Commerce · Clearance Hunter
Clearance Hunter
A retail-arbitrage signal tool that verifies clearance prices at the user's local stores, prices them against resale value, and ranks the trip by expected dollars per hour.
Local stock verified · resale checked · trip ranked
The problem
Clearance deals are everywhere, but verifying local stock, true resale value, fees and whether the drive is worth it is slow, and most "deals" turn out to be store-exclusive items with no resale market at all.
What it does
Clearance Hunter watches per-store prices, looks up resale value, applies hard sanity gates and ranks what survives by the expected value of the shopping trip. It learns from what the operator actually buys and sells. It runs as a Windows service with a phone barcode scanner for the store aisle. It is a lab project: the place where Stonebridge tests ranking, feedback loops and data-pipeline discipline on a problem with fast, honest feedback.
Capabilities
What it does, specifically.
Local verification
Per-store price and stock at the user's own stores, not national averages.
Resale-aware ranking
Resale lookup, fees, demand signals and private-label detection before anything is called an opportunity.
Dollars-per-hour trips
Opportunities ranked by the expected value of the trip, not by discount percentage.
Three buckets
Alert, needs a manual check, near miss. Nothing is hidden and nothing is overstated.
Outcome feedback
The ranking learns from purchases and sales, and the tool keeps its own demand history.
Aisle scanner
A phone barcode scanner that answers in the store.
Controls
Built in, not bolted on.
- Hard gates before any alert
- Writes to seller accounts require a two-step unlock
- Diagnostics read "needs a key", never "broken"
Python · FastAPI dashboard · SQLite · Windows installer
Windows service · phone web app
What we do not claim
- Not a commercial product and not an income claim.
- Sourcing depends on third-party data and retailer terms; it is run by one operator for one operator.
Status: Lab project · single operator. We would rather you heard it here.
Where it stands
Phases, stated plainly.
- Walking skeletoncomplete
- Local verification & rankingcomplete
- Sourcing channels & scannercomplete
- Alert quality (sourcing bias)in progress
- Outcome-trained rankingnext
Next step for collaborators.
A conversation about the open problems and how we work.
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