Complete AI Training
Sign inGet my AI kit

Your job's AI kit

Get your AI kit

Tell us who you are and what you do. We show you your kit right away and email you the link: skills, prompts, AI agents, MCP servers and courses for your job.

500+ jobs ready, and we make a kit for any other job. No payment needed to look.

Share

AI agent for real estate investors

Pro Forma Sensitivity Stress Agent

A clear map of which assumptions break returns or covenants, and a tested fix for each

Pro Forma Sensitivity Stress Agent: what goes in, what the agent does and what you get

What it does

A pro forma that works at today's numbers can fail when construction costs rise, rents come in low or interest rates move. Developers and investors often test one or two cases by hand. This agent takes the model and varies key inputs across ranges: construction cost, rent, vacancy, exit cap rate and interest rate. For each case it reruns the returns and the lender covenants, such as debt service coverage and loan to cost. It maps which combinations break a target, then suggests changes such as a lower budget line, a longer lease-up or more equity, and reruns the model with each change. It checks that its base case matches the original model before trusting results. The developer approves the summary shown to partners. Edge case: a rate rise breaks coverage only when rents are also low.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Pro forma updated or meeting approaching 2 USES A TOOL Load the model and the return and covenant targets 3 DOES Rebuild the base case and compare it with theoriginal output 4 CHECKS THE RESULT Does the base case match the original model? If not: find the broken link or input and fix the copybefore testing. Back to step 2. 5 USES A TOOL Run cases across cost, rent, vacancy, cap rate andrate ranges 6 DOES Mark every case that breaks a return or covenantthreshold 7 DOES Propose changes such as budget cuts, longer lease-upor more equity 8 CHECKS THE RESULT Does each proposed change clear all thresholds onrerun? If not: adjust the change or try another and rerun. Backto step 5. 9 YOU APPROVE Developer approves the summary for partners 10 RESULT Sensitivity summary with break points and fixes
Read the steps as a list
  1. Pro forma updated or meeting approaching
  2. Load the model and the return and covenant targets
  3. Rebuild the base case and compare it with the original output
  4. Does the base case match the original model?If not: find the broken link or input and fix the copy before testing. Back to step 2.
  5. Run cases across cost, rent, vacancy, cap rate and rate ranges
  6. Mark every case that breaks a return or covenant threshold
  7. Propose changes such as budget cuts, longer lease-up or more equity
  8. Does each proposed change clear all thresholds on rerun?If not: adjust the change or try another and rerun. Back to step 5.
  9. Developer approves the summary for partnersThe agent waits here for your OK.
  10. Sensitivity summary with break points and fixes

How it decides

A case fails when returns or covenant ratios cross the stated thresholds. A fix is kept only when a rerun clears every threshold.

  • Use ranges of plus and minus 10 percent for cost and rent unless set otherwise
  • Flag a combination as a break when any covenant fails
  • Prefer fixes that change the fewest assumptions
  • Show results for single changes and for pairs of changes

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Input ranges to vary
  • Return and covenant thresholds
  • Number of cases to run
  • Summary format for partners

What keeps you in control

It always asks you first

  • Developer approves the summary shown to partners
  • Developer approves any change to base assumptions

Hard limits

  • Never change the owner's base assumptions silently
  • State every assumption used in each case
  • Do not predict market outcomes

It stops when

  • Done: every break has a tested fix or a clear flag
  • Stop: the base case cannot be matched to the model

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA 120-unit project shows a 14% return at base. At cost up 8% and rates up 1 point, coverage drops to 1.12 against a 1.20 covenant. The agent tests a longer lease-up, which fails, then adding $900,000 of equity, which restores 1.21. The developer approves a summary showing both results.

More agents for real estate investors