# Yahoo! Auctions Japan Underpriced Deals — Live vs Sold (`jpmarketdata/yahoo-auction-underpriced-deals`) Actor

Which Yahoo! Auctions listings are cheap right now? Builds the sold-comp median for your keyword from closed auctions, then scores every live listing against it and returns the ones below your threshold, with the discount distribution and the comp basis. For resellers and proxy buyers. From $0.02.

- **URL**: https://apify.com/jpmarketdata/yahoo-auction-underpriced-deals.md
- **Developed by:** [h ichi](https://apify.com/jpmarketdata) (community)
- **Categories:** E-commerce, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 75.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $20.00 / 1,000 keyword scanned for deals

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.

Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event

## What's an Apify Actor?

Actors are web data automations that power AI and operations. They run on the Apify platform to scrape websites, process data, connect APIs, and automate workflows.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.

- **AI agents and MCP clients** — the [Apify MCP server](https://docs.apify.com/integrations/mcp.md) at `https://mcp.apify.com` (remote, streamable HTTP, OAuth on first use).
- **Agentic workflows and local Actor development** — [Agent Skills](https://apify.com/.well-known/agent-skills/index.json) with the [Apify CLI](https://docs.apify.com/cli/docs.md): `npm install -g apify-cli`, then `apify login`.
- **JavaScript/TypeScript projects** — the official [JS/TS client](https://docs.apify.com/api/client/js/docs.md): `npm install apify-client`.
- **Python projects** — the official [Python client](https://docs.apify.com/api/client/python/docs.md): `pip install apify-client`.
- **Any other language** — the [REST API](https://docs.apify.com/api/v2.md).

For usage examples, see the [API](#api) section below.

For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).

# README

## Yahoo! Auctions Japan Underpriced Deals — Live vs Sold Comps

Plenty of Actors will tell you what a thing sold for. The question that makes money is **what is mispriced right now**, and answering it needs both books in the same call: the closed-auction median *and* the live listings, scored against each other.

### How the score is built

1. Sample closed auctions for the keyword — **only ones that received a bid**, because an ended auction with no bids is an asking price nobody accepted → **the basis**.
2. Sample the live listings.
3. `discountPct = (1 - price / soldMedian) x 100`.
4. Return everything at or below your threshold, plus the distribution.

### Two guards, because a basis can lie in two ways

**Too few comps.** `minComps` (default 8) refuses a keyword whose median rests on a handful of sales.

**Too many kinds of thing.** A camera search also returns its batteries, cases and manuals. `maxCompSpread` (default 4.0) checks the p75/p25 ratio of the comps and refuses a keyword that mixes price tiers, pointing at the fix:

```json
{ "keywords": ["Nikon Z6"], "priceMinJpy": 50000 }
```

The price band is pushed to Yahoo on **both** sides, so the basis and the candidates cover the same tier.

In both cases the run returns `basisUsable: false` with the reason and **is not charged**. `mixedKeywordLikely` flags the remaining tell: in a coherent market only a small share of the live book sits far under the median, so a high `dealRatePct` means the keyword is still mixed.

### Parse health is part of the output

The live search page is server-rendered HTML, not JSON, and it has sharp edges — cards that cannot be closed on `</li>`, a listing promoted twice per page, a total count that lives in the tab rather than the `<meta>` description (which says *approximately*). `malformedCards` and `duplicateCardsDropped` ship with every summary, so a page redesign shows up as a number rather than as a quietly smaller sample.

### Pricing

From **$0.02** per keyword, $0.002 per individual deal. **An unusable basis is never charged.**

Read-only public pages, no login, throttled requests. Seller identities are never emitted. Nothing is stored between runs.

# Actor input Schema

## `keywords` (type: `array`):

Search terms, e.g. "Nikon Z6". Each keyword gets its own sold-comp basis.

## `dealThresholdPct` (type: `integer`):

A live listing counts as a deal when its current price is at or below this percentage of the sold-comp median. 80 means "20% under the going rate".

## `maxSoldComps` (type: `integer`):

How many sold auctions to sample for the basis. Only auctions that received a bid count as sold.

## `maxLiveListings` (type: `integer`):

How many current listings to score against the basis.

## `minComps` (type: `integer`):

Refuse to score a keyword with fewer sold comps than this. Guards against a median built on two data points.

## `maxCompSpread` (type: `string`):

Coherence ceiling for the basis. A keyword whose sold comps span more than this ratio is mixing price tiers (a camera search also returns its batteries and manuals) and is refused rather than scored.

## `priceMinJpy` (type: `integer`):

Pushed to Yahoo on both sides of the comparison, so the sold basis and the live candidates cover the same product tier.

## `priceMaxJpy` (type: `integer`):

Pushed to Yahoo on both sides, like the minimum.

## `includeIndividualDeals` (type: `boolean`):

Also return each matching auction (charged per deal).

## `convertToUsd` (type: `boolean`):

Add USD figures alongside JPY.

## Actor input object example

```json
{
  "keywords": [
    "Nikon Z6"
  ],
  "dealThresholdPct": 80,
  "maxSoldComps": 120,
  "maxLiveListings": 120,
  "minComps": 8,
  "maxCompSpread": "4.0",
  "includeIndividualDeals": true,
  "convertToUsd": true
}
```

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "keywords": [
        "Nikon Z6"
    ]
};

// Run the Actor and wait for it to finish
const run = await client.actor("jpmarketdata/yahoo-auction-underpriced-deals").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = { "keywords": ["Nikon Z6"] }

# Run the Actor and wait for it to finish
run = client.actor("jpmarketdata/yahoo-auction-underpriced-deals").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "keywords": [
    "Nikon Z6"
  ]
}' |
apify call jpmarketdata/yahoo-auction-underpriced-deals --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,jpmarketdata/yahoo-auction-underpriced-deals"
        }
    }
}

```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/dNEcqAkNWmGaWpZvz/builds/IbTCVQigTBFGle3cA/openapi.json