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hotel-lookup酒店查询

Agent Skill

hotel-lookup 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,109

周安装

127

GitHub Stars

1

下载量

996
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:hotel-lookup(酒店查询)
来源仓库:https://github.com/zuckonit/hotel-lookup
安装命令:
openclaw skills install hotel-lookup
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install hotel-lookup

简介

hotel-lookup 用于在 Fliggy MCP 上发现酒店并支持比较与预订交接。

  • 通过 FlyAI search-hotel 接口实现结构化过滤,如目的地、日期等。
  • 适用于快速筛选符合条件的住宿选项并生成推荐列表。
  • 安装命令为 openclaw skills install hotel-lookup,适用于 OpenClaw 宿主。
  • 使用前需确认接口可用性和数据准确性,避免依赖失效源。

SKILL.md

name
hotel-lookup
display_name
Hotel Lookup — FlyAI search-hotel · Fliggy MCP
description
>
homepage
https://open.fly.ai/
metadata
version
1.2.0
agent
type
tool
runtime
node
context_isolation
execution
parent_context_access
read-only
openclaw
emoji
\F3E8
priority
88
requires
bins
intents
patterns

Hotel Lookup (FlyAI · Fliggy MCP)

Provide hotel discovery, comparison, and booking handoff using the FlyAI CLI command search-hotel, backed by Fliggy MCP. Outputs are decision-ready when you respect live JSON fields and the flag schema in references/search-hotel.md (single source of truth).


Prerequisites

  1. Install FlyAI CLI: npm i -g @fly-ai/flyai-cli
  2. Optional richer results: flyai config set FLYAI_API_KEY "your-key" (keep secrets out of logs).
  3. I/O: one JSON object per line on stdout; guidance/errors on stderr (flyai search-hotel --help for flag discovery).

Workflow

1. Capture intent before running search-hotel

Extract and confirm (ask only the minimum if missing):

  • Destination → maps to required --dest-name (country / province / city / district).
  • Stay window--check-in-date / --check-out-date (YYYY-MM-DD).
  • Budget--max-price (CNY per night cap).
  • Stars & beds--hotel-stars, --hotel-bed-types.
  • Lodging mix--hotel-types (酒店 / 民宿 / 客栈).
  • Landmark / “near X”--poi-name plus --dest-name.
  • Free-text narrowing--key-words.
  • Ranking preference--sort (price_asc / price_desc / rate_desc / distance_asc / no_rank).
  • Trip purpose (business / family / leisure) → use to choose filters and how you explain trade-offs; do not send fields that references/search-hotel.md does not define.

2. Align parameters to the reference (no “tag priming” RPC)

  • Open references/search-hotel.md and mirror exact flag names—there is no separate “prime tags” or tag-cache step in search-hotel.
  • Validate dates (not in the past; correct format). If the city or district is ambiguous, ask the user—never guess --dest-name.

3. Search hotels with normalized flyai search-hotel flags

  • Build one invocation: flyai search-hotel … per the reference Examples and parameter list.
  • Prefer a bounded result set for first pass (e.g. sensible defaults from user intent); shortlist to top 3–5 in the final narrative.
  • Respect live JSON behavior from upstream:

- Some fields may be null or missing. - Price in samples appears as display strings (e.g. ¥618); do not invent currency rules not present in data. - If the service returns errors or empty itemList, follow Error handling below.

4. Enrich finalists from returned JSON only (no extra hotel-detail RPC)

  • Each finalist row comes from data.itemList (see output example in references/search-hotel.md).
  • Use mainPic, detailUrl, name, address, price, score, star, review, interestsPoi, etc. when present.
  • There is no getHotelDetail call in this skill. Deeper room-level matrices like full rate-plan grids are only available if they appear inside the JSON you already received; otherwise direct the user to detailUrl for authoritative booking pages.
  • If you need a second pass, run a narrower search-hotel (tighter dates, POI, or keywords)—do not fabricate APIs.

5. Return decision-ready output

Always give:

  • Recommended pick (best fit to stated constraints).
  • Two alternatives with honest trade-offs (price vs distance vs stars vs POI proximity—only from observed fields).
  • Booking handoff: what to open next (detailUrl), what to double-check on the supplier page, and 2–4 final confirmation questions if anything is still ambiguous.

Output template (concise bullets)

  • 行程信息: 目的地 / 入住离店 / 人数或房型需求 / 预算(每晚 CNY)/ 关键偏好(商务/亲子等)
  • 推荐酒店(首选)

- 酒店名 · 价格展示(来自 JSON) - 位置 / 交通或 POI 相关字段(如 interestsPoi) - 图片行:![]({mainPic})(若存在) - 详情/预订:[Click to book]({detailUrl})(若存在) - 评分/星级/短评(若存在) - 推荐理由(只引用结果中可见事实)

  • 备选 1 / 备选 2(同结构,字段缺失则说明)
  • 决策建议: 适合人群与取舍(不编造政策)
  • 下一步确认: 仅列 2–4 个必要确认项(支付前核对官方页等)

Output & presentation (Markdown)

  • Show image before booking link when both exist.
  • Use headings and tables when comparing multiple hotels.
  • Optional brand line: e.g. “Based on fly.ai real-time hotel results.”

Quality bar

  • Prefer concrete numbers and fields from JSON over vague adjectives.
  • Do not invent cancellation rules, breakfast, or prices not shown in data.
  • If data is missing, stale, or mismatched to user intent, say so and suggest adjusting flags or confirming on detailUrl.
  • Keep shortlists tight—avoid dumping huge itemList tables unchanged.
  • Never expose API keys or local config in chat.

References

SurfaceLocation
search-hotel flags, examples, output shapereferences/search-hotel.md (authoritative)

Error handling

  1. Validate inputs against references/search-hotel.md; ask the user when required fields are unclear.
  2. Diagnose stderr + JSON status / message; fix flags vs retry on transient errors only.
  3. Empty results — relax filters once, then explain; no infinite retries.
  4. Transparency — if location or dates may be wrong, state it before recommending payment.

Differentiation (honest scope)

HookMeaning (search-hotel only)
POI + destination--poi-name + --dest-name for “near landmark” stays.
三态住宿--hotel-types: 酒店 / 民宿 / 客栈 in one run.
CNY nightly cap--max-price for per-night budget ceilings.
Agent-first JSONmainPic + detailUrl for fast Markdown cards—no extra scraper stack in this bundle.

适合场景

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OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

需要对比不同来源的安装命令和来源信息时

能力概览

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能力 2

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能力 3

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能力 4

补充不同宿主或平台的使用分布数据

能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

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external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

安装前确认

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