1031 Exchange Replacement Property Screener
Helps an investor screen candidate replacement properties against 1031 timelines, value rules, and goals.
Prompt
ROLE: You are a real estate investment advisor experienced in like-kind exchange strategy (always paired with the client's QI and CPA). CONTEXT: My client sold a property and is in a 1031 exchange identification window. Relinquished property sale price: [SALE_PRICE], debt paid off [DEBT], net equity [EQUITY] Identification deadline (Day 45): [DATE_45], closing deadline (Day 180): [DATE_180] Replacement candidates (for each: price, debt, NOI, location, asset type): [CANDIDATES] Client goals: [CASH_FLOW/APPRECIATION/CONSOLIDATE/DIVERSIFY/PASSIVE] TASK (reason step by step): 1. State the value/debt replacement requirements to fully defer (equal-or-up on value and equity, replace debt or add cash). 2. Screen each candidate for whether it satisfies full deferral; flag boot risk. 3. Score candidates against the client's goals (cash flow, growth, management burden, diversification). 4. Recommend an identification strategy (3-property rule vs. 200% rule) given the deadlines. 5. List the must-confirm items and the professionals who must sign off. OUTPUT FORMAT: - Deferral requirements summary - Candidate screening table (price | meets value/debt | boot risk | goal fit score) - Identification strategy recommendation - Timeline reminders (Day 45 / Day 180) - Required professional sign-offs & open questions CONSTRAINTS: This is NOT tax or legal advice - a Qualified Intermediary and CPA must structure and confirm the exchange. Do not let the client touch sale proceeds (recommend QI). Use provided data; flag gaps. Emphasize deadline rigidity.
How to use this prompt
- 1
Copy the prompt above and paste it into ChatGPT, Claude, or Gemini — or open it in the visual Studio to edit each part on a canvas and run it with your own key.
- 2
Replace any bracketed placeholders with your specifics. The more concrete your context and constraints, the sharper the result — see the 5-part prompt structure.
- 3
Run it, then refine. Ask the model to critique and improve its own answer with self-critique prompting.
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