No hours figure for this stage was verified anywhere, so this page prints none. What is paid is Tuesday, decided from a number nobody joined.
You have four dashboards. You have no answer. Every product you pay for reports its own slice, and reports it well. This chapter concedes it first. For a six-person brokerage the join across them is a Monday with a spreadsheet.
By hand today
Reporting is the most covered stage in this book. Follow Up Boss ships “Lead source reporting” and a “Team Leaderboard”; PropSpace ships “Business Insights - Access critical performance data on leads and deals”. Nobody lacks charts.
Where they stop is the join. The portal reports the leads it sent you, on its own screen: Bayut Profolio sorts them into “Email, SMS, Phone, WhatsApp and Chat leads”, exportable to Excel, and Property Finder Leads Insights filters the same by channel. The CRM reports what agents did and the back office reports money. None holds portal spend next to the lead it bought, the deal it became and the commission on it. Nor does public code: the one repository that reaches invoicing stores total and grandTotal as String (raw.githubusercontent.com), and text does not forecast.
What it costs you each week
Zero, on the record
No hours figure for this stage was verified anywhere, so this book prints none. What is paid is Tuesday, decided from a number nobody joined.
Source: no hours-per-task figure verified for any stage; vendor pricing pages, 14 September 2026
The commission half is the same. PropSpace at AED 220 a user a month is the one product found with a native split, “Deal Tracking - Accurately monitor completed deals and commissions earned by both the company and individual agents”. If you have it, the split is calculated and your problem is reconciliation.
The build
Open Codex. Ask for one table. Portal spend off the portal, leads and deals off the CRM, commission off your sheet. Every count carries its total. A number nobody wrote stays blank, never zero.
Open Codex in the engine folder. Connect a Sheets server, taylorwilsdon/google_workspace_mcp (github.com), and the CRM server, HubSpot at mcp.hubspot.com (developers.hubspot.com). The portal publishes none, so the browser reads it: chrome-devtools-mcp drives your own Chrome, where list_network_requests shows the JSON behind the chart. Write monday.md once: the stage names, the sheet tab, the week that counts. Then say what you want:
Every Monday at seven, read the portal lead dashboard and the spend
beside it in the open browser; from the CRM every deal that changed
stage in seven days; and the commission tab of the sheet. Write one
table: per stage the count in, the count out, and the total sitting
in it, so every count has its total beside it, plus a row for portal
spend and one for commission raised. Print each stage conversion
this week beside the same stage last week, and name the ONE stage
whose rate fell furthest. Where a value was never written print a
dash, never a zero, and list what you could not read.
What comes back is a script, a schedule and one table.
Three honest limits, which Codex will name. The portal read runs against your own logged-in Chrome, a tool that “exposes content of the browser instance to the MCP clients”, so it runs on a screen you watch. A HubSpot account with sensitive data turned on blocks activity objects (developers.hubspot.com), so that half reads short and says so. And the table is only as true as chapter 16 made the record.
There is no benchmark either: no conversion rate for this trade was found published anywhere, so your week compares only against your last.
What it feeds
Next week, and the asset you do not own. One stage fell. That is what changes on Tuesday, and the only thing that changes. Then the row nothing else holds: who was asked, and who never answered.
The table names one stage. That is Tuesday, and the rest is left alone, because a week in which four things changed teaches nothing. Then the half no product reaches: the reviews that win your next client sit on a portal you do not own, and a broker traced an appointment to them:
“It all began on a listing appointment for an $800,000 home when the sellers said they found me on Zillow. … It turns out they read some reviews about me on Zillow from past clients”
Margaret Woda, Associate Broker, Long & Foster Real Estate, Crofton MD, on ActiveRain
One deal, self-reported, and this book makes no rate of it. Her postscript names the gap: “I just need to be more conscientious about requesting reviews.”
The platform says so itself. A managing broker published the email he got after a stranger who was never his client tried to rate him: “we are extending you a “Free Pass” and will not publish this review on your Zillow profile. Please note that this is a one-time courtesy” (J. Philip Faranda, Howard Hanna Rand Realty, Westchester NY, activerain.com). A Zillow employee replied in the thread: “The bigger issue is debate point of letting ‘anyone with a computer’ write a review” (Sara Bonert, same URL).
So the build owns the half it can: the Monday table gains a row per closed deal, who was asked, when, and whether a review appeared. No tool you pay for holds it.
The number that proves this stage worked is one screen where every count reconciles to the commission raised, plus past clients asked who never answered.
What stays with a person
What changes on Tuesday. The table says which stage fell. Choosing what to do is a judgement, made weekly. And the ask itself: whether to ask this client for a review.
The table names the stage. What to do is yours, and writing it down each week is the discipline: a leak found and forgotten is a leak.
The ask is yours too, including not making it:
“And if it bothers you, don’t do it. Your discomfort will be crystal clear to the person you’re asking”
Jennifer Allan-Hagedorn, Sell with Soul, on ActiveRain
The split agreement is a third. A machine flags where paid and agreed differ; varying one is a conversation.
The tools you already pay for
Nothing new to buy.
Portal is Bayut Profolio or Property Finder Leads Insights, whichever you advertise on; neither publishes a server, so the browser reads them.
CRM is HubSpot, Pipedrive at mcp.pipedrive.ai, or Zoho Data Insights.
Sheet is Google Sheets, or Excel through Softeria/ms-365-mcp-server.
Browser is chrome-devtools-mcp, or playwright-mcp unattended.
One table on a Monday, every count carrying its total, one stage fallen. That stage is Tuesday.
Ask: Last Monday you read four dashboards. Which stage did they agree had leaked?
This is stage 20 of twenty, the last, after knowing which document is missing and from whom. The whole engine in order is the book, Building a real estate sales engine with Claude Code and Codex, end to end.