Apify Ecommerce

apify/apify-ecommerce

Scrape e-commerce data for pricing, reviews, bestsellers, and seller discovery across 30+ platforms including Amazon, Walmart, eBay, Shopify, WooCommerce, and more. Use when user asks about product prices, competitor analysis, store scraping, tech stack detection, food delivery, real estate, or marketplace intelligence.

3k tokens

context cost

the whole folder, loaded on every use

files

instructions only

copies elsewhere

how many repositories repackaged it

239

stars on the repo

on the repository, not the skill itself

Install

one command, takes just this skill from the repository

npx skills add https://github.com/apify/awesome-skills --skill apify-ecommerce

The instruction itself

9 sections, as written by the author

E-Commerce Cluster

Answer natural language e-commerce questions by routing to the right Apify Actor and delivering a synthesized answer via the apify CLI.

CLI rules: Always pass --user-agent apify-awesome-skills/apify-ecommerce, --json (or the relevant --format flag on datasets get-items), and 2>/dev/null. The --user-agent flag is critical for telemetry — never omit it.

Prerequisites

(No need to check it upfront)

Apify CLI v1.5.0+ (npm install -g apify-cli)
jq (recommended for quick extraction and filtering; brew install jq on macOS, apt install jq on Linux)
Authentication via one of:
apify login (OAuth, opens browser)
APIFY_TOKEN env variable (e.g. export APIFY_TOKEN=... or .env file)
Token from Apify Console → Settings → Integrations

Verify auth: apify info --user-agent apify-awesome-skills/apify-ecommerce — should show username and userId.

Workflow

Copy this checklist and track progress:

Task Progress:
- [ ] Step 1: Detect intent and select Actor
- [ ] Step 2: Fetch Actor schema
- [ ] Step 3: Ask user preferences (format, result count)
- [ ] Step 4: Run the Actor and fetch results
- [ ] Step 5: Analyze results and deliver synthesized answer

Step 1: Detect Intent and Select Actor

Classify the user's message into an intent, then pick the right Actor.

Intent signals:

| Signals in user message | Intent |

|------------------------|--------|

| price, cost, cheapest, compare prices, pricing | pricing |

| review, rating, sentiment, stars, feedback | reviews |

| bestseller, top selling, most popular, trending | bestsellers |

| seller, vendor, reseller, who sells | sellers |

| all products from, scrape store, full catalog | store-scrape |

| what platform, built on, tech stack, Shopify or WooCommerce | tech-stack |

| SEO, listing quality, product page audit | seo-audit |

| competitor funnel, competitor pricing, conversion elements | competitor |

| search intent, keyword intent, SERP intent | search-intent |

| match products, same product on different platforms | product-matching |

| restaurant, food delivery, DoorDash, UberEats, TheFork | food-delivery |

| enrich store, store metadata, store list | store-enrichment |

| event, concert, ticket, Eventbrite | events |

| property, real estate, house listing, Realtor | real-estate |

| Facebook ads, Meta ads, ad library, competitor ads | ads-intelligence |

| classified, Craigslist, used item for sale | classifieds |

| car, used car, vehicle, automotive, Webmotors | automotive |

| pins, inspiration, Pinterest boards, visual search, Pinterest trends | content-discovery |

| TikTok Shop, TikTok store, TikTok creator | tiktok-shop |

| website for sale, domain for sale, Flippa | website-marketplace |

If multiple intents are detected, ask: *"Do you want [intent A] or [intent B]?"*

Actor routing table — always try Primary first, switch to Fallback only if it fails or returns 0 results:

|--------|----------|---------------|----------------|

Step 2: Fetch Actor Schema

Fetch the Actor summary, input schema, and README:

# Summary (title, description, pricing, stats)
apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-ecommerce --json 2>/dev/null

# Input schema (required and optional parameters; schema lives in
# .taggedBuilds.latest.build.inputSchema as an escaped JSON string)
apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-ecommerce --input --json 2>/dev/null

# README (capabilities, examples, gotchas)
apify actors info "ACTOR_ID" --user-agent apify-awesome-skills/apify-ecommerce --readme 2>/dev/null

Replace ACTOR_ID with the selected Actor (e.g., apify/e-commerce-scraping-tool).

