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BB etsy-shop-catalog

Etsy shop catalog scraper: given an Etsy shop URL (e.g. https://www.etsy.com/shop/{shop-name}) and optional page number, returns paginated product listings from that shop's own storefront with listingId, shopId, title, url, image, salePrice, originalPrice, currency, rating, reviewCount, shopName, isAd, freeShipping, badge. Use when user mentions Etsy shop, Etsy seller, Etsy store, etsy.com/shop, scrape Etsy shop, extract all products from Etsy shop, Etsy shop catalog, Etsy seller catalog, list all Etsy shop items, Etsy storefront scraper, Etsy vendor products, Etsy competitor shop, Etsy shop monitoring, get inventory of an Etsy shop, dump Etsy shop products, Etsy seller product export, seller product benchmarking, Etsy shop bulk export. Also applies to competitor shop tracking, supplier catalog collection, price monitoring for a specific shop, new-item detection on a shop, and any paginated bulk collection driven by a single Etsy shop URL.

browser-act/skills Agent Skills author: browser-act MIT 2 files · 1 script body ≈ 1 686 tokens Open the sourcegithub.com↗ analyzed 6 d ago

Etsy shop catalog scraper: given an Etsy shop URL (e.g. https://www.etsy.com/shop/{shop-name}) and optional page number, returns paginated product listings…

As a process B 67/100 · Nearly there — weak spots: result and completion, when it triggers, running it twice

AnalyzerInfrastructuretype and topics are labelled automatically from the skill text
Runs in: Claude / Claude Code ChatGPT / Codex Gemini CLI Cursor GitHub Copilot / VS Code Qwen Code Kimi Code CLI Z.ai (GLM) DeepSeek (Deep Code) Mistral Vibe LangChain (deepagents) OpenClaw Goose OpenCode
JSON
Technical rating
B
94/100
safety, quality, tests
Safety 60%
100
Quality 40%
84
Run on models
none yet
Process rating
B
67/100
Nearly there
Progress reporting w 2
0
When it triggers w 12
20
Running it twice w 4
30
the three weakest of ten parameters · all ten

How to improve

    For the model run — optional
    • 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: 2. 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 67/100

    • 0Progress reporting. Says nothing while it works
    • 20When it triggers. No condition that starts the skill
    • 30Running it twice. 2 mutating operations with no state check
    • 40Result and completion. Does not say what the result is
    • 60Tools and files. Uses tools (bash, python) that frontmatter does not declare
    • 70Inputs and preconditions. Inputs and preconditions are listed
    • 100Steps. 16 steps
    • 100Failures and branches. 1 branches, has a failure section
    • 100Consistency. Name and required fields are in place
    • 100Execution cost. Instruction body is 1686 tokens
    • 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 953: 120–800 characters recommended
    • +3Output format is not stated: the model decides each time
    • +1No license
    • +2Single-language instructions
    • +4Structure: 14 headings
    • +3Step-by-step instructions: 16 items
    • +4Has examples (1 code blocks)
    • +3All 1 scripts are documented

    Quality base 70; lint remarks subtract, signals add up to 100. Result: 84.