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Grok Bot+18 agentsE-commerce Competitor Pricing Scraper Setup
Build a local competitor-price monitor with resilient selector fallbacks, SQLite history, markup-drift detection, polite request controls, and cron-ready execution.
$5
E-commerce Competitor Pricing Scraper Setup
Example session with this skill installed
Build a local price monitor for the 35 competitor product URLs in competitors.csv.
I also saved representative product pages in ./html-samples/.
Requirements
- prefer JSON-LD or product metadata before CSS selectors;
- create multiple fallback selectors for price and availability;
- map every competitor product to our merchant_sku;
- store all observations in SQLite;
- never convert failed extraction into price 0;
- add markup-drift and access-review statuses;
- use a polite per-domain delay;
- stop on CAPTCHA or explicit bot-block pages rather than trying to bypass them;
- create a cron example for recurring runs;
- generate a maintenance guide for future HTML changes.
- Read your context and instructions
- Compiled the e-commerce competitor pricing
- Generated the data export
Competitor price-monitor setup complete
Competitor products configured: 35
Representative HTML pages inspected: 12
Products using JSON-LD as primary source: 24
Products using metadata fallback: 7
Products requiring CSS fallback: 4
Product-match reviews required: 2
Extraction strategy
| Source | Primary method | Fallbacks | Status |
|---|---|---|---|
| Competitor A / SKU-100 | JSON-LD offers.price | 3 | READY |
| Competitor B / SKU-205 | product:price:amount | 2 | READY |
| Competitor C / SKU-311 | data-testid="price" | 2 | READY |
| Competitor D / SKU-411 | .product-price | 1 | REVIEW |
Runtime safeguards
- Per-domain delay: 2.5 seconds
- Request timeout: 20 seconds
- Transient retries: 2
- 401 / 403 / 429: stop and review
- CAPTCHA / challenge page: stop and review
- Failed price parse: never stored as 0.00
- Historical observations: append-only SQLite
Example observation
| Field | Value |
|---|---|
| Merchant SKU | SKU-100 |
| Competitor | Competitor A |
| Price | 79.99 USD |
| Method | jsonld:offers.price |
| Status | OK |
Markup-drift behavior
If all configured extraction methods fail, the scraper records:
SELECTOR_DRIFT_REVIEW
The previous valid price remains in history. No fake replacement value is written.
SQLite history
Database
data/price_history.sqlite
Stored data includes
- merchant SKU
- competitor
- URL
- observed price
- currency
- availability
- timestamp
- extraction method
- content hash
- HTTP status
- review status
Files generated
- scraper.py
- scraper_config.json
- sqlite_schema.sql
- run_scraper.sh
- cron.example
- selector_strategy.md
- maintenance_guide.md
- latest_prices.csv
- price_history.sqlite
This package is designed for permitted public-page monitoring with polite request rates. Review site terms, access rules, selector drift, and product matching before production use.
e-commerce-competitor-pricing-scraper-se.csv
CSV · data export
Example file from a real run - the skill writes it into your workspace.
Connects securely to your tools. The creator never sees your data.
What you get
About this skill
The problem
Competitive prices change constantly, while home-grown monitoring scripts break whenever markup changes.
A scraper that works today can fail tomorrow because a competitor removes a class name, changes its product markup, renders price data differently, or starts returning an access challenge.
What it does
E-commerce Competitor Pricing Scraper Setup creates a complete local monitoring package from representative HTML or permitted public product pages.
- Inspects sample HTML for stable price sources
- Prefers JSON-LD and product metadata over brittle DOM paths
- Generates ordered selector fallbacks
- Stores append-only price history in SQLite
- Preserves currency and availability data
- Detects selector drift and extraction failures
- Uses bounded retries and polite per-domain delays
- Stops on blocked or CAPTCHA pages instead of bypassing them
- Creates a cron-ready background runner
- Includes a maintenance workflow for future markup changes
Why this beats prompting it yourself
A generic AI response might generate one BeautifulSoup selector.
This skill builds the complete operating workflow:
HTML Inspection → Selector Strategy → Runtime → SQLite History → Drift Detection → Scheduling → Maintenance
Resilience without anti-bot evasion
The workflow uses multiple legitimate extraction paths and structured-data fallbacks.
It does not include CAPTCHA bypass, stealth browser plugins, proxy rotation, fingerprint spoofing, or authentication bypass.
Local-first price history
Observations are stored locally in SQLite so teams can maintain their own historical pricing dataset without depending on a hosted monitoring service.
How to install
Works the same in every agent - Claude, Cursor, Codex, Copilot and 20+ more.
- 1
Download the ZIP
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- 2
Unzip into your skills folder
Every agent reads skills from one folder on your machine. Drop the unzipped folder in there.
- 3
Ask your agent to use it
Restart the agent if it was already running. It picks the skill up automatically - no config needed.
Skills folder by agent
Click the path to copy it. Create the folder if it does not exist yet.
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