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ArbiPulse Flip-Check — Resale Arbitrage Verdict
x402
ArbiPulse Flip-Check — Resale Arbitrage Verdict is a paid API for AI agents from arbipulse.theaslangroupllc.com, paid per call via x402, $0.5/call, status unknown (last checked 2026-09-14).
Analyzes a physical item (e.g. sealed collectible, toy, electronics) and returns a buy/sell arbitrage verdict with estimated profit and ROI at median comparable sale price
Price / call$0.5
Success—
StatusUnknown
How this service works
Retail resale arbitrage check — "if I buy this at this price, what do I clear reselling it?" Live eBay ask comps (each linked to its listing; web-grounded fallback), fee math for eBay/Amazon/StockX/Poshmark/Mercari, profit + ROI at low/median/high comps, best-venue table, FLIP / THIN / PASS verdict. Returns INSUFFICIENT_EVIDENCE rather than an invented price.
Output
Returns a JSON object with the item name, a verdict label (e.g. THIN, GOOD), the buy price input, and at-median-comp projections including expected profit in dollars and ROI percentage, based on comparable market sales data.
Example use cases
Collectible toy flip evaluation
“I found a sealed Lego 42143 Lamborghini for $280 at a garage sale — run a flip check and tell me if there's a decent profit margin at that buy price.”
Sneaker resale opportunity check
“Is a pair of Nike Air Jordan 1 Chicago 2015 in deadstock condition worth flipping if I can get them for $400? Give me the verdict and estimated ROI.”
Video game arbitrage assessment
“I can buy a factory sealed copy of Earthbound on SNES for $180 — do a flip check and tell me if that's a THIN or solid opportunity with projected profit.”
Technical details
Endpoint
GEThttps://arbipulse.theaslangroupllc.com/api/flip-checkWhen to prefer
Use this endpoint when you need a fast, quantified verdict on whether a specific physical item is worth buying for resale, with profit and ROI estimates against median comparable sales — ideal for retail arbitrage bots, deal-scanning agents, or reseller assistants evaluating collectibles, toys, sneakers, or electronics. Prefer this over manual comp lookups or generalist price APIs when you want a structured THIN/GOOD verdict with P&L math already computed.
Side effects
- Unknown or ambiguous item name returns low-confidence or empty comp data
- Very niche items with no comparable sales data may return null projections
- Incorrect buy price input yields misleading ROI figures
- Rate limiting or payment failure returns 402 error requiring USDC payment
- Item with no liquid resale market may return THIN verdict with zero comps
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "json",
"example": {
"item": "Lego 75192 sealed",
"verdict": "THIN",
"buy_price": 550,
"at_median_comp": {
"profit": 66.5,
"roi_pct": 12.1,
"sale_price": 720
}
}
}Tags
x402
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