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  "item": {
    "slug": "daolv-hotel-booking",
    "name": "Daolv Hotel Booking",
    "source": "tencent",
    "type": "skill",
    "category": "开发工具",
    "sourceUrl": "https://clawhub.ai/cnChenKai/daolv-hotel-booking",
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      "references/promo-copy.md"
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          "label": "Upgrade existing",
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    "summary": "Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.",
    "steps": [
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      "Paste one of the prompts below and point your agent at the extracted folder."
    ],
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      {
        "label": "New install",
        "body": "I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete."
      },
      {
        "label": "Upgrade existing",
        "body": "I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run."
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  "documentation": {
    "source": "clawhub",
    "primaryDoc": "SKILL.md",
    "sections": [
      {
        "title": "Daolv Hotel Booking",
        "body": "Provide reliable hotel planning and booking support with structured MCP calls and decision-ready outputs."
      },
      {
        "title": "Workflow",
        "body": "Capture booking intent before calling tools\n\nExtract: destination, check-in date, nights, adults/children, room count, budget, purpose (business/family/leisure), required amenities, preferred/avoided brands.\nIf key constraints are missing, ask only the minimum follow-up questions.\n\nPrime tags once per task\n\nCall ai-go-hotel.getHotelSearchTags once.\nCache returned tags for the rest of the conversation.\nUse those tags to build hotelTags.requiredTags, preferredTags, excludedTags, and optional budget constraints.\n\nSearch hotels with normalized parameters\n\nCall ai-go-hotel.searchHotels with:\n\nplace\nplaceType\noriginQuery\noptional checkInDate, stayNights, adultCount, size, starRatings, hotelTags, countryCode, distanceInMeter, withHotelAmenities, language\n\n\nPrefer size=8-12 for first pass; narrow to top 3-5 in final output.\nRespect live schema behavior:\n\ncheckInDate invalid/past/empty may fallback to tomorrow\nprice is an object (use price.lowestPrice + price.currency)\nsome fields can be null or missing\n\n\nplaceType can be normalized from user language:\n\n城市/city → 城市\n机场/airport → 机场\n景点/attraction → 景点\n火车站/railway station → 火车站\n地铁站/metro → 地铁站\n酒店/hotel → 酒店\n\nEnrich finalists with room-level details\n\nFor each shortlisted option, call ai-go-hotel.getHotelDetail (prefer hotelId when available).\nPass dates with checkInDate / checkOutDate format YYYY-MM-DD.\nHandle fallback and edge behavior:\n\ninvalid/empty dates may auto-correct\nfailures may return plain text (not structured JSON)\nroomRatePlans can be very large; render only top rows by relevance/price\n\n\nExtract actionable room/price data, cancellation policy, breakfast inclusion, and important constraints.\n\nReturn decision-ready output\n\nAlways provide:\n\nRecommended option (best fit)\nTwo alternatives\nWhy each matches constraints\nTrade-offs (price vs distance vs amenities)\nBooking handoff steps (what user should confirm next)"
      },
      {
        "title": "Output Template",
        "body": "Use concise bullet format:\n\n行程信息: 目的地 / 日期 / 人数 / 预算 / 关键偏好\n推荐酒店（首选）\n\n酒店名\n预估价格（每晚 & 总价）\n位置与交通\n房型亮点\n取消与早餐政策\n推荐理由\n\n\n备选 1 / 备选 2（同结构）\n决策建议: 适合人群与风险提示\n下一步确认: 仅列 2-4 个必要确认项"
      },
      {
        "title": "Quality Bar",
        "body": "Prefer concrete numbers over vague wording.\nDo not invent unavailable policies/prices.\nIf data is missing or stale, say so explicitly and suggest a refresh query.\nKeep choices constrained: no long dump lists.\nAvoid credential exposure or config leakage."
