18
Ready-to-run prompts
5
Workflows covered
1
Copy-paste workflow
How to use this
These are not writing prompts. They are data prompts. You feed them your MLS data and they return strategy you can use right now.
01
Pull up the address, neighborhood, or market area you want to analyze.
02
Fill in the bracketed fields with your real data, then paste into Claude.
03
Take the comp grid, pricing note, offer range, or post straight into your conversation, report, or content calendar.
The library
Filter by category or search by keyword. Every prompt copies straight to your clipboard.
Showing 18 of 18 prompts
Pricing & Listing
Run it when: New listing intake, before the listing goes live.
Prompt, paste as-is
Pull the 6 closest comparable closed sales and 4 closest active listings for [ADDRESS], matched on beds, baths, square footage, and lot size within a 1 mile radius and the last 6 months. Build a comp grid with address, sale/list price, price per square foot, days on market, and key differences from the subject property. Recommend a list price range with reasoning. Then draft the core content blocks for a single property listing website: headline, 3 paragraph description, and 5 highlight bullets, using only the facts in the comp data and property details I provide.
Produces: Comp grid, price range, and listing website copy blocks.
Sold Data & Negotiation
Run it when: Any seller conversation, or a scheduled report to active sellers. Also works as a buyer offer-strategy briefing from the same data.
Prompt, paste as-is
Pull every closed sale in [NEIGHBORHOOD / SUBDIVISION / RADIUS from ADDRESS] in the last 6 months. For each, note the sale price vs original list price, any concessions visible in the data (seller-paid closing costs, rate buydowns, repair credits, home warranty), and days on market. Identify the common denominators among the homes that sold fastest and closest to asking: price positioning, condition signals in the remarks, photo count if available, and concession patterns. Write two short summaries from the same data: one for a seller ("here's what's working right now"), one for a buyer writing an offer ("here's what sellers are actually saying yes to").
Produces: Two short reports from one data pull, seller-facing and buyer-facing.
Optional polish: Route the seller version through your own report template; the buyer version works as-is.
Pricing & Listing
Run it when: Seller listening appointment, or before pitching a re-list.
Prompt, paste as-is
Pull every expired and withdrawn listing in [NEIGHBORHOOD / ZIP] over the last 12 months. For each, note original list price, any price reductions and their timing, days on market before the listing was pulled, and how far the price sat above nearby closed comps at time of listing. Summarize the common pattern among the listings that failed to sell, and contrast it with what closed listings in the same area did differently.
Produces: A pattern summary you can use to explain why a home did not sell and what to change.
Pricing & Listing
Run it when: Before a new listing goes live, or mid-listing if showings slow down.
Prompt, paste as-is
Pull every currently active listing within [RADIUS] of [ADDRESS] in the same price range (+/- 10%). For each, list price, days on market, price per square foot, and the single strongest differentiator (updated kitchen, pool, lot size, school zone, garage size). Rank them by how directly they compete with the subject property and identify the 2-3 homes a buyer would cross-shop against it.
Produces: A ranked competitive set with the specific angle each competitor is winning on.
Optional polish: Feed straight into listing marketing copy to position against the named gaps.
Pricing & Listing
Run it when: Pricing strategy conversation with a seller anchored to a high number.
Prompt, paste as-is
Pull the last 12 months of closed and expired/withdrawn listings in [NEIGHBORHOOD / ZIP]. Group them into two buckets: homes whose original list price was within 3% of the eventual closed comp value at the time (or closed near asking), and homes whose original list price sat more than 8% above it. Compare average days on market, number of price reductions, and final sale-to-list ratio between the two groups. State the finding in one sentence a seller can understand without a chart.
Produces: A plain-language pricing-accuracy finding backed by local data.
Pricing & Listing
Run it when: A seller says they are not in a rush to sell.
Prompt, paste as-is
Pull the last 24-36 months of closed sales and current active/pending inventory for [NEIGHBORHOOD / ZIP]. For each calendar month, calculate: average days on market for homes listed that month, average sale-to-list ratio, and average number of competing active listings during that month. Rank the months best to worst for a seller based on the combination of fastest sale, best price ratio, and lowest competition. Then write a short, non-pushy paragraph I can say to a seller who is not in a rush, using the actual numbers to show there is still a better and worse time to list, without pressuring them to sell now.
Produces: Ranked month-by-month timing data plus a ready-to-say paragraph.
Pricing & Listing
Run it when: A seller is deciding whether to update before listing.
Prompt, paste as-is
Pull closed sales in [NEIGHBORHOOD / ZIP] over the last 12 months and split them into homes the remarks describe as updated (renovated kitchen or bath, new flooring, recent systems) versus homes described as original or dated condition. Compare average sale price, price per square foot, and days on market between the two groups. State the practical dollar gap and whether it is large enough to justify a specific renovation before listing.
Produces: An updated-vs-original comp comparison with a dollar-gap conclusion.
Offer Strategy
Run it when: Buyer consult, before writing an offer.
Prompt, paste as-is
Pull the last 6 months of closed sales in [NEIGHBORHOOD / ZIP / PRICE RANGE]. Calculate the average and median sale-to-list price ratio, and break it out by how many days the home was on market before going under contract (0-7 days, 8-21 days, 22+ days). Tell me, for a home that has been listed for [X] days, what sale-to-list ratio range recent comparable buyers actually needed to win.
