pricewin-deal-finder

name: pricewin-deal-finder description: "Find the cheapest hotel deal by comparing live prices across Booking.com, Agoda, Google Hotels, and OpenTravel for any city worldwide and any travel dates — one command returns ranked best-value, cheapest, and quality picks with direct booking links, all normalized to USD. Use whenever someone asks for hotel prices, hotel deals, the cheapest room or rate, best hotel rates, a hotel price comparison, or which OTA is cheaper — e.g. 'is Booking or Agoda cheaper for Tokyo', 'find me a hotel in Bangkok under $100', 'compare hotel prices for 12–15 Aug', 'cheapest hotel near Shinjuku'." version: 0.8.4 author: PriceWin platforms: [linux, macos, windows] tags: [hotel-price-comparison, compare-hotel-prices, cheapest-hotel, cheapest-hotels, hotel-deals, booking-vs-agoda, best-hotel-rates, best-rates, hotel-search, hotel-booking, price-comparison, booking-com, agoda, google-hotels, opentravel, ota, hotel, hotels, travel, travel-deals, trip-planning, accommodation, deals] metadata: openclaw: requires: bins: [node, npx] envVars: - name: OPENTRAVEL_API_BASE_URL required: false description: Override the OpenTravel API host (default https://api.opentravel.one). emoji: "🏨" homepage: https://github.com/Price-Win/pricewin-skills-hub

PriceWin Deal Finder

Compare live hotel prices across Booking.com, Agoda, Google Hotels & OpenTravel in one command — and get back ranked best-value, cheapest, and quality picks with direct booking links.

Stop opening five OTA tabs to find the real cheapest rate. Ask your agent "find me a hotel in Tokyo for 12–15 Aug, 2 guests" and this skill returns a clean, ranked comparison in ~30–60 seconds (cached cities).

Invoke this skill for questions like:

• "What's the cheapest hotel in <city> for <dates>?"
• "Is Booking.com or Agoda cheaper for this hotel?"
• "Compare hotel prices for <city>, <N> guests."
• "Find me a hotel under $<X>/night in <city>."
• "Best-value place to stay near <landmark> on <dates>?"

Each returns the same one-command answer below — no clarifying round-trip needed.

What you get from one command:

• 🥇 Best value · 🥈 Cheapest · 🥉 Quality — picked side-by-side
• Real per-night prices from up to 4 sources, normalized to USD
• Clickable booking links straight to the cheapest OTA for each hotel
• Works for any city worldwide — including bot-hardened ones (Shanghai, Hangzhou, Bangkok…) via a stealth Patchright daemon
• No API keys, no MCP server — node/npx is all you need

Sample result:

🏨 Tokyo • Aug 12–15 • 3 nights • 2 guests
━━━━━━━━━━━━━━━━━━━━
🥇 BEST VALUE
Shinjuku Granbell Hotel
  ✅ agoda      💰 $118/night
     booking    💰 $131/night
     → Save $13 vs Booking
🥈 CHEAPEST
APA Hotel Shinjuku
  ✅ google     💰 $94/night
📊 18 hotels | agoda, booking, google, opentravel • prices in USD

Install:

npx skills add https://github.com/Price-Win/pricewin-skills-hub --skill pricewin-deal-finder

🚨 IMPORTANT — HOW TO USE THIS SKILL

ONE command does everything. Run this as your FIRST action — no clarifying questions first:

cd {baseDir} && node bin/search.js "<city>" <checkInYYYY-MM-DD> <checkOutYYYY-MM-DD> <adults> en-us

{baseDir} is this skill's install directory (auto-resolved by the runtime). If your runtime does not substitute it, cd into the folder that contains this SKILL.md (the one with bin/search.js). Do NOT hardcode a ~/.hermes/... or ~/.openclaw/... path — it differs per platform.

Example:

cd {baseDir} && node bin/search.js "Hangzhou" 2026-06-10 2026-06-13 2 en-us

The script handles everything automatically: daemon launch, Agoda cache lookup, Google + Booking inline search, OpenTravel API lookup (all cities), discovery for new cities, and formatted tier-card output. Just run it and send the output to the user.

DO NOT ask clarifying questions first. Just run the command. Infer all parameters:

• Year: use the current year from today's date unless the user states otherwise. If the requested day/month has already passed this year, assume next year. (Get today's date with date +%Y-%m-%d if unsure.)
• "10-13/6" → <year>-06-10 <year>-06-13 — fill <year> from the rule above
• "2 guests" / "2 people" → 2 adults
• Locale: language/region code passed to the OTAs (controls site language + region). Default en-us. Prices are in USD (Google Hotels is requested with gl=us&curr=USD); other sources follow the locale you pass.

DO NOT use any other approach. No Python scripts, no curl, no browser tools, no subagents. This one command is all you need.

🚨 CRITICAL RULES — FOLLOW EVERY TIME

RULE 0 — FORBIDDEN TOOLS. Read this twice. This skill drives a long-running Patchright daemon via the terminal tool ONLY. Your runtime exposes several other tools that LOOK convenient but are STRICTLY FORBIDDEN inside this skill:

❌ browser_navigate / browser_open — FORBIDDEN ❌ browser_click — FORBIDDEN ❌ browser_type / browser_fill — FORBIDDEN ❌ browser_snapshot — FORBIDDEN ❌ browser_close — FORBIDDEN ❌ Any other browser_* native tool — FORBIDDEN ❌ delegate_task / spawn_agent / sub-agent delegation — FORBIDDEN

Why: those native tools spawn a vanilla Chromium without stealth, so Booking.com and Agoda detect the bot within seconds and the requests just hang until the runtime kills them with "Command timed out after 30/60 seconds". You will burn 5+ minutes on timeouts and the user will get nothing. The Patchright daemon launched via terminal survives bot-detection.

