--- name: al-531-answer-a-low-appraisal-before-the-deadline-give-an-ai-you description: "A low appraisal can sink a deal, and the window to respond is short. A Sidekick case study published Nov 1, 2026 describes Josh Zilke, a West Michigan agent three years into his career, who got his first Tidewater notice (a VA appraisal alert that gives the listing agent a narrow window to submit comps) while away at a conference. The appraiser's figure was more than $100,000 below his $630K list price. He gave Sidekick the list price, property details and a few comparable addresses; it built a report supporting the value, surfaced additional comps that matched on builder, build year and development, explained what made the home different and drafted the rebuttal email. He reviewed and adjusted it before sending. The case study says the deal closed at $620,000, and that he has since used it on a second Tidewater. This is a vendor case study, and the result also depends on the appraiser and the market. Any agent can follow the same steps with a general AI tool and their own MLS data,…" --- # Answer a low appraisal before the deadline: give an AI your list price, property details and the comps you have, and have it find more matching sales, build the case for your value and draft the rebuttal to the appraiser A low appraisal can sink a deal, and the window to respond is short. A Sidekick case study published Nov 1, 2026 describes Josh Zilke, a West Michigan agent three years into his career, who got his first Tidewater notice (a VA appraisal alert that gives the listing agent a narrow window to submit comps) while away at a conference. The appraiser's figure was more than $100,000 below his $630K list price. He gave Sidekick the list price, property details and a few comparable addresses; it built a report supporting the value, surfaced additional comps that matched on builder, build year and development, explained what made the home different and drafted the rebuttal email. He reviewed and adjusted it before sending. The case study says the deal closed at $620,000, and that he has since used it on a second Tidewater. This is a vendor case study, and the result also depends on the appraiser and the market. Any agent can follow the same steps with a general AI tool and their own MLS data, checking every comp before it goes out. ## Inputs to collect first Ask the user for anything below that they haven't already given you. Don't guess missing facts. - Price ## Instructions Do the task below with the user's inputs in place of each [bracket]. 1. Write down the list price, the appraised or flagged value, the deadline and the property's key facts (beds, baths, square feet, lot, year built, builder, upgrades). 2. Pull recent closed sales from your MLS for the same development or area, and paste them in with addresses, dates, prices and features. 3. Ask your AI: "Act as my appraisal-rebuttal assistant. Using only the sales I pasted, pick the closest comps to my listing (same development, builder and build year first), explain each adjustment in plain words, list anything that makes my listing worth more or less, and tell me honestly whether the data supports [list price]. Flag any comp that is weak or outside the appraiser's usual guidelines." 4. Ask it to draft a short, polite rebuttal to the appraiser: the value requested, the 3 to 5 strongest comps with the reason each fits, and corrections to any factual errors in the report. 5. Check every address, date and price against the MLS yourself, then send it before the deadline and tell your seller what you submitted. ## 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: Sidekick, ChatGPT, Claude, MLS - Based on this real-world example: https://www.sidekickdata.io/case-studies/when-the-appraiser-pushed-back-sidekick-had-the-answer - Free prompt from AgentPlaybook Real Estate: https://agentic-library.netlify.app/prompt/al-531-answer-a-low-appraisal-before-the-deadline-give-an-ai-your-l/ - 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/