This repository serves as the central source of truth for our Zapier automations. It is organized into subfolders representing different business domains (such as Orders, Fulfillment, or Invoicing), with each JSON file containing the configuration and metadata for a single Zap.

Use this guide to understand how the repository is structured, how to trace data mutations across an order's lifecycle, and how to read the documentation for individual Zaps.

Repository Organization

The repository is divided into subfolders based on the core monday.com board or business process the Zaps operate on.

Each JSON file represents a complete Zap export. When you need to understand a workflow, locate the corresponding JSON file and its accompanying documentation.

Tracing Data Modifications

To answer the question, "What changes column X across the lifecycle of an order?", refer to the data mapping tables maintained in each subfolder. Because Zaps operate linearly, identifying the modifying Zap is the first step in troubleshooting.

Here is an example of how data points on the Orders board map to their modifying Zaps:

Anatomy of a Zap Document

Every Zap in this repository is documented using a standardized format to help you quickly understand its purpose, its pipeline, and the specific fields it reads or writes.

Using the NOE Address Fixer as an example, here is how to read a Zap's documentation:

1. Executive Summary

This section defines the core objective. For example, the NOE Address Fixer takes messy address text from the Orders board, runs it through a Python parser to normalize the formatting, geocodes it via Google Maps, and pushes the corrected values (and coordinates) back to the monday.com item.

2. Workflow Pipeline

A visual breakdown of the Zap's execution order. Zaps are linear; understanding the sequence of operations helps pinpoint where data might be failing.

flowchart TD
    A["1: Catch Hook (monday.com ID)"] --> B["2: Get Column Values (monday.com)"]
    B --> C["3: Format Address (Python)"]
    C --> D["4: Get Lat/Long (Google Geocoding)"]
    D --> E["5: Change Multiple Columns (monday.com)"]

3. Step-by-Step Breakdown

This section details exactly what happens at each node in the pipeline, including API calls, code execution, and data transformations.

1. 1

   Trigger: Catch Hook

   Expects a raw webhook payload containing a monday.com item/pulse ID (event.pulseId).

2. 2

   Read: Get Column Values

   Looks up the Orders board item matching the pulseId and reads the raw address text stored in column text_mky5xz73.

3. 3

   Process: Format Address (Python)

   Strips control characters, splits the string into components, expands abbreviations (e.g., Ave → Avenue), applies smart title-casing, and extracts unit numbers. Returns a structured JSON object.

4. 4

   Enrich: Google Geocoding API

   Sends the cleaned address to maps.googleapis.com (restricted to US/NC) to retrieve resolved latitude and longitude coordinates.

5. 5

   Write: Change Multiple Column Values

   Overwrites the original monday.com item. Updates the Location column with coordinates, populates individual text columns (City, State, ZIP), and clears temporary status columns.

4. Practical Notes

Look here for caveats, hardcoded credentials, or deployment statuses. For instance, if a Zap relies on a hardcoded API key instead of a stored environment variable, it will be noted here.

Troubleshooting Common Issues

When you encounter an issue with order data, use the symptoms to trace back to the responsible Zap.