What Egg Roll Number 1 Actually Is
Egg Roll Number 1 is a spreadsheet macro and data-patching tool used primarily in small-scale manufacturing and inventory environments where Excel-based workflows have replaced dedicated software. It was never commercialized. You won't find it on a proper software marketplace. The closest thing to an official source is a GitHub repository and scattered forum posts from people who built around it. The core functionality is straightforward. It takes a template sheet with conditional formatting rules, lookup formulas, and VBA macros, then applies those rules to incoming batch data. The result is a flagged sheet where items that don't match expected ranges get highlighted in red, amber, or green depending on severity. For basic stock reconciliation, it usually cuts the process down from 2 hours to about 15 minutes, depending on your setup.
Downloading Egg Roll Number 1
The original repo lives under a fairly generic name, which is why finding the right file takes a few minutes of digging. Search for "egg roll number 1 spreadsheet tool" on GitHub and you should land on the main repository within the first result. The README there links to a .xlsm file in the /releases folder. Download that. Run it only on a machine where macros are already permitted for trusted locations, and ideally test it in a sandbox workbook first before touching anything with live data. Open the file. You will see two sheets: Template and Input. The Template sheet is preconfigured with everything. Input is where you paste your raw data. The macro runs when you hit the button on the Template sheet labeled "Process Batch." It validates column structure, matches against stored SKU/format rules, and writes output to a Results tab. There is one detail most people miss. The macro expects column A to be the primary identifier and column B to be the numeric field it compares against thresholds. If your data starts with a date or a free-text description in column A, the macro either errors out silently or misflags entries. I learned this the hard way when I ran a batch where the supplier sent part numbers as text strings instead of integers. Every single row came back as a false positive amber alert. The fix was a quick transpose step: I added a helper column that stripped non-numeric characters using =VALUE(SUBSTITUTE(A2,"-","")) and then referenced that helper in the macro config sheet instead of the raw column.
Counter-Intuitive Things Beginners Get Wrong
The biggest mistake people make is treating the color coding as a final verdict. Those colors are based on default thresholds baked into the template. They are not calibrated to your business logic. The red flag on row 47 might mean a quantity variance of 3 percent, which is acceptable in your context, or it might mean a missing shipment worth $12,000. You have to read the diagnostic notes column the macro writes alongside each flagged row. That column contains the actual deviation value and the rule that triggered it. Ignore it and you are just chasing colored cells. Another thing nobody warns you about: the macro caches previous run results in a hidden sheet called _History. If you run the same file twice without clearing it, the second run appends to the history but also references stale baseline values from the first run. This caused me to accidentally approve a reorder request because the history sheet showed a previous inventory count that had since been corrected manually. The workaround is to clear _History before every new batch. There is no auto-clear function built in.
Get the Full Details
Where It Falls Apart
Egg Roll Number 1 was built for simple SKU-level reconciliation, maybe a few thousand rows. It chokes on anything above roughly 8,000 rows in my experience. The VBA loops become noticeably slow and Excel starts freezing during the processing step. If your dataset is larger than that, you are better off writing a proper Python script with pandas or using a dedicated inventory tool. This macro is not going to scale past that point no matter how much you tweak the settings. It also does not handle duplicate SKUs gracefully. If your source data contains two rows with the same identifier but different batch codes, the macro will merge them incorrectly. I have seen batches get corrupted because a receiving log had split entries for the same item across two shifts. The macro assumed the last row was the authoritative one and overwrote the earlier quantity with the later one, effectively erasing the first shift's intake data.
Quick Step-by-Step Walkthrough
Prepare your source file as a clean CSV or paste directly into the Input sheet. Make sure column A is your primary key and column B is the numeric field you want validated. Open the _Config sheet if you need to adjust threshold values for your specific product categories. Save the file. Go to the Template sheet and click Process Batch. Wait for the macro to finish, which for a typical 500-row batch takes about 30 seconds on a standard office laptop. Review the Results tab and cross-reference any red flags against the diagnostic column. Export the results to a new file if you need to share them with a team member who should not see the template macros.
A Reasonable Alternative
If you need something that handles larger datasets and does not risk corrupting your data through silent overwrites, look into Power Query in Excel. It can do the same validation and flagging logic without VBA, it runs significantly faster on big files, and it leaves a clear audit trail of every transformation step. Egg Roll Number 1 still has a place for quick ad-hoc checks on small batches where setting up a Power Query pipeline is overkill. But for anything repeatable or production-facing, Power Query is the safer bet.
