Most listing descriptions on the MLS read the same way. They rely on the same stock phrases and rarely say anything specific about the home or the neighborhood. This is usually not a problem with the AI tools themselves, but with how they are used. When a model is given little information, it produces generic writing. When it is given detailed, accurate context, it produces a description that reflects the actual property.
At Agent Stack, we produce listing media for agents on a daily basis, and writing descriptions is part of that work. The process below is a straightforward way to use tools such as ChatGPT, Claude, or Gemini to generate a strong first draft. It applies to any of the three. The steps take only a few minutes per listing.
The Process
Select and upload 20 photos. Choose a set that represents the entire property, both exterior and interior. Include the front of the home, the yard, the kitchen, the main living areas, the bedrooms, the bathrooms, and any notable features. Twenty images is the maximum you can upload, and using the full set gives the model a complete view of the home. A representative set is shown below.
Upload the floor plan. The floor plan provides the layout, the bedroom and bathroom count, and the relationship between rooms. The photos convey the look and feel of the home, while the floor plan supplies the structural facts. Including both keeps the description accurate as well as descriptive
Enter the following prompt, replacing the placeholder with the full address:
“Write me a captivating property description for (insert full address) based on the photos I attached and floor plan. Add anything you know about the area and location that is relevant to potential buyers such as parks, schools, transportation, amenities close by and the lifestyle of the neighborhood. Don’t use the word nestled or use em dashes.”
Review the draft. With this amount of context and the model’s knowledge of the area, the result is a description specific to the property rather than the generic copy commonly found on the MLS. At this point the draft is largely complete and requires only minor editing.
Why the Prompt Is Structured This Way
Referencing the photos and floor plan directs the model to base its writing on the actual features of the home rather than inventing them. Requesting area and lifestyle detail draws on information the models handle well, including nearby parks, schools, transportation, and amenities, which matters to buyers who are evaluating the surrounding neighborhood as much as the house itself.
The two final instructions address common issues. Excluding the word “nestled” removes one of the most overused terms in real estate writing. Excluding em dashes removes a frequent indicator of AI-generated text and produces copy that reads more naturally.
Reviewing the Draft
A short review pass is worthwhile before publishing. Confirm any concrete details, such as square footage, year built, or school names, against your own listing data, since the model can occasionally estimate these. Trim sentences that do not add specific information, and make light edits so the copy matches your usual tone. Finally, verify the description against your local MLS guidelines, as some have character limits or content restrictions.
For Operations Teams
This process is straightforward to standardize. Saving the prompt as a template and following a consistent checklist for photo selection and floor plan upload allows a team to produce a reliable first draft for every listing in a few minutes, with consistent quality across all properties.
Summary
The quality of an AI-generated property description depends on the quality of the input. Providing a full set of photos, the floor plan, and a clear prompt that draws on neighborhood detail produces a description that reflects the specific property and reads naturally.
If you would prefer to have your listing descriptions and media produced for you, this is the work we do at Agent Stack. More information is available at www.agentstack.co.
