Companion reference skills. Load these for deeper context:

• hotel-chains — branded property to loyalty program mapping
• premium-hotels — FHR / THC / Chase Edit credits and stacking strategy
• points-valuations — CPP floor/ceiling for hotel programs (Hyatt 1.4-1.7cpp, Hilton 0.4cpp floor, etc.)
• fallback-and-resilience — recovery when a hotel source fails

Compare Hotels

Search every available source for accommodation and present one unified comparison. Combines portal premium programs (Chase Edit, Amex FHR/THC), cash pricing, and Airbnb alternatives into a single view.

This is an orchestration skill. It tells the agent which tools to run and how to combine results. No standalone script.

When to Use

• "Find me a hotel in Paris for Aug 11-15"
• "Should I book through Chase or Amex for this hotel?"
• "Compare hotels vs Airbnb in Oslo"
• Any accommodation search where the user wants the full picture

Sources

Run these in parallel where possible. Never fail silently.

Portal Premium Programs (Docker required)

| Source | Skill | Speed | What It Finds | |--------|-------|-------|---------------| | Chase Travel | chase-travel | ~45s | Edit hotels ($100 credit, breakfast, upgrade), Points Boost, standard hotels | | Amex Travel | amex-travel | ~45s | FHR ($100+ credit, breakfast, upgrade, late checkout), THC ($100 credit on 2+ nights) |

Cash Prices and Metasearch

| Source | Skill/Tool | Speed | What It Finds | |--------|------------|-------|---------------| | SerpAPI | serpapi | ~3s | Google Hotels cash prices and direct booking links. | | Trivago | web search | ~5s | Metasearch across many OTAs. Use tavily/exa to search trivago.com. Finds the absolute cheapest OTA rate. | | LiteAPI | web search | ~5s | Hotel API aggregator with negotiated rates. Check liteapi.travel. Can find rates below public OTA pricing. | | RapidAPI | rapidapi | ~3s | Booking.com inventory and pricing. Optional, use when user asks for Booking.com specifically. |

Quality and Ratings

| Source | Skill/Tool | Speed | What It Finds | |--------|------------|-------|---------------| | TripAdvisor | tripadvisor | ~2s | Ratings, rankings, subratings (location/service/cleanliness), reviews, photos, amenities, awards. 5K calls/month. |

SerpAPI, Trivago, and LiteAPI are all default. Always search all three. Only add RapidAPI if the user asks for Booking.com specifically. Use TripAdvisor for quality data (ratings, rankings, reviews) to complement pricing from other sources.

Vacation Rentals

| Source | Skill/Tool | Speed | What It Finds | |--------|------------|-------|---------------| | Airbnb | airbnb_search MCP tool | ~5s | Entire homes, private rooms, with total pricing | | VRBO | vrbo skill (Patchright) | ~20s | Whole homes, condos, cabins. Professionally-managed units often not on Airbnb. Headed/Docker — behind Akamai. |

Premium Property Databases (local, instant)

| Source | Data File | What It Finds | |--------|-----------|---------------| | FHR properties | data/fhr-properties.json | Check if a hotel is FHR before booking | | THC properties | data/thc-properties.json | Check if a hotel is THC | | Chase Edit properties | data/chase-edit-properties.json | Check if a hotel is in Chase's Edit program |

Workflow

Step 1: Search All Sources

PARALLEL GROUP 1 (fast — HTTP/API/MCP calls, no browser, ~3-5s):
  - SerpAPI: Google Hotels cash prices
  - Trivago: metasearch across OTAs (web search)
  - LiteAPI: negotiated hotel rates (web search)
  - Airbnb: vacation rentals in the area (npx MCP — lightweight scrape, not a browser)
  - Local data: check premium-hotels databases for the city

PARALLEL GROUP 2 (slow — headed browser via Patchright/Xvfb in Docker, ~20-45s):
  - VRBO: whole homes / condos / cabins — vrbo skill (~20s, headed/Docker, behind Akamai; run for whole-home comparisons alongside Airbnb)
  - Chase Travel: --hotel --dest "City" --checkin YYYY-MM-DD --checkout YYYY-MM-DD --json
  - Amex Travel: --hotel --dest "City" --checkin YYYY-MM-DD --checkout YYYY-MM-DD --json

For each source, capture:

• Source name
• Status: "ok" | "error: {reason}" | "skipped: {reason}"
• Results count
• Data

Step 2: Identify Stacking Opportunities

Cross-reference results with data/fhr-properties.json, data/thc-properties.json, and data/chase-edit-properties.json:

For each hotel in results:
  - Is it in FHR? → Tag [FHR]
  - Is it in THC? → Tag [THC]
  - Is it in Chase Edit? → Tag [EDIT]
  - Is it in multiple? → Tag [FHR+EDIT] and note stacking potential

Stacking means: book through one portal, pay with the other card separately. For example, book FHR through Amex (get breakfast + credit + upgrade), then use CSR $300 travel credit on something else at the property.

Step 3: Calculate Points Value

Chase:

• Chase portal pricing on CSR/CSP is dynamic Points Boost. Each booking quotes a specific points price; effective cpp typically falls in the 1.5-2.0 cpp range on CSR but is not a guaranteed floor on every booking. Pull the actual portal quote.
• Points Boost offers are dynamic and vary by route/date/inventory.
• The portal quote IS the actual UR cost. Don't divide by 1.5 — the listed points already reflect the dynamic Boost rate at quote time.