      },
      {
        "title": "MCP Preset Config",
        "body": "Embedded MCP preset is included at:\n\nreferences/mcp-client-config.json\n\n\nIt targets https://mcp.aigohotel.com/mcp using streamable_http and prefilled Authorization header."
      },
      {
        "title": "Platform Distribution",
        "body": "When user asks to publish/distribute this skill, follow the checklist in:\n\nreferences/distribution.md\nreferences/promo-copy.md"
      }
    ],
    "body": "Daolv Hotel Booking\n\nProvide reliable hotel planning and booking support with structured MCP calls and decision-ready outputs.\n\nWorkflow\nCapture booking intent before calling tools\nExtract: destination, check-in date, nights, adults/children, room count, budget, purpose (business/family/leisure), required amenities, preferred/avoided brands.\nIf key constraints are missing, ask only the minimum follow-up questions.\nPrime tags once per task\nCall ai-go-hotel.getHotelSearchTags once.\nCache returned tags for the rest of the conversation.\nUse those tags to build hotelTags.requiredTags, preferredTags, excludedTags, and optional budget constraints.\nSearch hotels with normalized parameters\nCall ai-go-hotel.searchHotels with:\nplace\nplaceType\noriginQuery\noptional checkInDate, stayNights, adultCount, size, starRatings, hotelTags, countryCode, distanceInMeter, withHotelAmenities, language\nPrefer size=8-12 for first pass; narrow to top 3-5 in final output.\nRespect live schema behavior:\ncheckInDate invalid/past/empty may fallback to tomorrow\nprice is an object (use price.lowestPrice + price.currency)\nsome fields can be null or missing\nplaceType can be normalized from user language:\n城市/city → 城市\n机场/airport → 机场\n景点/attraction → 景点\n火车站/railway station → 火车站\n地铁站/metro → 地铁站\n酒店/hotel → 酒店\nEnrich finalists with room-level details\nFor each shortlisted option, call ai-go-hotel.getHotelDetail (prefer hotelId when available).\nPass dates with checkInDate / checkOutDate format YYYY-MM-DD.\nHandle fallback and edge behavior:\ninvalid/empty dates may auto-correct\nfailures may return plain text (not structured JSON)\nroomRatePlans can be very large; render only top rows by relevance/price\nExtract actionable room/price data, cancellation policy, breakfast inclusion, and important constraints.\nReturn decision-ready output\nAlways provide:\nRecommended option (best fit)\nTwo alternatives\nWhy each matches constraints\nTrade-offs (price vs distance vs amenities)\nBooking handoff steps (what user should confirm next)\nOutput Template\n\nUse concise bullet format:\n\n行程信息: 目的地 / 日期 / 人数 / 预算 / 关键偏好\n推荐酒店（首选）\n酒店名\n预估价格（每晚 & 总价）\n位置与交通\n房型亮点\n取消与早餐政策\n推荐理由\n备选 1 / 备选 2（同结构）\n决策建议: 适合人群与风险提示\n下一步确认: 仅列 2-4 个必要确认项\nQuality Bar\nPrefer concrete numbers over vague wording.\nDo not invent unavailable policies/prices.\nIf data is missing or stale, say so explicitly and suggest a refresh query.\nKeep choices constrained: no long dump lists.\nAvoid credential exposure or config leakage.\nMCP Preset Config\nEmbedded MCP preset is included at:\nreferences/mcp-client-config.json\nIt targets https://mcp.aigohotel.com/mcp using streamable_http and prefilled Authorization header.\nPlatform Distribution\n\nWhen user asks to publish/distribute this skill, follow the checklist in:\n\nreferences/distribution.md\nreferences/promo-copy.md"
  },
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    "sourceLabel": "tencent",
    "provenanceUrl": "https://clawhub.ai/cnChenKai/daolv-hotel-booking",
    "publisherUrl": "https://clawhub.ai/cnChenKai/daolv-hotel-booking",
    "owner": "cnChenKai",
    "version": "0.1.3",
    "license": null,
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