AB 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.
Extract product list from any e-commerce category page, search results page, or keyword search with filters.
As a process B 65/100 · Nearly there — weak spots: result and completion, when it triggers, consistency
How to improve
- Your own cases (evals/evals.json, 4–6 real requests with expected answers): the full check would then run those instead of a model-drafted suite.
- A spec.yaml with trigger phrases and assertions — a behaviour contract for CI; `skilltest init` writes a template.
Guard findings · 0
✓ No critical or high findings
Files scanned: 4. Evidence is masked. Grey chips explain why severity was lowered.
Against the Agent Skills spec
✓ No remarks against the Agent Skills spec
Process rating: all ten parameters 65/100
- 0Progress reporting. Says nothing while it works
- 20When it triggers. No condition that starts the skill
- 40Result and completion. Does not say what the result is
- 40Consistency. Frontmatter name (ecommerce-listing) differs from the folder (ecommerce-listing-skill)
- 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
- 70Inputs and preconditions. Inputs and preconditions are listed
- 100Steps. 27 steps
- 100Failures and branches. 1 branches, has a failure section
- 100Execution cost. Instruction body is 1500 tokens
- 100Running it twice. Mutating operations check current state
- low 10 top-level sections: this looks like several domains in one skill
Everything here is measured from the skill text rather than judged by a model, so the numbers are checkable. A parameter weighs more when it is a more common reason for the process to stall.
Quality signals
- +5Description has no quoted example phrases that should trigger the skill
- +4Description does not say when NOT to use the skill (false activations)
- +3Description length 896: 120–800 characters recommended
- +3Output format is not stated: the model decides each time
- +1No license
- +2Single-language instructions
- +4Structure: 15 headings
- +3Step-by-step instructions: 27 items
- +4Has examples (9 code blocks)
- +3All 2 scripts are documented
Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.