Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/rondoflow/rondoflownpx agentmods add skills/rondoflow/rondoflow/amazon-product-listing-extractorWrote 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/rondoflow/rondoflow/amazon-product-listing-extractor)<a href="https://agentmods.dev/skills/rondoflow/rondoflow/amazon-product-listing-extractor"><img src="https://agentmods.dev/badge/skills/rondoflow/rondoflow/amazon-product-listing-extractor/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/rondoflow/rondoflow/amazon-product-listing-extractor"><img src="https://agentmods.dev/badge/skills/rondoflow/rondoflow/amazon-product-listing-extractor.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00062 | $0.01206 |
| Opus 5.5 | $0.00025 | $0.00482 |
| Sonnet 5.5 | $0.00012 | $0.00241 |
| Haiku 4.5 | $0.00006 | $0.00121 |
Grade A, and why
amazon-product-listing-extractor 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 1mo ago.
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.
How it starts
The opening of the file, as written. The whole thing — 102 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Amazon Product Search Skill
📖 Introduction
This skill utilizes BrowserAct's Amazon Product API template to extract structured product listings from Amazon search results. It provides detailed information including titles, ASINs, prices, ratings, and product specifications, enabling efficient market research and product monitoring without manual data collection.
✨ Features
- No Hallucinations, Reliable Data: Uses a pre-defined workflow to ensure accurate data extraction without AI-generated errors.
- No CAPTCHA Challenges: Built-in mechanisms bypass reCAPTCHA and other bot detection systems.
- Global Access, No Geo-fencing: Overcomes IP restrictions to ensure stable access from any location.
- Fast Execution: More efficient than general-purpose AI browser automation.
- Cost-Effective: Reduces data acquisition costs compared to high-token consumption AI models.
🔑 API Key Workflow
Before running the skill, the BROWSERACT_API_KEY environment variable must be checked. If it is not set, do not proceed; instead, request the key from the user.
Agent Instruction:
"Since you haven't configured the BrowserAct API Key yet, please go to the BrowserAct Console to get your Key and provide it here."
🛠️ Input Parameters
The agent should configure the following parameters based on user requirements:
-
KeyWords
- Type:
string - Description: Search keywords used to find products on Amazon.
- Required: Yes
- Example:
laptop,wireless earbuds
- Type:
-
Brand
- Type:
string - Description: Filter products by brand name.
- Default:
Apple - Example:
Dell,Samsung
- Type:
-
Maximum_number_of_page_turns
- Type:
number - Description: Number of search result pages to paginate through.
- Default:
1
- Type:
-
language
- Type:
string - Description: UI language for the Amazon browsing session.
- Default:
en - Example:
zh-CN,de
- Type:
What ships with it
1 file 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.
- 1mo ago First seen · 102 lines · 62 tokens per session scan A ee1869b382f0
amazon-product-listing-extractor is a skill published in the GitHub repository rondoflow/rondoflow (26 stars, last pushed today), licensed MIT. It adds 62 tokens to every session and 1,206 once invoked, about $0.0002 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 2026-09-03.
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