amazon

A scraping guide for Amazon search-result pages. It explains how to obtain the server-rendered product cards and work around Amazon’s CloudFront bot wall using a real Chrome session.

In plain words
What is it for?
Use it to extract product information from Amazon search URLs such as /s?k=... . It covers result pages, pagination, and the fields available in each result card.
Why use it?
Simple command-line requests may receive an error or CAPTCHA instead of search results. The guide identifies the page structure and the browser setup needed to retrieve the data.

Skill for Claude CodeCodex

Install

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.

agentmods
npx agentmods add skills/agentcomputerai/torch/amazon
Any agent
npx skills add AgentComputerAI/torch --skill amazon
Clone the repo
git clone --depth 1 https://github.com/AgentComputerAI/torch

Made for: Claude Code, Codex.

Per session 93 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,368 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce invoked
Fable 5 $0.00093 $0.02368
Opus 5 $0.00046 $0.01184
Sonnet 5 $0.00019 $0.00474
Haiku 4.5 $0.00009 $0.00237

Measured yesterday against content hash 9f02d88f7402, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

amazon scanned grade A with 1 finding 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.

Makes network callslowCapability

Not a fault in itself. Listed so you know the mod talks to something, and to what.

description: Proven scraping playbook for amazon.com search result pages (/s?k=...). CloudFront + CAPTCHA wall blocks bare curl with HTTP 503, but a real Chrome session via the real Chrome debug port walks right through
skills/sites/amazon/SKILL.md · 158 lines

How it starts

The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Amazon (amazon.com)

Amazon search pages are server-rendered HTML behind CloudFront. The only real obstacle is IP/UA reputation on anonymous clients (curl → HTTP/2 503 + x-cache: Error from cloudfront). Attaching to the user's real Chrome profile via 127.0.0.1:9222 defeats the bot wall on the first request — no stealth plugin, no proxy, no captcha solver required. From there it's pure cheerio on 22 s-search-result cards per page.

Detection

Signal Value
CDN CloudFront (via: 1.1 ...cloudfront.net, x-amz-cf-id, x-amz-cf-pop)
Framework Server-rendered HTML (no SPA, no hydration payload needed)
Anti-bot CloudFront + Amazon bot wall. Bare curl with a fake UA → HTTP 503, x-cache: Error from cloudfront. Escalates to Robot Check / CAPTCHA page if you push harder from a clean IP.
Auth Not required for /s search pages.
robots.txt Disallows /s?, but Amazon doesn't enforce it in-band — just don't abuse it.

Architecture

  • /s?k=<query>&page=<n> returns full HTML with 22 result cards per page, already populated (no client-side hydration needed for the fields we care about).
  • Each card is wrapped in div[data-component-type="s-search-result"] with data-asin="<ASIN>".
  • Title lives in h2 span (text). Link is h2 a[href] (relative, may be an /sspa/click?...url=... redirect for sponsored slots).
  • Price is .a-price > .a-offscreen"$83.59".
  • Rating and review count are both encoded in the aria-label of the review link: "Rated 4.5 out of 5 stars by 1,234 reviews. Go to review section." — regex it out, don't trust the nested star spans (they render with inconsistent text).
  • Image: img.s-image[src].
  • Sponsored flag: presence of .puis-sponsored-label-text / .s-sponsored-label-text inside the card.

Strategy used

  • Phase 0 (curl) — failed. curl -A <chrome UA> https://www.amazon.com/s?k=...HTTP/2 503 from CloudFront. Confirmed this is IP/UA reputation, not a missing header.
  • Phase 1 (framework) — skipped. No Next.js __NEXT_DATA__, no clean JSON API on public search. The HTML is the API.
  • Phase 2 (browser)puppeteer.connect({ browserURL: the real Chrome debug port }) to the user's real Chrome. First request loaded full results, no challenge, no captcha. Then page.content() → cheerio. Do not use a fresh Chromium + stealth here; it's a wasted escalation step on Amazon.

Read the full file on GitHub · 158 lines

Changes

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.

  1. yesterday First seen · 158 lines · 93 tokens per session scan A 9f02d88f7402

Subscribe to this mod's changes

amazon is a skill published in the GitHub repository AgentComputerAI/torch (5 stars, last pushed 4mo ago), licensed MIT. It adds 93 tokens to every session and 2,368 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

tiny-web-crawler

Crawl from one or more starting web pages, fetch readable content, search within pages, follow relevant links, and stop when the requested information is found or a bounded limit is reached.

leon-ai/leon · 42 tokens

playwright-cli

Automates browser interactions for web testing, form filling, screenshots, and data extraction. Use when the user needs to navigate websites, interact with web pages, fill forms, take screenshots, test web applications, or extract information from web pages.

VoltAgent/voltagent · 52 tokens

browserstack

../../../engineering-team/playwright-pro/skills/browserstack/SKILL.md.

alirezarezvani/claude-skills · 0 tokens

analyze-performance-traces

Analyze Chrome, Chromium, Electron, React DevTools, or Perfetto-compatible JSON traces and audit user-reported profiling findings without loading large artifacts into context; prove trigger-to-render/layout chains, separate measured facts from source inference, find exact code choke points, classify forced layout and…

tutti-os/tutti · 127 tokens

feature-demo-recording

Record a demo video of a web feature from a real browser. Two modes -- a NARRATED film where measured voiceover drives the timeline (designed slides, subtitles, punch-in camera, rendered from an HTML timeline), and a SILENT evidence clip for a PR or a QA pass. Use when the user asks to record a video, demo, or screen…

kirodotdev/KiroCrew · 90 tokens

browser-recording

Record a browser flow as a video/GIF for evidence — animations, transitions, and multi-step interactions that a still screenshot cannot prove. Drives the project's own Playwright through a bundled runner, then converts to mp4 + GIF via ffmpeg. Use when the user asks to record a demo, capture a GIF or video of the UI…

kirodotdev/KiroCrew · 85 tokens