---
name: ecommerce-seller-info
description: Extracts seller or merchant profile data from marketplace platform seller pages, including name, rating, review count, feedback percentage, joined date, and return policy.
---

# E-commerce — Seller Info

> Seller/merchant profile URL → seller name, rating, review count, feedback, joined date, return policy

## Language

All process output to user (progress updates, process notifications) follows the user's language.

## Objective

Extract seller profile information from marketplace platform seller or storefront pages using JSON-LD structured data and platform-specific DOM patterns.

## Prerequisites

- Target browser is open and connected
- No login required for public seller profile pages

## Pre-execution Checks

### 1. Tool Readiness

If browser-act has been confirmed available in the current session → skip this step.

Invoke `browser-act` via Skill tool to load usage. If installation or configuration issues arise, follow its guidance to resolve then retry.

## Capability Components

> This Skill's operational boundary = what the user can manually do in their browser. It only reads data already displayed to the user on the page. JS code is encapsulated in Python files under the `scripts/` directory, invoked via `eval "$(python scripts/xxx.py {params})"`. Use the bash tool for execution.

### DOM: Extract seller profile from current seller page

Navigate to the seller profile URL first, then extract:

```bash
eval "$(python scripts/extract-seller.py)"
```

Output example:
```json
{
  "url": "https://www.amazon.com/shops/seller/A1234567890",
  "name": "TechGadgets Store",
  "description": "Premium electronics accessories since 2015",
  "rating": 4.8,
  "review_count": 12450,
  "positive_feedback_pct": "98% positive feedback",
  "joined": "Member since: January 2015",
  "return_policy": "30-day returns accepted",
  "image": null,
  "_platform": "amazon"
}
```

### Composite: Amazon seller URL patterns

Amazon seller pages follow these URL patterns:

| Seller page type | URL |
|-----------------|-----|
| Seller storefront | `https://www.amazon.com/shops/{seller_id}` |
| Seller feedback (from product page) | Click "Sold by {seller_name}" link on a product page |
| Third-party seller ratings | `https://www.amazon.com/gp/seller/{seller_id}/ref=dp_byline_sr` |

To find a seller from a product page:
1. Navigate to product page → `wait stable`
2. `eval "document.querySelector('#sellerProfileTriggerId, #merchant-info a')?.href"` to get the seller URL
3. `navigate {seller_url}` → `wait stable`
4. `eval "$(python scripts/extract-seller.py)"`

### Composite: eBay seller URL patterns

| Seller page type | URL |
|-----------------|-----|
| eBay seller storefront | `https://www.ebay.com/str/{seller_username}` |
| eBay seller feedback | `https://www.ebay.com/usr/{seller_username}` |

To find seller from an eBay listing:
1. Navigate to eBay item page → `wait stable`
2. `eval "document.querySelector('.x-sellercard-atf__data a[href*=\"/usr/\"]')?.href"` to get seller URL
3. Navigate and extract

## Success Criteria

`result.name != null`

## Known Limitations

- Amazon seller pages may require navigating from `https://www.amazon.com` first on fresh sessions to avoid bot detection
- eBay seller pages may require navigating from `https://www.ebay.com` first
- Seller description and return policy availability depends on whether the seller has filled in their profile
- Rating scale differs by platform: Amazon uses 1–5 stars, eBay uses percentage of positive feedback; both are preserved in their native format

## Execution Efficiency

- **Batch orchestration**: Loop through seller URLs serially; add 1–2 second intervals between navigations
- **Test before batch execution**: Test with 1–2 sellers before running the full batch
- **Error resumption**: Save results item by item; on failure, resume from the breakpoint

## Experience Notes

Path: `{working-directory}/browser-act-skill-forge-memories/ecommerce-scraper-ecommerce-seller-info.memory.md`

**Before execution**: If the file exists, read it first — it records unexpected situations encountered during past executions; adjust strategy order accordingly.

**After execution**: If an unexpected situation is encountered (strategy became ineffective, page redesigned, anti-scraping upgraded, better path discovered), append a line:
`{YYYY-MM-DD}: {what happened} → {conclusion}`