The Scenario
You're a GIS analyst and you just wrapped an audit of your organization's Mapulus maps. The audit output is sitting in column A of your Google Sheet: 10 map IDs pulled from the account dashboard. Your job now is to build a proper map registry — each row expanded with the full metadata for that map. Title, description, location count, tags. Your manager wants it as a reference document that the whole operations team can use.
The obvious approach is to open each map in Mapulus one by one, read the details panel, and type them into the sheet. Ten maps sounds manageable until you realize that the Mapulus UI doesn't surface location counts in a scannable format, which means you're clicking into each map, waiting for it to load, and counting manually or copying a number that may or may not be accurate.
You're a GIS analyst. Your job is spatial analysis, not form data entry. The four hours this would take by hand are four hours you don't have allocated to it.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the map IDs in your sheet, fetches the full metadata for each one from Mapulus, and populates the adjacent columns automatically. The registry builds itself.
For each Mapulus map ID in column A, fetch the full map details and write the map title into column B, description into column C, creation date into column D, and total location count into column E — process all 10 rows
What You Get
- Column B gets the map title exactly as it appears in Mapulus
- Column C gets the map description (blank if none was set)
- Column D gets the creation date in ISO format
- Column E gets the total number of location pins on that map
- Any map ID that returns no result gets "not found" written across all four columns so the gap is visible
What If the Data Is Not Quite Ready
Some map IDs in column A were copied with surrounding whitespace
The IDs came from a CSV and some have leading or trailing spaces that could cause lookup failures.
Trim whitespace from all values in column A, then for each map ID fetch the Mapulus map details and write title, description, creation date, and location count into columns B through E
You need tag information too, not just core metadata
Your operations team uses Mapulus tags to categorize maps by region or project phase, and those tags need to be in the registry.
For each map ID in column A, fetch map details from Mapulus and write title into column B, description into column C, creation date into column D, location count into column E, and all tags as a comma-separated list into column F
The registry needs a "last updated" column alongside creation date
Your manager wants to see both dates so the team can identify maps that haven't been touched recently.
For each map ID in column A, fetch Mapulus map details and write title, description, creation date, last-updated date, and location count into columns B through F
Full registry build: clean IDs, fetch all metadata, flag sparse maps, add a summary
The registry needs to be production-ready — clean inputs, full metadata, and a flag for any map with fewer than five pins.
Trim all values in column A, fetch full Mapulus map details for each ID, write title into B, description into C, creation date into D, location count into E, and tags into F. Write "sparse" in column G for any map where location count is less than 5. Add a summary row at the bottom with total maps, total location count across all maps, and count of sparse maps.
Ask for the data pull, the flagging logic, and the summary in one shot — you get a finished registry document, not a table that still needs a column of conditional formatting applied.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a list of Mapulus map IDs in column A, then ask SheetXAI to pull the full metadata for each one and build your registry. When you're done here, see how to pull your full account map inventory or reconcile external IDs against location pins.