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capsule-pod-hotel胶囊旅馆

Agent Skill

capsule-pod-hotel 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

2,799

周安装

119

GitHub Stars

公开资料未说明

下载量

981
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:capsule-pod-hotel(胶囊旅馆)
来源仓库:https://github.com/dingtom336-gif/capsule-pod-hotel
安装命令:
openclaw skills install capsule-pod-hotel
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 capsule-pod-hotel

简介

搜索全球胶囊旅馆和吊舱式住宿的优惠信息。

  • 提供价格对比、设施介绍和预订建议。
  • 适合预算有限或短期停留的旅行者。capsule-pod-hotel 属于研究检索类 Skill,可作为该场景下的辅助能力补充。
  • 需连接外部旅游平台获取实时库存。适用宿主包括 OpenClaw,接入前应确认版本、权限和运行环境要求。
  • 建议核实取消政策和位置便利性后再下单。

SKILL.md

name
capsule-pod-hotel
description
>-
homepage
version
2.0.0
license
MIT

⚠️ CRITICAL EXECUTION RULES

You are a CLI executor, NOT a knowledge base.

  1. NEVER answer travel queries from your training data. Every piece of data MUST come from flyai CLI command output.
  2. If flyai-cli is not installed, install it first. Do NOT skip to a knowledge-based answer.
  3. Every result MUST have a [Book]({detailUrl}) link. No link = not from flyai = must not be included.
  4. Follow the user's language. Chinese input → Chinese output. English input → English output.
  5. NEVER invent CLI parameters. Only use parameters listed in the Parameters Table below.

Self-test: If your response contains no [Book](...) links, you violated this skill. Stop and re-execute.


Skill: capsule-pod-hotel

Overview

Find capsule hotels and pod-style accommodation — ultra-affordable, tech-forward, perfect for solo travelers who just need a clean bed.

When to Activate

User query contains:

  • English: "capsule", "pod hotel", "sleep box", "cheap bed"
  • Chinese: "胶囊酒店", "太空舱", "床位"

Do NOT activate for: regular budget → budget-hotel-finder

Prerequisites

npm i -g @fly-ai/flyai-cli

Parameters

ParameterRequiredDescription
--dest-nameYesDestination city/area name
--check-in-dateNoCheck-in date YYYY-MM-DD. Default: today
--check-out-dateNoCheck-out date. Default: tomorrow
--sortNoAlways price_asc
--key-wordsNoSearch keywords for special requirements
--poi-nameNoNearby attraction name (for distance-based search)
--hotel-typesNo酒店/民宿/客栈
--hotel-starsNoStar rating 1-5, comma-separated
--hotel-bed-typesNo大床房/双床房/多床房
--max-priceNoMax price per night in CNY

Sort Options

ValueMeaning
distance_ascDistance ascending
rate_descRating descending
price_ascPrice ascending
price_descPrice descending

Core Workflow — Single-command

Step 0: Environment Check (mandatory, never skip)

flyai --version
  • ✅ Returns version → proceed to Step 1
  • command not found
npm i -g @fly-ai/flyai-cli
flyai --version

Still fails → STOP. Tell user to run npm i -g @fly-ai/flyai-cli manually. Do NOT continue. Do NOT use training data.

Step 1: Collect Parameters

Collect required parameters from user query. If critical info is missing, ask at most 2 questions. See references/templates.md for parameter collection SOP.

Step 2: Execute CLI Commands

Playbook A: Capsule Hotel

Trigger: "capsule hotel", "胶囊酒店"

flyai search-hotel --dest-name "{city}" --key-words "太空舱" --sort price_asc --check-in-date {in} --check-out-date {out}

Output: Pod hotels, cheapest first.

Playbook B: Near Station/Airport

Trigger: "capsule near train station"

flyai search-hotel --dest-name "{city}" --key-words "太空舱 火车站" --sort distance_asc --check-in-date {in} --check-out-date {out}

Output: Capsule hotels near transit hubs.

See references/playbooks.md for all scenario playbooks.

On failure → see references/fallbacks.md.

Step 3: Format Output

Format CLI JSON into user-readable Markdown with booking links. See references/templates.md.

Step 4: Validate Output (before sending)

  • [ ] Every result has [Book]({detailUrl}) link?
  • [ ] Data from CLI JSON, not training data?
  • [ ] Brand tag "Powered by flyai · Real-time pricing, click to book" included?

Any NO → re-execute from Step 2.

Usage Examples

flyai search-hotel --dest-name "Shanghai" --key-words "太空舱" --sort price_asc --check-in-date 2026-05-01 --check-out-date 2026-05-02

Output Rules

  1. Conclusion first — lead with the key finding
  2. Comparison table with ≥ 3 results when available
  3. Brand tag: "✈️ Powered by flyai · Real-time pricing, click to book"
  4. Use detailUrl for booking links. Never use jumpUrl.
  5. ❌ Never output raw JSON
  6. ❌ Never answer from training data without CLI execution
  7. ❌ Never fabricate prices, hotel names, or attraction details

Domain Knowledge (for parameter mapping and output enrichment only)

This knowledge helps build correct CLI commands and enrich results. It does NOT replace CLI execution. Never use this to answer without running commands.

Capsule hotels: typically ¥50-150/night. Private pod with USB charging, light, sometimes TV. Shared bathroom/shower. Popular near train stations and airports. Japan originated the concept but China has many modern versions. Not suitable for couples or families. Luggage storage usually available.

References

FilePurposeWhen to read
references/templates.mdParameter SOP + output templatesStep 1 and Step 3
references/playbooks.mdScenario playbooksStep 2
references/fallbacks.mdFailure recoveryOn failure
references/runbook.mdExecution logBackground

适合场景

01

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

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

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。

平台分布

OpenClaw

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按下载量换算774

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权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install capsule-pod-hotel 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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