Invoice Processor Skill

Purpose

Automates the complete invoice processing workflow from upload to categorization, using OCR for scanned documents and LLM for intelligent field extraction and validation.

Triggers

• •User uploads an invoice document
• •Email with invoice attachment received
• •API integration sends invoice data
• •Manual invoice entry needs validation

Capabilities

1. •OCR Processing - Extract text from PDF, PNG, JPG invoice images
2. •Field Extraction - Identify vendor, amount, date, line items
3. •Data Validation - Verify required fields, check formats
4. •Duplicate Detection - Match against existing invoices
5. •Expense Categorization - Classify expenses to GL accounts
6. •Amount Verification - Verify line items sum to total

Instructions

Step 1: Document Parsing

If document is image or PDF:

1. •Use document-parser skill to extract text via OCR
2. •Receive raw text output

Step 2: Field Extraction

Extract required fields using LLM:

• •Vendor Name - Company issuing the invoice
• •Vendor Email/Address - Contact information
• •Invoice Number - Unique identifier
• •Invoice Date - Date invoice was issued
• •Due Date - Payment due date
• •Total Amount - Total amount due
• •Currency - Currency code (default USD)
• •Line Items - Array of:
  • •Description
  • •Quantity
  • •Unit Price
  • •Total Amount
  • •Category (if indicated)

Step 3: Validation

Validate extracted data:

• •All required fields present
• •Amounts are numeric and positive
• •Dates are valid and logical (due_date >= invoice_date)
• •Line items sum equals total amount (within $0.01 tolerance)
• •Invoice number not empty

Step 4: Duplicate Detection

Check for duplicates:

• •Match by vendor_name + invoice_number
• •Match by vendor_name + amount + invoice_date
• •If match found, flag as potential duplicate

Step 5: Expense Categorization

Categorize each line item:

• •Use LLM to classify description to standard categories
• •Categories: Office Supplies, Software, Cloud Services, Marketing, Travel, Equipment, Professional Services, Utilities, Rent, Insurance, etc.
• •Map to GL account codes if tenant has custom chart of accounts

Step 6: Structure Output

Return structured JSON:

{
  "vendor_name": "...",
  "vendor_email": "...",
  "invoice_number": "...",
  "invoice_date": "2026-01-15T00:00:00Z",
  "due_date": "2026-02-15T00:00:00Z",
  "amount": 50000,  // cents
  "currency": "USD",
  "line_items": [
    {
      "id": "uuid",
      "description": "...",
      "quantity": 10,
      "unit_price": 1500,  // cents
      "amount": 15000,  // cents
      "category": "Office Supplies"
    }
  ],
  "is_duplicate": false,
  "confidence_score": 0.95,
  "validation_errors": [],
  "suggested_approval_workflow": "auto_approve" // or "manual_review"
}

Error Handling

• •OCR Failed - Return error, suggest manual entry
• •Missing Required Fields - Flag fields, suggest manual completion
• •Validation Failed - Return specific validation errors
• •Duplicate Detected - Flag but allow manual override
• •Categorization Uncertain - Mark as "Uncategorized" for manual review

Integration Points

• •document-parser - For OCR processing
• •duplicate-detector (AP worker) - For duplicate checking
• •expense-categorizer (AP worker) - For GL coding
• •audit-trail - Log all processing actions

Models

• •OCR: Google Document AI
• •Field Extraction: Claude Sonnet 4
• •Categorization: Claude Sonnet 4 or Gemini 2.0 Flash

Security

• •Redact PII (SSN, credit card numbers) before LLM processing
• •Validate file types (PDF, PNG, JPG only)
• •Limit file size (< 10MB)
• •Sanitize output before storage

Invoke this skill when an invoice needs to be processed from upload to categorized data ready for approval.