Step 3: Ask User Preferences

Before running, ask:

Output format:
Quick answer (default) — synthesized answer in chat, no file saved
CSV — full export saved to disk
JSON — full export saved to disk
Result count — suggest defaults by intent:

| Intent | Default |

|--------|---------|

| pricing | 50 products |

| reviews | 200 reviews |

| bestsellers | 100 items |

| sellers | 50 sellers |

| store-scrape | all (unlimited) |

| food-delivery | 50 restaurants |

| all others | 20–50 |

Cost safety: Always set a sensible result limit in the Actor input (e.g., maxResults, resultsLimit, maxCrawledPages, or equivalent field from the input schema). Default to the per-intent values above unless the user explicitly asks for more. Warn the user before running large scrapes (1000+ results) as they consume more Apify credits.

Step 4: Run the Actor and Fetch Results

Two steps: run the Actor (blocks until done), then fetch dataset items in the requested format.

Run the Actor — returns run metadata as JSON; extract defaultDatasetId for the next step:

apify actors call "ACTOR_ID" -i 'JSON_INPUT' \
  --user-agent apify-awesome-skills/apify-ecommerce --json 2>/dev/null

From the output use .id (run ID), .status (should be SUCCEEDED), and .defaultDatasetId.

Fetch results — pick the variant based on the user's preference:

# Quick answer: total count + fields + top 5 in chat (no file)
apify datasets info DATASET_ID --json \
  --user-agent apify-awesome-skills/apify-ecommerce 2>/dev/null \
  | jq '{itemCount, fields, consoleUrl}'
apify datasets get-items DATASET_ID --limit 5 \
  --user-agent apify-awesome-skills/apify-ecommerce --format json 2>/dev/null

# CSV file
apify datasets get-items DATASET_ID \
  --user-agent apify-awesome-skills/apify-ecommerce --format csv 2>/dev/null > YYYY-MM-DD_OUTPUT_FILE.csv

# JSON file
apify datasets get-items DATASET_ID \
  --user-agent apify-awesome-skills/apify-ecommerce --format json 2>/dev/null > YYYY-MM-DD_OUTPUT_FILE.json

Other --format options: jsonl, xlsx, xml, rss, html. Use --offset N to paginate large datasets.

Tip: for anything more than a quick peek, save the dataset to a local file first (with > file.json / > file.csv) and run further analysis from disk. apify datasets get-items always streams over the network, so piping it straight into jq re-downloads the whole thing every iteration.

Combining with jq for quick extraction:

Treat jq as a complement to apify datasets get-items, not a replacement: server-side --limit / --offset / --format keeps cost and bandwidth down. Use jq on a sample item or on a file you already saved.

# Discover real field names from one sample item (Actor outputs vary —
# use this before composing further jq queries)
apify datasets get-items DATASET_ID --limit 1 --format json \
  --user-agent apify-awesome-skills/apify-ecommerce 2>/dev/null \
  | jq '.[0]'

# Quick aggregation from a JSON file you already saved with the commands above
jq '[.[] | select(.rating != null and .rating >= 4.5)] | length' YYYY-MM-DD_OUTPUT_FILE.json

Step 5: Analyze Results and Deliver Answer

After the run completes, deliver a direct synthesized answer — not a data dump:

Pricing: price range, average, top 5 cheapest with URLs
Reviews: average rating, top 3 positive and negative themes, recent snippets
Bestsellers: top 10 by rank with name, price, rating, URL
Sellers: total sellers, price range per seller, unauthorized seller flags
Store-scrape: total products, category breakdown, price range, stock summary
Tech-stack: platform detected, confidence level, notable plugins
Food delivery: restaurant count, average rating, price tier breakdown
Ads intelligence: total ads, active/inactive split, top creative formats

Error Handling

Auth error → run apify login, or set APIFY_TOKEN env var
Actor not found → check Actor ID spelling in the routing table
Run status FAILED → open the console URL (.consoleUrl from run metadata) for logs
Timeout / very long run → pass --timeout <seconds> to apify actors call
No results → broaden the keyword or switch to a Fallback Actor from the routing table
proxy is required → add "proxy": {"useApifyProxy": true} to the Actor input
Platform not detected → default to apify/e-commerce-scraping-tool with generic intent

How to use it

Copy the folder

Take apify/apify-ecommerce from the repository into ~/.claude/skills for personal use, or into .claude/skills inside a project.

Check the name does not clash

The agent identifies a skill by the name field in its header. Two skills with the same name cannot sit side by side — one of them will be ignored.

Install what it needs

The instructions reference npm, brew. Without those the skill loads but fails at the first command.