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extract-invoice-data

Extract invoice data into structured JSON for ERP integrations.

2|Updated Mar 14, 2026
Search Tags:#data#json#document-processing#invoice#extract#structured
One-click install
npx skills add https://github.com/iterationlayer/skills --skill extract-invoice-data
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: extract-invoice-data
Source: https://github.com/iterationlayer/skills/tree/main/skills/extract-invoice-data
Command: npx skills add https://github.com/iterationlayer/skills --skill extract-invoice-data

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Invoices are often received in unstructured formats, requiring manual data entry to enable ERP and accounting systems.

Core Features & Use Cases

  • Vendor, invoice_number, date, line_items, and total_amount extraction from diverse invoice formats to structured JSON.
  • Multi-format input support including PDFs and images, with consistent field schemas for downstream processing.
  • ERP integration readiness with a clearly defined schema (vendor, invoice_number, date, line_items, total_amount) for automation.

Quick Start

Upload an invoice using the Iteration Layer API and receive a JSON payload with vendor, date, line_items, and total_amount.

Frequently Asked Questions about extract-invoice-data

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I extract invoice data into structured JSON for automated ERP integration?▼

To extract invoice data into structured JSON, you upload invoices via the API to receive a payload containing vendor, invoice_number, date, line_items, and total_amount. This defined schema enables direct automated ERP and accounting system integration.

What is the best way to parse vendor name and total amount from unstructured PDF invoices?▼

Parsing vendor name and total amount from unstructured PDF invoices is handled by multi-format input support that extracts these fields into a consistent JSON schema. This eliminates manual data entry for diverse invoice formats.

Can I process image-based invoices and get a consistent field schema for downstream processing?▼

Yes, you can process image-based invoices alongside PDFs using multi-format input support. The extraction returns a consistent field schema including vendor, date, line_items, and total_amount for reliable downstream processing.

Does invoice data extraction work with diverse invoice formats or do I need a fixed template?▼

Invoice data extraction works with diverse invoice formats without requiring a fixed template. It consistently extracts vendor, invoice_number, date, line_items, and total_amount into structured JSON for automated processing.

How do I handle invoice extraction errors when automated processing fails?▼

Handling invoice extraction errors is supported through clear error reporting provided by the API. When automated processing fails, the system returns error details to help you identify and resolve multi-format input issues.

What specific fields are included in the structured JSON when extracting invoice data?▼

The structured JSON includes vendor, invoice_number, date, line_items, and total_amount fields. This defined schema ensures consistent extraction results from diverse invoice formats for ERP integration readiness.

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