A scraping guide for Apple's online product-configuration pages, such as the Mac, iPhone, iPad, and Watch buying pages. It explains how to read product, price, colour, chip, storage, and other configuration data embedded in the page's HTML.

Use it to extract product options and prices from Apple's supported shop buying pages.

It provides a way to collect the configuration data with a normal page request instead of relying on a browser or separate network calls. The input describes Apple's page structure and extraction approach.

apple — Skill for Claude Code and Codex by AgentComputerAI/torch

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.

Any agent

npx skills add AgentComputerAI/torch --skill apple

Clone the repo

git clone --depth 1 https://github.com/AgentComputerAI/torch

Made for: Claude Code, Codex.

Wrote 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.

README.md

[![agentmods](https://agentmods.dev/badge/skills/agentcomputerai/torch/apple/github.svg)](https://agentmods.dev/skills/agentcomputerai/torch/apple)

Your own site

<a href="https://agentmods.dev/skills/agentcomputerai/torch/apple"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/apple/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.

Your own site · 80×15

<a href="https://agentmods.dev/skills/agentcomputerai/torch/apple"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/apple.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 127 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.

When invoked 2,487 The whole file, excluding the scripts and references it only reads on demand.

Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.

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.

Model	Per session	Once invoked
Fable 5.1	$0.00127	$0.02487
Opus 5.5	$0.00051	$0.00995
Sonnet 5.5	$0.00025	$0.00497
Haiku 4.5	$0.00013	$0.00249

Measured 1mo ago against content hash ca4ff99a44b6, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

apple 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 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.

Makes network callslowCapability

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

| Status | 200 to bare `curl` with no UA tricks |

skills/sites/apple/SKILL.md · 179 lines

How it starts

The opening of the file, as written. The whole thing — 179 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Apple Store buy-flow (apple.com/shop/buy-*)

Apple's online store is a thin client over a giant SSR HTML page. The configurator state — every SKU, color, chip, price, customization option — is embedded inline as JavaScript object literals. No XHRs needed: fetch the page, find the bootstrap, extract the inner JSON. Sub-second scrape, 0 anti-bot.

Detection

Signal	Value
Server	`Server: Apple` (custom edge, not Akamai/CF)
Status	200 to bare `curl` with no UA tricks
Framework	Custom AS (Apple Store) buyflow — not Next/Nuxt
Anti-bot	None on `/shop/buy-*` HTML
robots.txt	Allows `/shop/buy-*` for Googlebot etc.
Auth	None required

Architecture

The buyflow page ships ~550 KB of HTML containing several window.*_BOOTSTRAP = blocks injected by the server:

window.PRODUCT_SELECTION_BOOTSTRAP — the one you want. Holds productSelectionData with products[], mainDisplayValues (colors, sizes, chips, prices), and configDisplayValues (memory, storage, adapter, keyboard).
window.PURCHASE_OPTIONS_BOOTSTRAP — checkout/financing options.
window.APPLECARE_BOOTSTRAP — AppleCare add-ons.
window.TRADEUP_BOOTSTRAP — trade-in calculator data.
window.LOCATION_BOOTSTRAP, window.ECHO_CONFIG, window.GLOBAL_ASSETS, window.NAMED_ASSETS, window.ACI_CONFIG_MAP, window.BUYFLOW_MESSAGES_BOOTSTRAP — UI/i18n/asset metadata.

The React-ish client just hydrates from these. There is no /api/ you need to call for the configurator — everything is server-printed.

Strategy used

Phase 0 (curl) — curl -sL returns 200 with the full HTML. Done.
Phase 1/2 skipped.

Stealth config

None required. Plain fetch works. One gotcha: Node's undici occasionally hangs on Apple's edge over IPv6 (ETIMEDOUT from internalConnectMultiple). Force IPv4:

Read the full file on GitHub · 179 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.

1mo ago First seen · 179 lines · 127 tokens per session scan A ca4ff99a44b6

Subscribe to this mod's changes

apple is a skill published in the GitHub repository AgentComputerAI/torch (5 stars, last pushed 6mo ago), licensed MIT. It adds 127 tokens to every session and 2,487 once invoked, about $0.0005 per session on Opus 5.5. 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.

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apple