Decide where to live next, or whether to move at all.
A private, AI-ready housing assistant. Compare apartments, condos, and houses against your budget, commute, and deal-breakers, with every option scored against the home you live in now.
Screenshots use the tool's built-in fictional demo data.
Listing sites rank homes for their business, not your life.
Rental and real-estate sites sort by sponsored placement, newest, or cheapest. None of them know how often you commute, what you will not compromise on, or what the true monthly cost is once parking and fees are added. And none of them ask the most important question: is this actually better than where you live now?
Most people end up juggling spreadsheets, browser tabs, and gut feel. Housing Decision Agent replaces that with a consistent, explainable score built from your own priorities.
Your priorities in. A ranked, explainable shortlist out.
Set up your profile
Run housing init and answer a few questions: budget, places you travel to often, and deal-breakers. Every question is skippable.
Add candidates
Enter apartments, condos, or houses by hand, or let an AI agent do the research. Every fact records its source and the date it was checked.
Compare against home
Each option gets a weighted score with risk caps and deal-breakers applied, side by side with your current home as the baseline.
- ›Should I even move? Your current home is the benchmark every option has to beat.
- ›True all-in cost including parking and required fees, checked against ideal, soft, and hard budget ceilings.
- ›Commute to the places that matter: work, gym, family, weighted by how often you go.
- ›Risk rules and deal-breakers such as flood-exposed parking or heavy construction nearby cap or rule out a place.
- ›Stale-data warnings so old prices and availability get re-checked instead of trusted.
Point and click, or let an agent do the legwork.
The dashboard and the command line share one backend, so a change made in either shows up in both. AI coding agents that can run terminal commands (Claude Code, Codex, GitHub Copilot, Cursor) can set up your profile, record researched facts with sources, and score candidates, using a clear JSON interface and written agent instructions.
Your budget and addresses never leave your machine.
Local files only
No accounts, no cloud, no database. Your profile is a folder of plain JSON files that you own, kept outside the code.
Local-only server
The dashboard only listens on your own computer, with a per-launch token. Map tiles are off until you turn them on.
Publish-safe tooling
A built-in privacy scanner and gitleaks gate help keep personal data out of anything shared publicly.
Simple on purpose.
Scores are recomputed from facts and judgments every time, never stored, so results stay reproducible and explainable. Writes are coordinated across the dashboard and CLI, so a stale edit returns a conflict instead of silently overwriting newer work.
Turning a personal tool into something anyone can use.
Separate the engine from the person. It started as a tool for my own move. Making it shareable meant pulling every personal value into a private profile folder, so the public code holds no one's budget, city, or home.
Facts, judgments, and math are different things. Keeping sourced facts separate from scored judgments, and letting the code do the math, made recommendations reproducible instead of a guess.
Design for AI agents from day one. A clean CLI with JSON output and written agent instructions lets an assistant do real research work without editing files directly.
Privacy has to be verified, not assumed. Before going public, the release was built as a fresh export with no history and checked by automated scanners plus an independent review.
The roadmap.
- →MCP server so AI tools can use the agent natively.
- →More city region packs with local research sources; Miami is the first.
- →"What if" views that show how the ranking changes if your priorities shift.
- →Buying support with mortgage-style monthly cost estimates.
Free and open source
Try it on your next move.
Clone the repo, run the fictional demo, then create your own private profile in a few minutes. Built by Bryan Totty.