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 AgentComputerAI/torch --skill walmartgit clone --depth 1 https://github.com/AgentComputerAI/torchWrote 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/agentcomputerai/torch/walmart)<a href="https://agentmods.dev/skills/agentcomputerai/torch/walmart"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/walmart/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/agentcomputerai/torch/walmart"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/walmart.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00091 | $0.02268 |
| Opus 5.5 | $0.00036 | $0.00907 |
| Sonnet 5.5 | $0.00018 | $0.00454 |
| Haiku 4.5 | $0.00009 | $0.00227 |
Grade A, and why
walmart 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.
description: Proven scraping playbook for walmart.com. Next.js SPA behind Akamai Bot Manager — curl is 307-redirected to /blocked, but a puppeteer connection to the user's real Chrome (`127.0.0.1:9222`) walks straight th How it starts
The opening of the file, as written. The whole thing — 170 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Walmart (walmart.com)
Walmart is a Next.js storefront fronted by Akamai Bot Manager. Anonymous curl/fetch is hard-blocked (307 →
/blocked?url=...&uuid=...), and a fresh Chromium — even with stealth — gets served interstitials and challenge pages. The single thing that makes it trivial is127.0.0.1:9222: connect to the user's real Chrome and Walmart treats you like a normal shopper. All listing data hydrates from an embedded__NEXT_DATA__JSON blob, so you don't need to reverse any internal APIs.
Detection
| Signal | Value |
|---|---|
| Framework | Next.js (<script id="__NEXT_DATA__"> on every page) |
| CDN / edge | Akamai (x-ak-protocol, ak_p server-timing, TS* cookies) |
| Anti-bot | Akamai Bot Manager + PerimeterX (_pxhd cookie, px-captcha challenges) |
| Auth | Not required for search/browse/PDP |
| robots.txt | Disallows /search for most bots — ignore at your own risk, rate-limit yourself |
Block signature from curl:
HTTP/2 307
location: /blocked?url=<base64>&uuid=<px-uuid>&vid=&g=b
set-cookie: _pxhd=...
Seeing any of /blocked?, _pxhd, or the string "Robot or human" in the body means you're shadow-blocked.
Architecture
- Next.js SSR — the initial HTML already contains the full product grid as JSON inside
<script id="__NEXT_DATA__">. - The grid lives at
props.pageProps.initialData.searchResult.itemStacks[*].items[*], but there are severalitemStacks(main grid, sponsored rails, "popular in category"). Walk the tree and dedupe byusItemId. - Pagination is pure querystring:
&page=1..N. Each page returns ~48–50 items. No cursor, no infinite scroll fallback needed for search results. - PDPs follow the same pattern — hydrated product state in
__NEXT_DATA__.
Strategy used
- Phase 0 (curl): 307 →
/blocked. Skipped. - Phase 1 (framework): Next.js confirmed, but you can't get the HTML without a browser. Skipped.
- Phase 2 (browser):
puppeteer-core.connect({ browserURL: the real Chrome debug port }). No stealth, no cookies, no headers set — the real Chrome profile is already trusted. Walks in on the first try, parses__NEXT_DATA__, done.
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 · 170 lines · 91 tokens per session scan A ef3966845e66
walmart is a skill published in the GitHub repository AgentComputerAI/torch (5 stars, last pushed 6mo ago), licensed MIT. It adds 91 tokens to every session and 2,268 once invoked, about $0.0004 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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