Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Developer Tools
Daolv Hotel Booking
Hotel discovery, shortlist comparison, and booking handoff using the ai-go-hotel MCP server (getHotelSearchTags, searchHotels, getHotelDetail). Use when user...
skill openclawclawhub Free
Hotel discovery, shortlist comparison, and booking handoff using the ai-go-hotel MCP server (getHotelSearchTags, searchHotels, getHotelDetail). Use when user...
⬇ 0 downloads ★ 0 stars Unverified but indexed
Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/aigohotel-mcp-spec.md, references/distribution.md, references/mcp-client-config.json, references/promo-copy.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
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.
Upgrade existing
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.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 0.1.3
Provenance
- Publisher
- cnChenKai
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Daolv Hotel Booking
Provide reliable hotel planning and booking support with structured MCP calls and decision-ready outputs.
Workflow
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. 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. 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 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. 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
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
4 Docs1 Config
- SKILL.md
- references/aigohotel-mcp-spec.md
- references/distribution.md
- references/promo-copy.md
- references/mcp-client-config.json