Amex:

• Hotel portal pricing is variable (NOT always 1 cpp like flights).
• The points price shown is the actual MR cost. Calculate CPP from cash/points ratio.
• FHR benefits ($100+ credit, breakfast) offset the rate significantly.

Calculate benefit-adjusted price:

FHR adjusted = total_price - $100 credit - (breakfast_value × nights)
  breakfast_value ≈ $30-50/person × 2 people = $60-100/night
THC adjusted = total_price - $100 credit (2+ night stays only)
Edit adjusted = total_price - $100 credit - (breakfast_value × nights)

Step 4: Present Unified Table

Always use markdown tables. Hotels sorted by benefit-adjusted total price.

Example: Paris, Aug 11-15 (4 nights, 2 guests)

| # | Hotel | Program | Stars | Per Night | Total | Points | Benefits | Adj Total | |---|-------|---------|-------|-----------|-------|--------|----------|-----------| | 1 | SO/ Paris | EDIT+BOOST | 5★ | $639 | $2,555 | 127,756 UR | Breakfast, $100 credit, upgrade | ~$1,855 | | 2 | Hotel Balzac | EDIT+BOOST | 5★ | $614 | $2,455 | 122,769 UR | Breakfast, $100 credit, upgrade | ~$1,755 | | 3 | Le Bristol | FHR | 5★ | $1,849 | $8,284 | n/a | $100 credit, breakfast, upgrade, 4pm checkout | ~$6,884 | | 4 | Marriott Champs-Élysées | — | 4★ | $289 | $1,156 | — | — | $1,156 | | 5 | Airbnb: Marais 2BR | — | — | $195 | $780 | — | Kitchen, washing machine | $780 |

Sources checked:

• ✅ Chase Travel: 21 hotels (15 Edit, 6 standard)
• ✅ Amex Travel: 17 hotels (13 FHR, 4 THC)
• ✅ SerpAPI: 25 hotels
• ✅ Trivago: 30 hotels (cheapest OTA per hotel)
• ✅ LiteAPI: 22 hotels (negotiated rates)
• ✅ Airbnb: 18 listings
• ✅ Premium databases: 8 FHR, 3 THC, 15 Edit properties in Paris
• ⏭️ RapidAPI/Booking.com: skipped (not requested)

Step 5: Recommendation

After the table, always provide:

1. Best luxury value: Which premium hotel gives the most benefit-adjusted savings
2. Best budget option: Cheapest option (often Airbnb for longer stays)
3. Stacking opportunities: Hotels in both FHR/THC AND Chase Edit
4. Credit usage: Which card credits apply ($600 Amex FHR, $300 CSR travel, $250 Select Hotels)
5. Points vs cash: Is using points worthwhile for any of these? (Calculate CPP)
6. Direct booking comparison: Note if direct booking is significantly cheaper than portal price

Airbnb Integration

Use the airbnb_search MCP tool:

airbnb_search(
  location="Paris, France",
  checkin="2026-08-11",
  checkout="2026-08-15",
  adults=2,
  propertyType="entire_home"
)

For each Airbnb result, extract:

• Name, price, rating, reviews
• Property type (entire home, private room)
• Key amenities (kitchen, washer, wifi, AC)
• Direct link to listing

When Airbnb makes sense:

• Stays of 5+ nights (usually cheaper per night)
• Groups or families needing space
• Destinations where hotels are overpriced
• When kitchen access matters (dietary restrictions, saving on meals)

When hotels win:

• Short stays (1-2 nights)
• Premium benefits offset the rate (FHR breakfast alone can be $100+/night value)
• Points redemption gives good CPP
• Loyalty status benefits (upgrades, late checkout, lounge access)

Error Handling

NEVER fail silently. Every source must report its status.

- ❌ Chase Travel: Login failed. No Chase portal pricing available.
- ❌ Airbnb: No results for this location/dates.
- ⚠️ Amex Travel: Only 3 results (some hotels may not be available for these dates).

If premium databases show FHR/Edit properties in the city but the portal search didn't return them, note this: "The FHR database lists 8 properties in Paris but Amex Travel only returned 3. Some may not have availability for your dates."

Data Files Used

| File | Purpose | |------|---------| | data/fhr-properties.json | FHR property lookup by city/coordinates | | data/thc-properties.json | THC property lookup | | data/chase-edit-properties.json | Chase Edit property lookup | | data/hotel-chains.json | Hotel chain to loyalty program mapping | | data/points-valuations.json | CPP valuations for points calculations |

Limitations

• Portal searches require Docker and credentials. Skip if not configured.
• Airbnb MCP must be available. Skip gracefully if not.
• FHR/THC/Edit databases are updated periodically. Properties may have been added or removed.
• Amex hotel points pricing is variable (not 1 cpp). Use the actual points price from the portal.
• Chase portal pricing is dynamic Points Boost (~1.5-2.0 cpp on select bookings, not a guaranteed floor). The historical static 1.5x multiplier is gone.
• Direct booking prices (via SerpAPI) may differ from portal prices for the same hotel.