AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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.
npx skills add sickn33/agentic-awesome-skills --skill apify-ecommercegit clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsWrote 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.
[](https://agentmods.dev/skills/sickn33/agentic-awesome-skills/apify-ecommerce)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/apify-ecommerce"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/apify-ecommerce/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/apify-ecommerce"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/apify-ecommerce.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Snyk warn
- NVIDIA SkillSpector warn
SkillSpector: 3 findings, up to high
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- high Privilege Escalation · line 227 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 234 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
- high Privilege Escalation · line 243 Code accesses credential files (SSH keys, AWS credentials, etc.). This could indicate credential theft attempts.Fix: Remove references to credential paths. Use environment variables or secrets managers. For docs, use placeholder paths (e.g., /path/to/config). Never load .env or token files in production code paths.
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00031 | $0.02468 |
| Opus 5.5 | $0.00012 | $0.00987 |
| Sonnet 5.5 | $0.00006 | $0.00494 |
| Haiku 4.5 | $0.00003 | $0.00247 |
Grade A, and why
apify-ecommerce 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 yesterday.
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.
Copies of this mod
8 near-identical copies found in the catalogue:
- apify-ecommerce — 100% identical, 13 lines differ
- apify-ecommerce — 100% identical, 12 lines differ
- apify-ecommerce — 98% identical, 15 lines differ
- apify-ecommerce — 98% identical, 15 lines differ
- apify-ecommerce — 98% identical, 15 lines differ
- apify-ecommerce — 98% identical, 15 lines differ
- apify-ecommerce — 98% identical, 15 lines differ
- apify-ecommerce — 92% identical, 25 lines differ
How it starts
The opening of the file, as written. The whole thing — 279 lines — stays where its author put it; the contents beside it link to each section on GitHub.
E-commerce Data Extraction
Extract product data, prices, reviews, and seller information from any e-commerce platform using Apify's E-commerce Scraping Tool.
When to Use
- You need product, pricing, review, stock, or seller data from e-commerce sites.
- The task involves price monitoring, competitor product comparison, MAP enforcement, or review analysis.
- You need a guided workflow for extracting marketplace data and summarizing findings.
Prerequisites
.envfile withAPIFY_TOKEN(at~/.claude/.env)- Node.js 20.6+ (for native
--env-filesupport)
Workflow Selection
| User Need | Workflow | Best For |
|---|---|---|
| Track prices, compare products | Workflow 1: Products & Pricing | Price monitoring, MAP compliance, competitor analysis. Add AI summary for insights. |
| Analyze reviews (sentiment or quality) | Workflow 2: Reviews | Brand perception, customer sentiment, quality issues, defect patterns |
| Find sellers across stores | Workflow 3: Sellers | Unauthorized resellers, vendor discovery via Google Shopping |
Progress Tracking
Task Progress:
- [ ] Step 1: Select workflow and determine data source
- [ ] Step 2: Configure Actor input
- [ ] Step 3: Ask user preferences (format, filename)
- [ ] Step 4: Run the extraction script
- [ ] Step 5: Summarize results
Workflow 1: Products & Pricing
Use case: Extract product data, prices, and stock status. Track competitor prices, detect MAP violations, benchmark products, or research markets.
Best for: Pricing analysts, product managers, market researchers.
Input Options
| Input Type | Field | Description |
|---|---|---|
| Product URLs | detailsUrls |
Direct URLs to product pages (use object format) |
| Category URLs | listingUrls |
URLs to category/search result pages |
| Keyword Search | keyword + marketplaces |
Search term across selected marketplaces |
Example - Product URLs
{
"detailsUrls": [
{"url": "https://www.amazon.com/dp/B09V3KXJPB"},
{"url": "https://www.walmart.com/ip/123456789"}
],
"additionalProperties": true
}
What ships with it
2 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- yesterday Changed · +2 lines a1af401bbfa5
- 4d ago Changed 4e55fea14b1d
- 1mo ago Changed · +1 lines 171ad52c1f04
- 1mo ago First seen · 276 lines · 31 tokens per session scan A a5125cd00da5
apify-ecommerce is a skill published in the GitHub repository sickn33/agentic-awesome-skills (48,503 stars, last pushed yesterday), licensed MIT. It adds 31 tokens to every session and 2,468 once invoked, about $0.0001 per session on Opus 5.5. 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 2026-09-05.
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