| name | accounting-skill |
| description | Process accounting documents — invoices (hóa đơn GTGT), purchase orders, and bank statements. Extract structured data from PDF (digital and scanned), JPG, and PNG files using OCR. Output Excel tracking sheets and JSON backups. Classify unknown documents and route to the correct extractor. Supports Vietnamese and international formats. Use when asked to extract, process, classify, or track invoices, POs, bank statements, or accounting documents.
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Accounting Skill
Extract structured data from accounting documents (invoices, POs, bank statements) into Excel tracking sheets with JSON backups. Handles digital PDFs, scanned PDFs, and images via automatic OCR.
Prerequisites
Install system OCR dependencies before first use. See {baseDir}/references/ocr-setup.md for full guide.
sudo apt install tesseract-ocr tesseract-ocr-vie poppler-utils
uv run {baseDir}/scripts/ocr_utils.py check
Quick Start
1. Classify an unknown document
uv run {baseDir}/scripts/classify_document.py /path/to/document.pdf
Returns JSON with type (invoice / po / statement / other), confidence, and a ready-to-run extraction command.
2. Extract an invoice
uv run {baseDir}/scripts/extract_invoice.py /path/to/invoice.pdf -o invoice_tracking.xlsx
Appends to the Excel tracking sheet. Use --dry-run to preview parsed data without writing.
3. Extract a bank statement
uv run {baseDir}/scripts/extract_statement.py /path/to/statement.pdf
Creates statement_{bank}_{date}.xlsx with transactions. Use -o to specify output path.
4. Extract a purchase order
uv run {baseDir}/scripts/extract_po.py /path/to/po.pdf -o po_tracking.xlsx
Tracks delivery dates and flags overdue/urgent POs.
5. Generate empty Excel templates
uv run {baseDir}/scripts/generate_templates.py all -o ~/accounting/
Creates blank tracking sheets: invoice_tracking.xlsx, po_tracking.xlsx, statement_template.xlsx.
Common Options (all extractors)
| Flag | Description |
|---|
--format excel|json|both | Output format (default: both) |
--dry-run | Parse and validate only, print JSON to stdout |
--json-dir DIR | Directory for JSON backup files |
-o FILE | Output Excel file path |
Workflow
Single Document
File → classify_document.py → route → extract_*.py → Excel + JSON
Batch Processing
For a folder of mixed documents, classify first, then route:
for f in /path/to/docs/*; do
uv run {baseDir}/scripts/classify_document.py "$f" --output-dir ~/accounting/
done
Then run the suggested extraction commands from each classification result.
OCR Strategy
All scripts share {baseDir}/scripts/ocr_utils.py which auto-selects the best extraction method:
- Digital PDFs → pdfplumber (fast, no OCR needed)
- Scanned PDFs → pdf2image + pytesseract at 300 DPI (fallback when pdfplumber gets <50 chars/page)
- Images (JPG/PNG/TIFF) → pytesseract with grayscale preprocessing
Each result includes ocr_confidence and extraction_confidence percentages. Documents below 85% are automatically flagged needs_review.
Validation Rules
- Invoices: Subtotal + VAT = Total (auto-checks math), duplicate detection by invoice number + vendor
- Bank statements: Opening balance + credits − debits = closing balance
- POs: Delivery date tracking with overdue/urgent alerts
Reference Documents
Read these for field schemas, Vietnamese format details, and validation logic:
{baseDir}/references/invoice-fields.md — Vietnamese VAT invoice fields, tax rates, patterns{baseDir}/references/bank-formats.md — Vietnamese bank names, transaction formats, amount patterns{baseDir}/references/po-fields.md — PO fields, delivery status logic, payment terms{baseDir}/references/ocr-setup.md — OCR installation, troubleshooting, confidence scoring
