Rent it long-term or list it on Airbnb? I stopped guessing and ran one call

Anyone who has owned a property has had this argument with themselves. Do I take
the steady long-term tenant, or do I furnish it and put it on Airbnb for more per
night but more hassle and more empty nights? Most people decide it on a feeling,
or on one Airbnb listing they saw once, which is not data, it is an anecdote.

The honest version of this decision needs four numbers for the same area: what is
for sale, what recently sold, what long-term rents ask, and what short-term
rentals actually earn. Those normally live in four different tools. I put them in
one call.

What I actually did

// tools/call → market_report
{ "location": "Austin, TX" }

For Austin that came back in about 19 seconds with all four sides. The two
numbers I put next to each other were a recently sold 3 bed, 1,984 square feet at
a $648,000 estimate in ZIP 78739, and a downtown condo renting on the short-term
market at $808 for three nights, rated 4.97 across 387 reviews.

Those are different ZIPs and different property types, so it is not a direct
swap. But it is the exact comparison the decision requires, and having both sides
in the same object means the arithmetic is right there instead of scattered
across four tabs.

How to actually decide with it

1. Pull the four sides for your specific area. Not a national average, your
   ZIP. Real estate is local and averages lie.

2. Anchor on the sold price, not the asking price. What is listed is a hope.
   What sold is what the market paid. Your yield math has to start from the real
   number.

3. Read the review count on the short-term side, not just the nightly rate.
   A high nightly price on an empty calendar earns nothing. 387 reviews at 4.97
   is a property that is genuinely getting booked, which is a completely
   different thing from one that is merely listed at a high price.

4. Do the yield both ways. Long-term rent times twelve, against nightly rate
   times realistic occupancy. Now you are deciding on two numbers you trust
   instead of a feeling.

Why this works

The reason people get this wrong is that the four data points live in four
places, so nobody assembles all four before deciding. They look at one Airbnb
listing, get excited by the nightly number, and forget that empty nights and
cleaning turn it into a job. Seeing supply, sold comps, long-term rent and real
short-term performance together is what turns a hunch into a decision.

Honest limits

Coverage is US only. The sold estimates are model output, not appraisals, and
they come back labelled as such. A thin market returns fewer records. The
short-term side reflects what is listed publicly, so it is a supply and pricing
picture, not a landlord's actual tax return. But for making the rent-versus-list
call with real numbers instead of a story, it is the fastest honest look I have
found.

The tool is the Real Estate MCP
from The Mine Works, on Apify with your own account. It bills by outcome, so a
location with no listings returns an empty report and costs nothing.