doordash

A scraping guide for collecting deal listings from DoorDash’s public deal page. DoorDash is a food-delivery website, and its page loads deal items into the browser.

In plain words
What is it for?
Use it to collect deal names, prices, and related listing data from DoorDash’s deals page. It covers browser automation, scrolling for additional sections, and parsing the resulting HTML.
Why use it?
It helps deal with Cloudflare’s browser check and shows where the listings are already present after the page loads. It avoids relying on private or personalized data endpoints.

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

Made for: Claude Code, Codex.

Per session 82 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,977 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 $0.00082 $0.01977
Opus 5 $0.00041 $0.00988
Sonnet 5 $0.00016 $0.00395
Haiku 4.5 $0.00008 $0.00198

Measured 2d ago against content hash 95368a0c1474, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

doordash 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 2d 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.

| **CDN** | Cloudflare (`cf-ray`, `cf-mitigated`, "Just a moment..." on raw curl) |
skills/sites/doordash/SKILL.md · 201 lines

How it starts

The opening of the file, as written. The whole thing — 201 lines — stays where its author put it; the contents beside it link to each section on GitHub.

DoorDash (doordash.com)

React SPA served through Cloudflare. Deal pages are server-side rendered with all items inlined in the initial HTML — don't bother with the GraphQL endpoints. A headed stealth Puppeteer session clears the Cloudflare challenge automatically; no captcha solver or proxy needed.

Detection

Signal Value
CDN Cloudflare (cf-ray, cf-mitigated, "Just a moment..." on raw curl)
Framework React SPA with SSR bootstrap
Anti-bot Cloudflare Managed Challenge — clears via stealth plugin, no CAPTCHA
Rendering SSR for deals carousels; GraphQL for personalized/auth surfaces
Auth Not required for /browse/deals
Geo Results vary by geoIP — default US egress lands in SF 94107

Strategy

Puppeteer (stealth, headed)
  → wait for networkidle2
  → scroll to trigger lazy sections
  → parse rendered HTML with Cheerio

Do NOT hit the GraphQL endpoints:

  • /graphql/homeLandingPageStores, getGeoByIP, etc. fire on page load but none return the deals feed.
  • The typical facetFeed endpoint only fires on authenticated/personalized surfaces, not /browse/deals.
  • The deals feed is inlined in the SSR HTML — parse that directly.

Stealth config that works

import puppeteer from "puppeteer-extra";
import StealthPlugin from "puppeteer-extra-plugin-stealth";
puppeteer.use(StealthPlugin());

const browser = await puppeteer.launch({
  headless: false,
  args: [
    "--no-sandbox",
    "--disable-setuid-sandbox",
    "--disable-blink-features=AutomationControlled",
  ],
});

const page = await browser.newPage();
await page.goto("https://www.doordash.com/browse/deals", { waitUntil: "networkidle2" });

Standard Chrome UA is fine — no rotation needed. Cloudflare clears on its own once JS runs.

Verify you're past the challenge before parsing:

const title = await page.title();
if (title !== "Deals | Doordash") {
  throw new Error(`Unexpected page title: ${title} — Cloudflare may still be challenging`);
}

Read the full file on GitHub · 201 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. 2d ago First seen · 201 lines · 82 tokens per session scan A 95368a0c1474

Subscribe to this mod's changes

doordash is a skill published in the GitHub repository AgentComputerAI/torch (5 stars, last pushed 4mo ago), licensed MIT. It adds 82 tokens to every session and 1,977 once invoked, about $0.0004 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.

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