Daolv Hotel Search#

Focus on fast discovery and clean shortlist output.

Workflow#

1. Capture search intent

• Extract destination, check-in date, nights, guests, budget, star range, distance preference, amenities, brand preferences.
• Ask only minimal missing questions.

1. Prime tags once

• Call ai-go-hotel.getHotelSearchTags once per task.
• Map user intent into hotelTags.requiredTags / preferredTags / excludedTags.

1. Run hotel search

• Call ai-go-hotel.searchHotels with required fields:

  • originQuery, place, placeType

• Include optional fields when available:

  • checkInDate, stayNights, adultCount, countryCode, starRatings, distanceInMeter, size, hotelTags

• Prefer size=10 first, then narrow to top 3-5.

1. Return shortlist only

• Output: 1 recommended + 2 alternatives.
• Include quick trade-off: price / location / amenities / star.
• Do not deep-dive room plans unless user asks to proceed to booking.

Output Template#

• 搜索条件：地点 / 日期 / 人数 / 预算 / 偏好
• 首选酒店：价格区间、位置、标签命中、推荐理由
• 备选 1-2：同结构
• 下一步：是否进入“房型与退改细节”阶段

Quality Bar#

• Use concrete numbers when available.
• Use price.lowestPrice + price.currency (price is object).
• If price missing/null, mark as “需二次查价”.
• Keep output concise and decision-oriented.

MCP Preset Config#

• Embedded preset: references/mcp-client-config.json
• Endpoint: https://mcp.aigohotel.com/mcp ( streamable_http + prefilled Authorization header)