scraper-models

scraper-models is a cursor rule for Cursor from TheWebScrapingClub/AI-Cursor-Scraping-Assistant. It costs 1,899 tokens per session, scanned A, original, MIT.

A set of coding rules for building web scrapers with Scrapy, a Python framework that collects structured information from websites. It defines the data fields and crawling approach for product-list pages and product-detail pages in online shops.

In plain words
What is it for?
Use it when creating Scrapy spiders for online shops, especially to collect catalogue fields such as prices and product links or detail fields such as size, colour, and description.
Why use it?
It gives a scraper a consistent output format and helps distinguish between collecting many products from a catalogue and collecting full details for one product.

Cursor rule for Cursor

Written for Cursor: a Cursor rule (.mdc).

Good fit Use it when creating Scrapy spiders for online shops, especially to collect catalogue fields such as prices and product links or detail fields such as size, colour, and description.

Compare 6 cursor rules from other repositories ↓
Install with agentmods
npx agentmods add rules/thewebscrapingclub/ai-cursor-scraping-assistant/scraper-models
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Clone the repo
git clone --depth 1 https://github.com/TheWebScrapingClub/AI-Cursor-Scraping-Assistant

Made for: Cursor.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for scraper-models

README.md
[![agentmods](https://agentmods.dev/badge/rules/thewebscrapingclub/ai-cursor-scraping-assistant/scraper-models.svg)](https://agentmods.dev/rules/thewebscrapingclub/ai-cursor-scraping-assistant/scraper-models)
Your own site
<a href="https://agentmods.dev/rules/thewebscrapingclub/ai-cursor-scraping-assistant/scraper-models"><img src="https://agentmods.dev/badge/rules/thewebscrapingclub/ai-cursor-scraping-assistant/scraper-models.svg" alt="Measured on agentmods" height="20"></a>
Per session 1,899 This file is loaded in full into every session.
When invoked 1,899 The same file — it is already loaded in full.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.01899 $0.01899
Opus 5 $0.00949 $0.00949
Sonnet 5 $0.00380 $0.00380
Haiku 4.5 $0.00190 $0.00190

Measured 8d ago against content hash 0b38ed5a7e92, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

scraper-models scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

Copies of this mod

1 near-identical copy found in the catalogue:

cursor-rules/scraper-models.mdc · 96 lines

How it starts

The opening of the file, as written. The whole thing — 96 lines — stays where its author put it; the contents beside it link to each section on GitHub.


description: This rule provides the description of the possible scraper types that can be created. globs: **/*.py

Scraper types

Here's a list of possible scraper types and ther data structures

E-commerce PLP

  • The structure of the items in a PLP scraper is the following: website_name, extraction_date, product_code, item_url, full_price, price, currency, image_url, brand, product_category1, product_category2, product_category3, product_name
  • When asked to create an e-commerce PLP scraper, set items.py file and in the scraper ouput accordingly to the data structure.
  • PLP pages are the product list pages in an e-commerce, also called catalogue pages. In a e-commerce PLP scraper, the scraper should crawl all the product catalog without entering the pages with product details.
  • The scraper will usually start from a home page.

E-commerce PDP

  • The strucutre of the items in a PDP scraper is the following: website_name, extraction_date, product_code, item_url, full_price, price, currency, image_url, brand, product_category1, product_category2, product_category3, product_name, product_description, product_size, product_color, additional_info
  • When asked to create an e-commerce PDP scraper, set items.py file and in the scraper ouput accordingly to the data structure.
  • PDP pages are product detail pages, the final leaf of an e-commerce website. An e-commerce PDP scraper will have in input a list of PDP pages and won't need to crawl the website further.

How to fill the scraper fields with values

  • When asked to map a field of a data structure to the information contained in the HTML, use the following rules:
    • website_name: this is a fixed value per each scraper, usually the website's name in upper case. If in doubt, ask to the operator
    • extraction_date: fixed value for the whole execution, YYYY-MM-DD format. Use datetime library
    • product_code: code that identifies every single product on the website
    • item_url: URL of the page containing the details of the product. If PDP data structure, it corresponds to response.url
    • full_price: price before the discounts. If there's no discount on the item, it's the selling price.
    • price: final selling price after the discounts. If no discount is on the website, it's the selling price.
    • currency: ISO3 Code for currency, fixed value for a whole scraper. Detect the currency from the HTML and use the ISO Code to populate the field
    • brand: brand or producer of the product sold on the website
    • product_category1: first level or product categorization, usually the first level of the breadcrumb of the page, if any.
    • product_category2: second level or product categorization, usually the second level of the breadcrumb of the page, if any.
    • product_category3: third level or product categorization, usually the third level of the breadcrumb of the page, if any.
    • product_name: name of the product as shown on the pages
  • In any case and in any field of a scraper, do not hardcode any value but always find a selector to get the correct one.
  • Always print in output every field of the scraper, even if it's empty.

Read the full file on GitHub · 96 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 96 lines · 1,899 tokens per session scan A 0b38ed5a7e92

Subscribe to this mod's changes

scraper-models is a cursor rule published in the GitHub repository TheWebScrapingClub/AI-Cursor-Scraping-Assistant (55 stars, last pushed 1y ago), licensed MIT. It adds 1,899 tokens to every session, about $0.0095 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.