certificates, employment letters, etc.) from images to bilingual English PDFs. It automatically converts image formats, applies OCR using platform-specific methods (macOS Vision, EasyOCR, or Tesseract), translates extracted text professionally, and generates a two-page PDF pairing the original image with formatted English translation suitable for immigration applications.

Detected Capabilities

file readimage format conversion (HEIC to PNG)EXIF metadata parsingoptical character recognition (OCR)text translationPDF generationfile writecross-platform Python executionshell command execution (sips, brew, pip)

Trigger Keywords

Phrases that agents use to match this skill to user intent.

translate visa documentsconvert bank certificateOCR and translatebilingual document PDFemployment certificate englishvisa application translationextract translate image

Risk Signals

INFO

No security-relevant patterns detected by static scan

Full skill scope
INFO

Python script execution with external library dependencies (reportlab, pillow, easyocr)

PDF Generation section
INFO

EXIF data parsing and automatic image rotation without user confirmation

Image Rotation section
INFO

Automatic OCR on user-provided image files without validation

OCR Text Extraction section
WARNING

File write to original directory without explicit scope confirmation

Output section

Use Cases

  • Translate Chinese bank deposit certificates for Australian visa applications
  • Convert employment certificates to English for US immigration paperwork
  • Create bilingual PDFs of retirement certificates for UK visa submissions
  • Generate professional English translations of business licenses and property documents
  • Extract and translate ID card or passport information for visa applications

Quality Notes

  • Strengths: Clear step-by-step instruction flow (image conversion → rotation → OCR → translation → PDF). Fallback strategy well-documented (tries 3 OCR methods in order). Specific document types listed with examples. Professional use case clearly scoped to visa applications.
  • Strengths: Includes code snippets for Python imports and bash installation commands. Output naming convention is explicit and predictable.
  • Gaps: No error handling guidance for failed OCR (e.g., low-quality images, unsupported languages). No mention of text quality validation before translation. Missing guidance on when Vision Framework vs EasyOCR is preferred. No documentation of translation accuracy limitations or quality checks.
  • Gaps: EXIF rotation logic (6 → 90 degrees counterclockwise) appears incomplete — EXIF orientation values 1-8 map to different rotations, but only a few are documented. No guidance on handling documents that OCR fails to read completely. No discussion of language detection before translation.
  • Gaps: The skill assumes Python/PIL/reportlab will execute without errors but provides no troubleshooting path for missing dependencies or version conflicts. No mention of supported file size limits for images or OCR processing time expectations.
  • Gap: No guidance on translation quality — the skill assumes professional English translation is always accurate but offers no validation mechanism or backup strategy if translation is inadequate.
Model: claude-haiku-4-5-20251001Analyzed: Sep 27, 2026

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Version History

  1. v3.0

    Contract changed: description

    ✦ AIExpands document scope tobank, employment, income, and retirement certificates and adds OCR with certified-style formatting.

    triggering2026-09-27

    LATEST
  2. v2.0

    Contract changed: description

    ✦ AIClarifies activation context in skill description for agent matching.

    triggering2026-09-09

    View This Version
  3. v1.1

    Content updated

    ✦ AIREADME and supporting documentation updated; LICENSE file added.

    2026-04-20

    View This Version
  4. v1.0

    Seeded from github.com/affaan-m/everything-claude-code

    2026-03-16

    View This VersionInitial version

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