freight-email-parser

Monitor freight emails via Gmail IMAP or Microsoft Graph to classify and extract quotes, invoices, and carrier communications.

Updated Mar 4, 2026
One-click install
npx skills add https://github.com/wasay1200/freight-broker-ai --skill freight-email-parser
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: freight-email-parser
Source: https://github.com/wasay1200/freight-broker-ai/tree/main/skills/freight-email-parser
Command: npx skills add https://github.com/wasay1200/freight-broker-ai --skill freight-email-parser

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires flask, imap-tools, msal, transformers, torch, requests, python-dateutil, docling, and includes scripts (resource) and references (resource) components.

What problem does it solve?

Freight brokers spend excessive time monitoring inboxes, sifting through messages, and manually extracting structured data from quotes, carrier replies, PODs, and invoices. This skill automates that workflow to reduce manual effort and speed up operations.

Core Features & Use Cases

  • Email monitoring via Gmail IMAP and Outlook Graph to surface new messages and attachments.
  • Classification & extraction using HuggingFace zero-shot or regex to identify quote requests, carrier communications, PODs/BOL, and invoices and to extract key fields.
  • Automated replies and alerts by drafting emails, sending SMS summaries, and flagging overdue quotes for follow-up.
  • Use Case: A broker can receive a new quote request, extract origin/destination, equipment, and dates, and instantly push an SMS alert with a ready-to-send quote.

Quick Start

Run the main pipeline to poll the inbox, classify messages, extract data, and generate alerts, drafts, and reminders.

Frequently Asked Questions about freight-email-parser

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

FAQPage Schema
How do I automate parsing freight quotes and carrier emails from Gmail or Outlook?

Automate freight email parsing by connecting Gmail IMAP or Microsoft Graph to classify quote requests, carrier communications, PODs, and invoices, then extract origin, destination, and equipment data to generate SMS or email alerts.

Can I use a zero-shot classifier with regex fallback for freight email classification?

Yes, freight email classification supports HuggingFace zero-shot classifiers with a regex fallback mechanism to identify quote requests, BOLs, and invoices, ensuring accurate data extraction even when machine learning confidence is low.

How does automated freight inbox monitoring handle overdue quotes and carrier replies?

Automated freight inbox monitoring tracks carrier replies and flags overdue quotes for follow-up by maintaining state storage, generating actionable SMS summaries, and drafting ready-to-send email replies for brokers.

Do I need OAuth to connect Microsoft Outlook Graph for extracting freight invoices and PODs?

Yes, connecting Microsoft Outlook Graph requires optional OAuth-based account linking via a lightweight auth service to securely access inboxes and extract freight invoices, PODs, and carrier communications.

What is the best way to extract structured data from freight quote request emails?

The best way to extract structured data from freight quote emails is using a modular pipeline that combines zero-shot classification with dedicated quote extractors to pull origin, destination, equipment, and dates automatically.

What are the limitations of using regex fallback for classifying freight carrier communications?

Regex fallback for classifying freight carrier communications may struggle with highly variable email formats or unstructured text, making it less accurate than zero-shot classifiers for complex invoice or POD extraction.