Daolv Hotel Booking

Hotel discovery, shortlist comparison, and booking handoff using the ai-go-hotel MCP server (getHotelSearchTags, searchHotels, getHotelDetail). Use when user...

Provide reliable hotel planning and booking support with structured MCP calls and decision-ready outputs.

Workflow

1. Capture booking intent before calling tools

• Extract: destination, check-in date, nights, adults/children, room count, budget, purpose (business/family/leisure), required amenities, preferred/avoided brands.
• If key constraints are missing, ask only the minimum follow-up questions.

2. Prime tags once per task

• Call ai-go-hotel.getHotelSearchTags once.
• Cache returned tags for the rest of the conversation.
• Use those tags to build hotelTags.requiredTags, preferredTags, excludedTags, and optional budget constraints.

3. Search hotels with normalized parameters

• Call ai-go-hotel.searchHotels with:
  • place
  • placeType
  • originQuery
  • optional checkInDate, stayNights, adultCount, size, starRatings, hotelTags, countryCode, distanceInMeter, withHotelAmenities, language
• Prefer size=8-12 for first pass; narrow to top 3-5 in final output.
• Respect live schema behavior:
  • checkInDate invalid/past/empty may fallback to tomorrow
  • price is an object (use price.lowestPrice + price.currency)
  • some fields can be null or missing
• placeType can be normalized from user language:
  • 城市/city → 城市
  • 机场/airport → 机场
  • 景点/attraction → 景点
  • 火车站/railway station → 火车站
  • 地铁站/metro → 地铁站
  • 酒店/hotel → 酒店

4. Enrich finalists with room-level details

• For each shortlisted option, call ai-go-hotel.getHotelDetail (prefer hotelId when available).
• Pass dates with checkInDate / checkOutDate format YYYY-MM-DD.
• Handle fallback and edge behavior:
  • invalid/empty dates may auto-correct
  • failures may return plain text (not structured JSON)
  • roomRatePlans can be very large; render only top rows by relevance/price
• Extract actionable room/price data, cancellation policy, breakfast inclusion, and important constraints.

5. Return decision-ready output

• Always provide:
  • Recommended option (best fit)
  • Two alternatives
  • Why each matches constraints
  • Trade-offs (price vs distance vs amenities)
  • Booking handoff steps (what user should confirm next)

Output Template

Use concise bullet format:

• 行程信息: 目的地 / 日期 / 人数 / 预算 / 关键偏好
• 推荐酒店（首选）
  • 酒店名
  • 预估价格（每晚 & 总价）
  • 位置与交通
  • 房型亮点
  • 取消与早餐政策
  • 推荐理由
• 备选 1 / 备选 2（同结构）
• 决策建议: 适合人群与风险提示
• 下一步确认: 仅列 2-4 个必要确认项

Quality Bar

• Prefer concrete numbers over vague wording.
• Do not invent unavailable policies/prices.
• If data is missing or stale, say so explicitly and suggest a refresh query.
• Keep choices constrained: no long dump lists.
• Avoid credential exposure or config leakage.

MCP Preset Config

• Embedded MCP preset is included at:
  • references/mcp-client-config.json
• It targets https://mcp.aigohotel.com/mcp using streamable_http and prefilled Authorization header.

Platform Distribution

When user asks to publish/distribute this skill, follow the checklist in:

• references/distribution.md
• references/promo-copy.md