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OpenClaw

daolv-hotel-search

Hotel search and shortlist comparison using the ai-go-hotel MCP server (getHotelSearchTags, searchHotels). Use when users need fast hotel discovery by city/POI/date/budget/amenities/brand, but do not yet need full booking-room confirmation.

cnchenkai0 source installs☆ 0 Repository stars

Installation

Follow the repository instructions for this skill and your agent. Review the files and dependencies before adding it to your workflow.

SkillHub CLI

skillhub install cnchenkai/daolv-hotel-search

Inspect the source and compatibility requirements, then follow its installation steps.

Give your agent the source link and ask it to inspect instructions and dependencies before explaining the installation steps.

View source ↗Guides

Skill instructions

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)

Source information

Source
github
Repository
openclaw/skills
Path
skills/cnchenkai/daolv-hotel-search
Version
—
Commit
c8f19dadf96de0ad7389446c99fb704b1ee53c4a
Classification source
rules
Status
active
Visibility
public

These signals come from indexed source analysis and may lag behind changes. Check the current source files.

Extracted content

SKILL.md
# 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.

2. Prime tags once
- Call `ai-go-hotel.getHotelSearchTags` once per task.
- Map user intent into `hotelTags.requiredTags` / `preferredTags` / `excludedTags`.

3. 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.

4. 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)

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