Delegated subagents start with empty history and no skill context — they will always fall back to Python/curl scraping, which gets bot-blocked immediately. This skill must run entirely in the current agent, using only the terminal tool.

✅ The ONLY allowed way to drive a browser in this skill is via terminal:

terminal: cd {baseDir} && node bin/search.js ...

RULE 1 — search.js handles everything. NEVER scrape an OTA yourself. Do not manually call browse.js commands, do not goto/click/type in the browser, do not build Agoda/Booking/Google URLs by hand, do not call the OpenTravel API separately, do not try to launch the daemon yourself. search.js already drives the stealth daemon through a careful flow that survives bot-detection — it handles Agoda discovery internally for EVERY city (including Chinese cities like Shanghai, Hangzhou, etc.). Manually navigating an OTA is the #1 cause of failure: it trips Agoda/Booking anti-bot ("detect automation", "redirect to homepage", "problem completing your search") and gets the IP blocked. Your ONLY job is to run search.js once and send its output. If you think a source is "missing", re-read RULE 4 — do NOT go fetch it by hand.

RULE 2 — First-time city discovery takes 2–4 minutes. If search.js output contains "discovering" or "launching" messages, tell the user: "First time searching this city — discovering selectors, this takes about 2–4 minutes..." and wait for the result. Do NOT retry or abort.

RULE 3 — Send the output exactly. search.js outputs formatted tier cards ready to send. Copy the output directly into your response. Do not reformat, summarize, or abbreviate it.

RULE 3a — PRESERVE MARKDOWN HYPERLINKS. Every hotel name in the output is already wrapped as [Hotel Name](https://booking-url...). This is a clickable hyperlink — DO NOT:

• Strip the markdown and show the URL on a separate 🔗 https://... line
• Replace [Hotel Name](url) with plain text
• Capitalize OTA names ("google" stays "google", not "Google")
• Rename sections — "📋 More good deals" stays exactly

The output is Telegram-MarkdownV2-ready. Sending it as-is gives the user clickable hotel names with hidden URLs (clean UI).

RULE 3b — If you DO add a suggestion / commentary section after the output, every hotel name you mention MUST also be a markdown hyperlink [Hotel Name](url) using the SAME URL the script printed for that hotel. Never write a hotel name as plain text in your own commentary.

RULE 4 — Partial results are NORMAL and acceptable. Never "fix" them by hand. A source can be absent from the output (e.g. Agoda blocked this run, or OpenTravel has no inventory for the city). That is FINE — send the tier cards with whatever sources are present. The footer (📊 N hotels | <sources> • prices in USD) lists exactly what was found. Do NOT try to fetch the missing source via the browser, a direct URL, or any other tool — that triggers anti-bot and makes things worse. If search.js errors out entirely, tell the user what failed in 1 line and show any partial output it printed above the error. If you want more coverage, the only valid retry is running the SAME search.js command again (anti-bot is often transient).

Output Format Reference

search.js prints tier cards in this format — you send this directly to the user:

The hotel name is a Markdown link to its cheapest OTA. Price rows carry NO links and the OTA key is shown lowercase (agoda/booking/google/opentravel). There are no star ratings or area lines — the script does not have that data.

🏨 <city> • <d1>–<d2> • <N> nights • <adults> guests
━━━━━━━━━━━━━━━━━━━━

🥇 BEST VALUE
[<Hotel Name>](<cheapest_link>)
  ✅ agoda      💰 <price>/night
     booking    💰 <price>/night
     opentravel 💰 <price>/night
     → Save <diff> vs Booking

🥈 CHEAPEST
[<Hotel Name>](<cheapest_link>)
  ✅ google     💰 <price>/night
     agoda      💰 <price>/night

🥉 QUALITY
[<Hotel Name>](<cheapest_link>)
  ✅ booking    💰 <price>/night
     agoda      💰 <price>/night

📋 More good deals
  — Agoda —
  • [<Hotel>](<agoda_link>) — agoda: <price> | booking: <price>
  — Booking —
  • [<Hotel>](<booking_link>) — booking: <price>
  — Google —
  • [<Hotel>](<google_link>) — google: <price>
  — OpenTravel —
  • [<Hotel>](<opentravel_link>) — opentravel: <price>

💡 Tip: <best Hotel Name>
   [Book on <OTA>](<link>) — <price>/night

📊 <N> hotels | <sources with data> • prices in USD

All prices are shown in USD. Agoda, Google and OpenTravel geo-lock to VND by IP and are converted via a live FX rate; Booking returns USD natively. Only sources that actually returned data are listed in the footer.

Limitations

• First search per city pays the Agoda discovery cost (2–4 minutes). Google and Booking are inline (no discovery); OpenTravel is a direct API call.
• Subsequent searches reuse the Agoda cache and complete in ~30–60 seconds.