Produces: A data-backed offer-price range calibrated to how long the target home has been listed.
Offer Strategy
Run it when: Buyer consult, or as standalone buyer-facing content.
Prompt, paste as-is
Pull the last 90 days of closed sales in [ZIP / NEIGHBORHOOD / PRICE RANGE]. Identify any seller concessions visible in the data (seller-paid closing costs, rate buydowns, repair credits, home warranty). Summarize what percentage of closed sales included a concession, the average concession amount, and 2-3 notable examples. Write it two ways: a private buyer-consult version with specifics, and a short public social caption with no addresses or personal details, telling local buyers what sellers are actually agreeing to right now.
Produces: A private buyer briefing plus a shareable social caption from the same pull.
Optional polish: Run the social version through your own voice and graphic template.
Offer Strategy
Run it when: Buyer is entering a competitive situation.
Prompt, paste as-is
Pull closed sales in [NEIGHBORHOOD / ZIP / PRICE RANGE] over the last 6 months that went under contract in 7 days or fewer (a proxy for multiple offers). For these, note the sale-to-list ratio and, where visible in remarks or agent notes, any mention of waived contingencies, escalation clauses, or shortened option periods. Summarize what it actually took to win in this specific market segment, in plain terms a buyer can act on.
Produces: A realistic picture of what a winning offer looked like recently in this segment.
Offer Strategy
Run it when: Buyer is worried about an appraisal gap, or deciding how much coverage to offer.
Prompt, paste as-is
Pull closed sales in [NEIGHBORHOOD / ZIP] over the last 6 months where the closed price came in above the average of comparable recent sales at time of contract (a proxy for an appraisal-gap situation). Estimate how often this appears to have happened in this price range and roughly how large the gap was. Explain in plain terms whether appraisal gap coverage is commonly needed here right now, and roughly how much.
Produces: A grounded read on whether and how much appraisal gap coverage this market currently requires.
Lead-Gen Content
Run it when: Weekly or biweekly content cadence, buyer-facing lead gen (the buyer-side parallel to the seller concessions report).
Prompt, paste as-is
Pull the last 60 days of closed sales in [ZIP / NEIGHBORHOOD / PRICE RANGE]. Summarize, in aggregate only with no addresses, what percentage of buyers got some form of concession, the average amount, and one standout example described generically (e.g. "a buyer near [general area] got $8,000 toward closing costs"). Write it as a short, scroll-stopping social caption for a local buyer-focused Facebook group.
Produces: A ready-to-post buyer lead-gen caption.
Optional polish: Apply your own voice and graphic template depending on which account posts it.
Lead-Gen Content
Run it when: Monthly content cadence, or a buyer asking whether to pause their search.
Prompt, paste as-is
Pull the current active and pending inventory count in [ZIP / NEIGHBORHOOD] and compare it to the same point 3, 6, and 12 months ago. Combine that with the recent sale-to-list ratio trend. Write a short, honest answer to "should I wait or buy now" using only this data: is inventory growing or shrinking, and is competition easing or intensifying.
Produces: A short, data-grounded market-timing read for buyers.
Lead-Gen Content
Run it when: Weekly content cadence, buyer lead gen.
Prompt, paste as-is
Pull homes that closed below their original list price in [ZIP / NEIGHBORHOOD] in the last 30 days. List how many there were and the average discount from list price, without naming addresses. Write it as a short social post telling buyers that data-backed offers are winning right now, with the discount stat as proof.
Produces: A shareable proof that negotiation works post.
Lead-Gen Content
Run it when: Content cadence, or an early buyer consult with someone unsure what their budget actually buys.
Prompt, paste as-is
Pull the current median list price and typical square footage for active listings in [SUBURB / ZIP / PRICE RANGE]. Using a stated interest rate and down payment percentage, estimate a rough monthly payment (principal, interest, and an estimated tax/insurance figure if known for the area). Write one clear sentence: "here's what $[X]/month actually buys in [SUBURB] right now."
Produces: A single, highly shareable affordability line plus the supporting numbers.
Lead-Gen Content
Run it when: Weekly content cadence, buyer lead gen.
Prompt, paste as-is
Pull every new listing that hit the market in the last 7 days in [ZIP / NEIGHBORHOOD / PRICE RANGE]. Summarize the count and the 2-3 most notable ones (price, beds/baths, standout feature) without needing to name every address. Write it as a short first to know digest post for buyers watching this area.
Produces: A recurring content piece that positions you as first-to-know on new inventory.
Prospecting
Run it when: New listing intake, to identify who to notify directly.
Prompt, paste as-is
Pull every buyer-side agent who showed or wrote an offer on comparable properties to [ADDRESS] (same neighborhood, similar price range and specs) over the last 6 months. List the agent names and brokerages so I can reach out directly about this new listing.
Produces: A targeted outreach list of buyer agents likely to have an active client for this listing.
Prospecting
Run it when: Prospecting or farming a specific neighborhood.
Prompt, paste as-is
For [NEIGHBORHOOD / SUBDIVISION], identify homes where the current owner has held the property for 7+ years and the neighborhood's price-per-square-foot has risen meaningfully since typical purchase timing for that tenure. Rank streets or blocks by likely built-up equity, as a prioritization list for farming outreach, not a claim about any specific owner's finances.
Produces: A prioritized farming list based on equity and tenure signals.
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