Ecommerce Listing logo

Ecommerce Listing

OrganizationPopular
browser-act
ecommerce-listing

Extract product list from any e-commerce category page, search results page, or keyword search with filters. Returns paginated product arrays with URL, name, price, currency, image, rating, review count per item. Supports URL input, keyword search, and site-scoped search with filters: price range, brand, category, minimum rating, in-stock only, and sort order. Works on Amazon, eBay, Walmart, Shopify collections, WooCommerce shops, Google Shopping, and any public product listing page. Use when: category listing, product search results, ecommerce search, search for products, filter products by price, list products from a site, price range filter, brand filter, keyword search with filters, scrape product list, product catalog extraction, get all products from category, bulk product URLs, product list scraping, category page scraper, search results scraper, multi-page product extraction.

Overview

Publisherbrowser-act
Repositoryskills
Skill nameecommerce-listing
Stars
5.9K
Forks
295
Bundled files
2
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 2 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by browser-act on GitHub. Read the source before you install it.

Installation

Install the Ecommerce Listing AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/browser-act/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/solutions/ecommerce/ecommerce-listing .claude/skills/ecommerce-listing
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ecommerce Listing in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ecommerce Listing on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ecommerce Listing is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

E-commerce — Product Listing

Category/search URL or keyword + filters → paginated product list (URL, name, price, image, rating per item)

Language

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

Objective

Extract a structured list of products from any e-commerce category, search results, or keyword search page, with support for price/brand/rating filters and multi-page pagination.

Prerequisites

  • Target browser is open and connected
  • No login required for public listing 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 product list from current page

Navigate to the listing/search page first, then extract:

bash
eval "$(python scripts/extract-listing.py --max-results 20)"

Parameters:

  • --max-results: max items to return per page, default 20

Output example:

json
{
  "count": 20,
  "items": [
    {
      "url": "https://www.amazon.com/dp/B09WNK39JN",
      "name": "Amazon Echo Pop",
      "price": 39.99,
      "currency": "USD",
      "image": "https://m.media-amazon.com/images/I/...jpg",
      "rating": 4.7,
      "review_count": 103789,
      "asin": "B09WNK39JN"
    }
  ]
}

DOM: Get next page URL

After extracting a page, get the URL to navigate to for the next page:

bash
eval "$(python scripts/extract-listing-next-page.py)"

Output example:

json
{"next_url": "https://www.amazon.com/s?k=headphones&page=2", "has_next": true, "method": "amazon"}

When has_next is false, pagination is complete.

Composite: Keyword search with filters → product list

Step 1 — Build search URL with filters:

Construct the URL based on target site and desired filters using the patterns below, then navigate:

Amazon (amazon.com):

https://www.amazon.com/s?k={keyword_urlencoded}&s={sort}&rh={filter_params}
  • Sort (s): price-asc-rank | price-desc-rank | review-rank | date-desc-rank (omit for relevance)
  • Price filter: append p_36:{min_cents}-{max_cents} to rh (dollars × 100, e.g. $50–$200 → p_36:5000-20000)
  • Rating filter: append avg_customer_review:four-and-above | three-and-above | two-and-above to rh
  • In-stock: append p_n_availability:1248801011 to rh
  • Multiple rh values: comma-separate (e.g. rh=p_36:5000-20000,avg_customer_review:four-and-above)

eBay (ebay.com):

https://www.ebay.com/sch/i.html?_nkw={keyword_urlencoded}&_udlo={min_price}&_udhi={max_price}&_sop={sort_num}
  • Sort: 12=BestMatch | 15=PriceLow | 16=PriceHigh | 24=NewlyListed

Walmart (walmart.com):

https://www.walmart.com/search?q={keyword_urlencoded}&min_price={min}&max_price={max}&sort={sort}
  • Sort: best_match | price_low | price_high | rating_high

Google Shopping (cross-site, no --site):

https://www.google.com/search?tbm=shop&q={keyword_urlencoded}&tbs=p_ord:{sort}
  • Sort: rv=relevance | pd=price ascending | prd=price descending

Any site with --site (generic):

https://{site}/search?q={keyword_urlencoded}

Step 2 — Navigate and extract:

  1. navigate {constructed_url}wait stable
  2. eval "$(python scripts/extract-listing.py --max-results {n})"

Step 3 — Paginate (repeat until done):

  1. eval "$(python scripts/extract-listing-next-page.py)"
  2. If has_next is true: navigate {next_url}wait stable → re-run extract-listing.py
  3. If has_next is false: stop

Pagination

URL Pagination: extract-listing-next-page.py detects rel=next link, platform-specific pagination controls, and URL page parameters. Returns next_url for navigation.

DOM Pagination: For sites with load-more buttons (some Shopify themes):

  1. state to find "Load more" or "Show more" button
  2. click <index>wait stable → re-run extract-listing.py
  3. Termination: button no longer present, or item count stops increasing

Success Criteria

result.count >= 1 AND items[0].url != null

Known Limitations

  • Amazon: direct navigation may trigger bot detection on fresh sessions — navigate from https://www.amazon.com first
  • eBay listing pages may require navigating from https://www.ebay.com first
  • Google Shopping results have complex SPA structure and may have reduced accuracy; prefer direct site search when --site is specified
  • Filter URL parameters are site-specific; unsupported filter parameters are silently ignored by some sites
  • Shopify themes vary widely; if the generic DOM strategies miss items, check if the page has JSON-LD ItemList or Product array in page source

Execution Efficiency

  • Batch orchestration: Loop through pages serially within a single session; add 1–2 second intervals between page navigations
  • Test before batch execution: Test with 1 page before running multi-page extraction
  • Error resumption: Record page number; on failure, resume from the last successful page

Experience Notes

Path: {working-directory}/browser-act-skill-forge-memories/ecommerce-scraper-ecommerce-listing.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}

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ecommerce Listing AI skill do?

Extract product list from any e-commerce category page, search results page, or keyword search with filters. Returns paginated product arrays with URL, name, price, currency, image, rating, review count per item. Supports URL input, keyword search, and site-scoped search with filters: price range, brand, category, minimum rating, in-stock only, and sort order. Works on Amazon, eBay, Walmart, Shopify collections, WooCommerce shops, Google Shopping, and any public product listing page. Use when: category listing, product search results, ecommerce search, search for products, filter products b...

Why use Ecommerce Listing on TypingMind?

Because you install it once and use it with any model. Ecommerce Listing is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ecommerce Listing in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/browser-act/skills/tree/main/solutions/ecommerce/ecommerce-listing. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ecommerce Listing?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ecommerce Listing?

As many as you like. As long as a model supports skills, you can use Ecommerce Listing with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ecommerce Listing AI skill free?

Yes. It is published on GitHub by browser-act under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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