# eBay Sold Listings Price Decision Pack (`theendfear/factory-ebay-sold-listings-price-decision-pack`) Actor

Post-process an explicit upstream Actor dataset or equivalent records into deterministic decision-ready rows.

- **URL**: https://apify.com/theendfear/factory-ebay-sold-listings-price-decision-pack.md
- **Developed by:** [Marco S.](https://apify.com/theendfear) (community)
- **Categories:** E-commerce, Business
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

$15.00 / 1,000 post-processed decision rows

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/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
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.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## 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.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For examples already wired to this Actor's own input schema, see the [API](#api) section below.

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).

# README

## eBay Sold Listings Price Decision Pack

Post-process datasets from `eBay Sold Listings Search` into deterministic decision-ready rows. This Actor does not run the upstream Actor by itself; it reads an explicitly provided `datasetId`/`defaultDatasetId` or equivalent direct `records`.

### What It Does

It validates the upstream dataset contract, normalizes required fields, removes duplicates, preserves source attribution, applies explicit rule scoring, and emits a new output contract for downstream workflows.

### Who It Is For

Operators who already run the upstream Actor and need a bounded post-processing layer with repeatable validation, scoring, and integration-ready output.

### Input

Use `datasetId` or `defaultDatasetId` for an existing Apify dataset, or provide `records` directly. Required upstream fields: title, soldPrice, currency, soldAt.

### Output

Each row includes `sourceActorId`, `sourceDatasetId`, `sourceRecordIndex`, `normalizedKey`, `score`, `decision`, `ScoreExplanation`, and `sourceAttribution`.

### How It Works

The F1 pattern is schema-first: resolve dataset or direct records, validate required upstream fields, normalize, deduplicate, score with deterministic thresholds, attach source attribution, and emit only valid post-processed rows.

Recommended action derivation is explicit: score 80 or higher means `prioritize`, score 65-79 means `review`, and lower scores mean `monitor`. Score contributions are required-field completeness plus observed numeric signal strength; every emitted row includes `ScoreExplanation`.

### Example

```json
{ "datasetId": "abc123", "maxRecords": 5000 }
```

### Pricing

PAY\_PER\_EVENT event `post_processed_record_emitted` is charged once per valid post-processed row emitted. Invalid records, duplicates, empty datasets, and rows skipped by charge limits are not billable.

### Limitations

This is not a wrapper pass-through and it does not claim to acquire upstream data. Upstream acquisition cost is separate from post-processor cost. If the upstream schema fingerprint changes incompatibly, the Actor fails closed with a schema mismatch report.

### Integration

Use it standalone after an upstream run or as an integration target in a workflow. Direct upstream execution may be added later only when it can stay within LIMITED\_PERMISSIONS and explicit cost accounting.

# Changelog

This Actor's version history is a separate document: https://apify.com/theendfear/factory-ebay-sold-listings-price-decision-pack/changelog.md

# Actor input Schema

## `datasetId` (type: `string`):

Optional Apify dataset ID produced by the named upstream Actor.

## `defaultDatasetId` (type: `string`):

Alternative storage reference for upstream default dataset.

## `records` (type: `array`):

Optional direct records equivalent to the upstream dataset schema.

## `maxRecords` (type: `integer`):

Maximum number of upstream rows to process in one run.

## `expectedUpstreamSchemaFingerprint` (type: `string`):

Optional schema fingerprint guard for future drift checks.

## Actor input object example

```json
{
  "maxRecords": 5000
}
```

# Actor output Schema

## `results` (type: `string`):

Post-processed rows in the default dataset.

# 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 = {};

// Run the Actor and wait for it to finish
const run = await client.actor("theendfear/factory-ebay-sold-listings-price-decision-pack").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 = {}

# Run the Actor and wait for it to finish
run = client.actor("theendfear/factory-ebay-sold-listings-price-decision-pack").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 '{}' |
apify call theendfear/factory-ebay-sold-listings-price-decision-pack --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,theendfear/factory-ebay-sold-listings-price-decision-pack"
        }
    }
}
```

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/5yJ70jHjTcdj3EBtH/builds/eYtXw6lAAm39q8OyL/openapi.json