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Capsule Pod Hotel

作者 dingtom336-gif · GitHub ↗ · v1.0.0 · MIT-0
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在 OpenClaw 中安装
/install capsule-pod-hotel
功能描述
Find capsule hotels and pod-style accommodation — ultra-affordable, tech-forward, perfect for solo travelers who just need a clean bed. Also supports: flight...
使用说明 (SKILL.md)

⚠️ 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

Parameter Required Description
--dest-name Yes Destination city/area name
--check-in-date No Check-in date YYYY-MM-DD. Default: today
--check-out-date No Check-out date. Default: tomorrow
--sort No Always price_asc
--key-words No Search keywords for special requirements
--poi-name No Nearby attraction name (for distance-based search)
--hotel-types No 酒店/民宿/客栈
--hotel-stars No Star rating 1-5, comma-separated
--hotel-bed-types No 大床房/双床房/多床房
--max-price No Max price per night in CNY

Sort Options

Value Meaning
distance_asc Distance ascending
rate_desc Rating descending
price_asc Price ascending
price_desc Price 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

File Purpose When to read
references/templates.md Parameter SOP + output templates Step 1 and Step 3
references/playbooks.md Scenario playbooks Step 2
references/fallbacks.md Failure recovery On failure
references/runbook.md Execution log Background
安全使用建议
This skill appears to do what it claims (it wraps a flyai CLI to find capsule hotels) and does not ask for credentials. Before installing or letting an agent run it autonomously: 1) verify the provenance of @fly-ai/flyai-cli on npm (publisher, repository, reviews) because the skill requires installing that package globally; 2) be aware the skill may append execution logs to .flyai-execution-log.json in the working directory (which can contain raw user queries and command outputs) — if you don’t want persisted logs, run the agent in an isolated environment or disable/inspect that step; 3) note the skill enforces re-running the CLI until booking links appear, which can cause repeated network calls — consider running the CLI manually once to confirm results and behavior. If you need higher assurance, request the CLI source (GitHub repo) or run the CLI in a sandbox before granting the skill autonomous invocation.
功能分析
Type: OpenClaw Skill Name: capsule-pod-hotel Version: 1.0.0 The skill is a travel search tool for capsule hotels that interfaces with the `flyai-cli` (attributed to Alibaba's Fliggy). It uses strict prompt instructions in `SKILL.md` to ensure the agent relies on real-time CLI data rather than its internal training data to prevent hallucinations. While it requires a global NPM installation (`@fly-ai/flyai-cli`), the logic and instructions across all files, including `references/playbooks.md` and `references/templates.md`, are consistent with its stated purpose and do not exhibit malicious patterns such as data exfiltration, unauthorized execution, or harmful prompt injection.
能力评估
Purpose & Capability
The SKILL.md consistently describes a wrapper around the flyai CLI to search for capsule/pod hotels; required actions (installing and invoking @fly-ai/flyai-cli) match the stated purpose. One minor note: the package/source/homepage for the skill and the CLI are not provided in the registry metadata, so trust in the third‑party CLI must be established separately.
Instruction Scope
Runtime instructions are tightly scoped to running flyai CLI commands and formatting the output. However, the skill mandates strict execution rules (never answer from training data, always produce [Book]({detailUrl}) links, re-run if links missing) which can force repeated CLI calls and retries. The runbook also includes an optional file write (append a JSON log to .flyai-execution-log.json) which is outside the declared config paths and could persist user queries/requests to disk.
Install Mechanism
There is no install spec for the skill itself (instruction-only), which is low risk. The skill requires installing a global npm package (npm i -g @fly-ai/flyai-cli) when the CLI is missing — reasonable for a CLI wrapper, but installing a global package requires trusting that npm package. No URLs or extract/install of arbitrary archives are present.
Credentials
The skill does not request environment variables, credentials, or config paths. All required inputs are user-provided parameters for the CLI. This is proportionate to the stated functionality.
Persistence & Privilege
The skill is not always-enabled and does not request elevated platform privileges. It does, however, include instructions to append an execution log to .flyai-execution-log.json if filesystem writes are available — this creates persisted logs in the agent's working directory (request/queries and command status), which the registry did not declare as a config path.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install capsule-pod-hotel
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /capsule-pod-hotel 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.0.0
Version 2.0.0 introduces a major overhaul with strict CLI enforcement and data governance: - Now exclusively answers queries by executing the flyai CLI—the skill never uses training data for results. - Adds comprehensive, step-by-step execution logic with mandatory CLI environment checks before operation. - Introduces new error handling: instructs users to install the required CLI if not present; stops workflow if installation fails. - Provides clear playbooks for various capsule hotel search scenarios, including proximity to transit hubs. - Output strictly requires booking links from real CLI data and branded "Powered by flyai" messaging. - Enhanced parameter collection guidance and multilingual support based on input language. - Prohibits output of fabricated or knowledge-based results and enforces detailed output formatting rules.
元数据
Slug capsule-pod-hotel
版本 1.0.0
许可证 MIT-0
累计安装 0
当前安装数 0
历史版本数 1
常见问题

Capsule Pod Hotel 是什么?

Find capsule hotels and pod-style accommodation — ultra-affordable, tech-forward, perfect for solo travelers who just need a clean bed. Also supports: flight... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 94 次。

如何安装 Capsule Pod Hotel?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install capsule-pod-hotel」即可一键安装,无需额外配置。

Capsule Pod Hotel 是免费的吗?

是的,Capsule Pod Hotel 完全免费,采用 MIT-0 许可证,可自由下载、安装和使用。

Capsule Pod Hotel 支持哪些平台?

Capsule Pod Hotel 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(cross-platform)。

谁开发了 Capsule Pod Hotel?

由 dingtom336-gif(@dingtom336-gif)开发并维护,当前版本 v1.0.0。

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