--- name: al-492-find-the-owners-most-likely-to-want-your-commercial-listi description: "Commercial brokers often have a listing and no obvious buyer, and building a list of nearby owners who might want it used to take hours of record searching. AI Business Plays writes up a self-reported LinkedIn post by Rudy Martinez, an industrial commercial real estate broker in Southern California. He asked an AI prospecting agent (Terrakotta) to find industrial owners within 10 miles of his Azusa, California listing who would want to trade up into an 8,000 square foot facility. It returned 624 owners in 30 seconds and found phone numbers for each from Secretary of State records. On his 21st cold call he reached the owner of a 3,100 square foot building 2.2 miles away who wanted to sell as soon as possible, and he won the roughly $1M listing. He also uses an AI notetaker on his calls. It is self-reported, and the deal is a listing, not a closed sale yet. Check your local cold-calling rules and the Do Not Call list, and verify every owner record before you call. Use when the user…" --- # Find the owners most likely to want your commercial listing: have an AI prospecting agent list nearby owners who fit a trade-up profile, pull public contact records into one call list, and log every call Commercial brokers often have a listing and no obvious buyer, and building a list of nearby owners who might want it used to take hours of record searching. AI Business Plays writes up a self-reported LinkedIn post by Rudy Martinez, an industrial commercial real estate broker in Southern California. He asked an AI prospecting agent (Terrakotta) to find industrial owners within 10 miles of his Azusa, California listing who would want to trade up into an 8,000 square foot facility. It returned 624 owners in 30 seconds and found phone numbers for each from Secretary of State records. On his 21st cold call he reached the owner of a 3,100 square foot building 2.2 miles away who wanted to sell as soon as possible, and he won the roughly $1M listing. He also uses an AI notetaker on his calls. It is self-reported, and the deal is a listing, not a closed sale yet. Check your local cold-calling rules and the Do Not Call list, and verify every owner record before you call. ## Inputs to collect first Ask the user for anything below that they haven't already given you. Don't guess missing facts. - Ress, property type, size in square feet, key features, price or… - E.g. an owner-user of a smaller industrial building nearby who is… - Distance, e.g. within 10 miles ## Instructions Do the task below with the user's inputs in place of each [bracket]. Help me find property owners who are likely to want, or trade up into, my commercial listing. My listing: [address, property type, size in square feet, key features, price or lease rate]. The owner most likely to want it: [e.g. an owner-user of a smaller industrial building nearby who is outgrowing it]. Search area: [distance, e.g. within 10 miles]. 1) List up to [number] properties in that area that fit the profile, with the address, size, owner name or owning company, and the public source for each (county assessor, business registry or Secretary of State record). Don't guess an owner or a phone number; leave it blank if you can't find a public record. 2) Rank the list by how likely the owner is to want my property, with a one-line reason each (size gap, age of building, how long they've owned it). 3) Turn the top 25 into a call list with a 2-sentence opener for each that mentions their building. 4) Give me a simple call log table: owner, date called, outcome, interest level, next step. Remind me to check my local cold-calling rules and the Do Not Call list before I dial. ## Safety checks (share these with the user) - Check every figure, price and total against your own records before anything is sent, posted or booked. A person approves refunds, discounts, payments and price changes. - Remove names, contact details, account numbers and other personal data the task doesn't need before you paste, and check your AI tool's data and training settings. - Read and edit the draft before it reaches a customer or goes public. If you later automate this prompt, start with "draft and notify me", not "send automatically". - Check names, dates, numbers and any claim against your own source material before you use the answer. AI can misread or invent details. - Say clearly which parts need a person to review or approve before anything is sent, paid, posted or filed. ## About this skill - Works with: Terrakotta, ChatGPT, Claude, Perplexity, AI notetaker - Based on this real-world example: https://aibusinessplays.com/plays/commercial-broker-ai-prospecting-finds-1m-listing-in-21-calls/ - Free prompt from AgentPlaybook Real Estate: https://agentic-library.netlify.app/prompt/al-492-find-the-owners-most-likely-to-want-your-commercial-listing/ - To install in an agent that supports Agent Skills, save this file as SKILL.md in a folder with the same name as `name` above (for example in your skills directory). Install steps for Claude.ai, Claude Code, Cursor and Codex: https://agentic-library.netlify.app/skills/