An agent that watches competitor offers around the clock and works out every price move inside guardrails you set — up when rivals stock out, down only as far as your margin allows — then hands the change list to Flashpricer to execute.
For: All sellersWalmart · Amazon↗ Runs 24/7
The workflow
How the agent runs
1
Set the guardrails
You define min and max per listing (or per strategy). The agent can never price outside them — that's the whole safety model.
2
Watch every competing offer
The agent re-checks the offers on your shared listings via FreshCrawl on a schedule and logs every price, stock, and fulfillment change.
3
Decide the move for each event
Rival stocks out → propose a nudge up. Rival undercuts → propose matching down to your floor, no further. New seller appears → recheck position. Every proposal lands on the change list with its trigger.
4
Log every move
Each change is recorded with its trigger, so you can audit exactly why a price moved at 3 AM.
5
Execute + morning summary
The change list goes to Flashpricer, which applies targets inside your guardrails (or you apply it via your own API integration). One digest: changes proposed, executed, Buy Boxes won back, listings pinned at floor.
What it needs
Inputs & tools
Your listingsSeller ID / catalog
Price dataFreshCrawl (live data)
GuardrailsMin / max per listing
CadenceEvery 15–60 min
DeliveryDigest, 6:30 AM
Your time≈ 10 min/day
The pattern behind Flashpricer: sellers who reprice on a schedule instead of on a hunch stop donating the Buy Box to whoever checked last. The agent version adds the event log — you always know why a price moved.
Run this agent yourself
⚡
1 · Get a FreshCrawl subscription
The agent runs on live marketplace data. FreshCrawl plans start free (1,000 credits), paid plans from $29/mo — every plan includes MCP access and an API key. freshcrawl.io →
🔗
2 · Link the MCP to your LLM
In Claude or ChatGPT, add a custom FreshCrawl MCP connector — server crawl.onewally.com/mcp — and paste your FreshCrawl API key. Your LLM can now pull live offers, Buy Box history, and sales estimates itself.
📋
3 · Paste the prompt
Copy the prompt below into your LLM and name your store. The agent runs against the live data it can now reach — no code, no exports.
Copy the prompt
Starter prompt
Step 3 · Paste this into your LLM
# Repricing Watchdog
MY STORE (fill in once):
- Store name: [your store name]
- Seller ID or storefront URL: [paste it — the agent uses it to find your catalog]
- Marketplace: [Walmart US / Amazon US]
First, use the FreshCrawl MCP to look up my store, pull my catalog,
and work only on my listings. If you can't identify my store from
what I gave you, ask me for my storefront URL before anything else.
RUN SCHEDULE (set this where you run the prompt):
- Run this prompt: every 30 minutes (hot listings: every 15).
- If your LLM app supports scheduled/recurring tasks, set it there; otherwise re-paste the prompt on that cadence.
For my shared listings, check every competing offer on the schedule I set above. When a rival is out of stock and I hold the Buy Box, propose +2% (never above my max). When a rival undercuts me and I lose the Buy Box, propose their price minus $0.01 (never below my min). Output a PRICE CHANGE LIST — listing, current price, target price, trigger, guardrail check — plus the listings stuck at my floor. Summary at 6:30 AM daily.
EXECUTION — READ CAREFULLY:
You have NO price-writing access — the FreshCrawl MCP is read-only data. Do not claim you changed any price. Your output is a PRICE CHANGE LIST: listing, current price, target price, the trigger, and the guardrail check. I execute changes through Flashpricer (it applies targets inside my min/max automatically) or through my own marketplace API integration. Mark a change 'applied' only after I confirm it executed.
The prompt gets you the shape. The reliable version runs on live data through the MCP — that's steps 1 and 2 above.
Finds below-MAP listings across the web daily and builds the enforcement evidence pack.
Questions sellers ask
Will it start a price war?
No — the floor is a hard limit. The agent stops at your minimum and flags the listing for a human decision instead of chasing a rival below your margin.
How is this different from a normal repricer?
A repricer executes rules; the watchdog also watches events (stock-outs, new sellers, fulfillment changes), explains its moves in plain language, and escalates the judgment calls.
Which marketplaces?
Walmart and Amazon — anywhere offers compete for one featured position.
How do the price changes actually happen?
The agent decides; it cannot write prices — the FreshCrawl MCP is read-only on purpose. Execution is Flashpricer's job (it applies the targets inside your min/max automatically), or your own marketplace API integration if you've built one. The prompt is written so the agent never claims a price changed until execution is confirmed.
Run this on your store.
Every agent here runs on live FreshCrawl data through the MCP. Start free, connect your LLM, paste the prompt — or get the free Buy Box Loss Report and see the data first.