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 yelpgit 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/yelp)<a href="https://agentmods.dev/skills/agentcomputerai/torch/yelp"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/yelp/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/yelp"><img src="https://agentmods.dev/badge/skills/agentcomputerai/torch/yelp.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 | $0.00125 | $0.02391 |
| Opus 5.5 | $0.00050 | $0.00956 |
| Sonnet 5.5 | $0.00025 | $0.00478 |
| Haiku 4.5 | $0.00013 | $0.00239 |
Grade A, and why
yelp 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 yelp.com search result pages (/search?find_desc=...&find_loc=...). Yelp is behind DataDome — bare curl gets HTTP 403 with `server: DataDome` and a captcha-delivery interstitial. How it starts
The opening of the file, as written. The whole thing — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Yelp (yelp.com)
Yelp's SERP is fully server-rendered HTML wrapped in a DataDome anti-bot. The trick is not to fight DataDome — connect to the user's real Chrome and the cookie does the work.
Detection
| Signal | Value |
|---|---|
| CDN | Fastly (x-served-by: cache-pao-...) |
| Framework | SSR HTML (no __NEXT_DATA__, no React shell) |
| Anti-bot | DataDome (server: DataDome, x-datadome: protected, x-dd-b: 2) |
| Auth | Not required for search |
| Structured | ld+json BreadcrumbList + FAQPage only — no ItemList |
| robots.txt | Disallows /search for most bots, but real users are fine |
curl -sL https://www.yelp.com/search?find_desc=pizza&find_loc=New+York%2C+NY → HTTP 403 with a geo.captcha-delivery.com iframe in the body.
Architecture
- Pure SSR. The full result list ships in the initial HTML — no XHR hydration.
- Each page returns 10 organic results plus ~13 ad cards (
[data-testid="serp-ia-card"]). - Pagination is
&start=10,&start=20, … (offset, not page number). - DataDome enforcement is per-session: the first navigation in a fresh browser context triggers a JS challenge, but a real Chrome with a persistent profile already has a valid
datadomecookie and skates through. Disposable Chromium with stealth is NOT enough — DataDome scores it as a bot.
Strategy used
- Phase 0 (curl): 403 DataDome → escalate.
- Phase 1 (framework): no Next/Nuxt blob, no API endpoint visible in source → escalate.
- Phase 2 (browser):
puppeteer.connect({ browserURL: "http://127.0.0.1:9222" })→ first nav clears DataDome automatically within ~1.5s, subsequent navs are instant. - Phase 3: parse with cheerio, walk leaf-text spans for neighborhood/status/snippet.
Stealth config that works
None. Don't use puppeteer-extra/stealth on the real-Chrome path — Yelp's profile cookie is the entire bypass. Just:
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 · 163 lines · 0 tokens per session scan A 493cad2260be
yelp is a skill published in the GitHub repository AgentComputerAI/torch (5 stars, last pushed 6mo ago), licensed MIT. It adds 125 tokens to every session and 2,391 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.
Other skills, from other repositories
chrome-extension
Use when building or shipping a Manifest V3 browser extension and hitting its quirks — service worker dying and losing state, permission warnings, a Chrome Web Store rejection, content-script/worker/popup messaging, or an MV2-to-V3 migration. NOT a generic web app (that is nextjs), NOT a desktop shell (that is…
data-scraper
Use when data lives on a website with no usable API — listings, prices, public records — and the scrape must stay legal and not get blocked: legal gate, extraction path, durable selectors, pacing, resilience. NOT parsing bytes you already hold into fields (that is structured-extraction), NOT a documented API or key…
nodejs
Use when building or operating a plain Node.js / Express 5 backend service: project layout, async correctness, central error middleware, fail-fast config, graceful shutdown on SIGTERM. NOT DI modules/providers/guards (that is nestjs), NOT the type system or tsconfig (that is typescript), NOT REST contract design (that…
checking-a-page
Check that a web page you wrote or changed actually works, by opening it in a browser and driving every control on it. Use after creating or editing an HTML page, or the JavaScript or CSS that a page loads.
browser-qa
Testing web apps through a real browser: reconnaissance before acting, selector discovery, state capture, console errors and screenshot evidence. Use on a web surface end to end, or to reproduce a front-end bug.
browser-automation
A browser-automation workflow that detects the terminal environment and chooses a browser control tool. It supports opening pages, taking snapshots, clicking, filling fields, and other checks.